Elevated levels of tumor necrosis factor alpha (TNF-alpha) in human immunodeficiency virus type 1-transgenic mice: prevention of death by antibody to TNF-alpha

Homozygous human immunodeficiency virus type 1 (HIV-1)-transgenic mice (Tg26) appear normal at birth but die within 3 to 4 weeks. The skin of these animals shows diffuse scaling and high-level expression of both HIV-1 mRNA and gp120. Previous experiments showed that treatment with human chorionic gonadatropin (hCG) prevented death and the expression of HIV-1 mRNA and gp120. The present experiments were initiated to study the role of tumor necrosis factor alpha (TNF-alpha) in HIV-1-induced pathology. Examination of the sera of Tg26 mice revealed a 50-fold increase in TNF-alpha levels compared to those in nontransgenic mice. Treatment with antibody to TNF-alpha prevented death, resulted in near normal growth, and produced a marked decrease in skin lesions and a profound reduction in the expression of HIV-1 mRNA and gp120. Both TNF-alpha antibody and hCG reduced TNF-alpha levels in sera by approximately 75%. We conclude that TNF-alpha contributes in a major way to HIV-1-induced pathology in transgenic mice and that both hCG and antibody to TNF-alpha prevent the development of pathology by suppressing the level of TNF-alpha.     

Systematic variation of amino acid substitutions for stringent assessment of pairwise covariation

During protein evolution, amino acids change due to a combination of functional constraints and genetic drift. Proteins frequently contain pairs of amino acids that appear to change together (covariation). Analysis of covariation from naturally occurring sets of orthologs cannot distinguish between residue pairs retained by functional requirements of the protein and those pairs existing due to changes along a common evolutionary path. Here, we have separated the two types of covariation by independently recombining every naturally occurring amino acid variant within a set of 15 subtilisin orthologs. Our analysis shows that in this family of subtilisin orthologs, almost all possible pairwise combinations of amino acids can coexist. This suggests that amino acid covariation found in the subtilisin orthologs is almost entirely due to common ancestral origin of the changes rather than functional constraints. We conclude that naturally occurring sequence diversity can be used to identify positions that can vary independently without destroying protein function.     

Environmental contaminants and the prevalence of hemic neoplasia (leukemia) in the common mussel (Mytilus edulis complex) from Puget Sound, Washington, U.S.A

The relationship between hemic neoplasia, a blood cell disorder in bivalve molluscs, and chemical contaminants was evaluated in the common mussel (Mytilus edulis complex). Hemic neoplasia (HN) is endemic to mussel populations in Puget Sound. The prevalence of hemic neoplasia ranged from 0 to 30% in mussels from nine sites in Puget Sound, Washington. Organic chemical contamination in sediment from these sites range from 0.1 to 64.0 ppm of polycyclic aromatic hydrocarbons (PAHs) and 0.07 to 0.50 ppm chlorinated hydrocarbons. No relationship between the body burden of environmental contaminants and the prevalence of HN in mussels was identified. To evaluate the short-term ability of chemical contaminants to induce HN in mussels, mussels, from a site where mussels were previously determined to be HN free, were fed microencapsulated PAHs (composed of a mixture of phenanthrene, flouranthene, and benzo[a]pyrene) or PCBs (Aroclor 1254) and the prevalence of HN was assessed after 30 days of exposure. Although an apparent increase in HN prevalence (20 to 30%) was observed in all treatments groups except the untreated controls, no significant difference in the prevalence of HN was observed between the control group of mussels fed corn oil (vehicle) and mussels fed either PAHs or PCBs in corn oil. A long-term (180-day) exposure study was conducted to evaluate the influence of PAHs or PCBs in modulating the prevalence of HN in a mussel population already exhibiting a moderate HN prevalence. Mussels, from a site where mussels were previously determined to exhibit a background prevalence of HN, fed microencapsulated PAHs, PCBs, and corn oil (vehicle) over a long time period (180 days), revealed an apparent increased prevalence of HN (30 to 40%) above the low levels (20%) initially present. However, no significant difference in the prevalence of HN was observed between the control group of mussels fed corn oil (vehicle) and mussels fed either PAHs or PCBs in corn oil. Although chemical contaminants have been proposed as a modulating factor in the development and promotion of HN in bivalve molluscs from environmentally stressed and degraded habitats, we find no evidence that chemical contaminants induce or promote the development of HN in the mussel M. edulis complex.     

Camptothecin analogs with bulky, hydrophobic substituents at the 7-position via a Grignard reaction

By developing a new synthetic procedure for introduction of side chains onto the camptothecin ring system, we were able to achieve the preparation of a number of analogs bearing bulky, hydrophobic groups directly attached to the 7-position. These include 7-tert-butylcamptothecin, 7-benzylcamptothecin and the corresponding 10,11-methylenedioxycamptothecins. This method involves the reaction of an appropriate orthoaminobenzonitrile with various Grignard reagents to give the corresponding orthoaminoketones. Friedlander condensation of the latter with the key tricyclic ketone leads to 7-substituted camptothecin analogs. We report the activity of these compounds as topoisomerase I poisons and their ability to inhibit growth of selected tumor cell lines.     

The adaptive evolution database (TAED)

Background

The Master Catalog is a collection of evolutionary families, including multiple sequence alignments, phylogenetic trees and reconstructed ancestral sequences, for all protein-sequence modules encoded by genes in GenBank. It can therefore support large-scale genomic surveys, of which we present here The Adaptive Evolution Database (TAED). In TAED, potential examples of positive adaptation are identified by high values for the normalized ratio of nonsynonymous to synonymous nucleotide substitution rates (K_A/K_S values) on branches of an evolutionary tree between nodes representing reconstructed ancestral sequences.

Results

Evolutionary trees and reconstructed ancestral sequences were extracted from the Master Catalog for every subtree containing proteins from the Chordata only or the Embryophyta only. Branches with high K_A/K_S values were identified. These represent candidate episodes in the history of the protein family when the protein may have undergone positive selection, where the mutant form conferred more fitness than the ancestral form. Such episodes are frequently associated with change in function. An unexpectedly large number of families (between 10% and 20% of those families examined) were found to have at least one branch with high K_A/K_S values above arbitrarily chosen cut-offs (1 and 0.6). Most of these survived a robustness test and were collected into TAED.

Conclusions

TAED is a raw resource for bioinformaticists interested in data mining and for experimental evolutionists seeking candidate examples of adaptive evolution for further experimental study. It can be expanded to include other evolutionary information (for example changes in gene regulation or splicing) placed in a phylogenetic perspective.     

Optimal local propensities for model proteins

Lattice models of proteins were used to examine the role of local propensities in stabilizing the native state of a protein, using techniques drawn from spin-glass theory to characterize the free-energy landscapes. In the strong evolutionary limit, optimal conditions for folding are achieved when the contributions from local interactions to the stability of the native state is small. Further increasing the local interactions rapidly decreases the foldability. © 1995 Wiley-Liss, Inc.     

A clustered plasticity model of long-term memory engrams

Long-term memory and its putative synaptic correlates the late phases of both long-term potentiation and long-term depression require enhanced protein synthesis. On the basis of recent data on translation-dependent synaptic plasticity and on the supralinear effect of activation of nearby synapses on action potential generation, we propose a model for the formation of long-term memory engrams at the single neuron level. In this model, which we call clustered plasticity, local translational enhancement, along with synaptic tagging and capture, facilitates the formation of long-term memory engrams through bidirectional synaptic weight changes among synapses within a dendritic branch.     

Effects of turbulence on the feeding rate of a pelagic predator: The planktonic hydroid Clytia gracilis

Relatively little is known about the role of turbulence in a predator-prey system where the predator is a passive, pelagic forager. The Campanulariid hydroid Clytia gracilis (Cnidaria, Hydrozoa) is unusual because it occurs as planktonic colonies and is reported to forage passively in the water column on Georges Bank, Massachusetts, USA. In this study, we investigated the role of various turbulence conditions on the feeding rate of C. gracilis colonies in laboratory experiments. We found a positive relationship between turbulence velocities and feeding rates up to a turbulent energy dissipation rate of ca. 1 cm² s^− 3. Beyond this threshold feeding rate decreased slightly, indicating a dome-shaped relationship. Additionally, a negative relationship was found between feeding efficiency and hydroid colony size under lower turbulent velocities, but this trend was not significant under higher turbulence regimes.     

Engineering proteinase K using machine learning and synthetic genes

Background  

Altering a protein's function by changing its sequence allows natural proteins to be converted into useful molecular tools. Current protein engineering methods are limited by a lack of high throughput physical or computational tests that can accurately predict protein activity under conditions relevant to its final application. Here we describe a new synthetic biology approach to protein engineering that avoids these limitations by combining high throughput gene synthesis with machine learning-based design algorithms.