"PP2C7s", Genes Most Highly Elaborated in Photosynthetic Organisms,Reveal the Bacterial Origin and Stepwise Evolution of PPM/PP2C Protein Phosphatases

Mg⁺²/Mn⁺²-dependent type 2C protein phosphatases (PP2Cs) are ubiquitous in eukaryotes, mediating diverse cellular signaling processes through metal ion catalyzed dephosphorylation of target proteins. We have identified a distinct PP2C sequence class (“PP2C7s”) which is nearly universally distributed in Eukaryotes, and therefore apparently ancient. PP2C7s are by far most prominent and diverse in plants and green algae. Combining phylogenetic analysis, subcellular localization predictions, and a distillation of publically available gene expression data, we have traced the evolutionary trajectory of this gene family in photosynthetic eukaryotes, demonstrating two major sequence assemblages featuring a succession of increasingly derived sub-clades. These display predominant expression moving from an ancestral pattern in photosynthetic tissues toward non-photosynthetic, specialized and reproductive structures. Gene co-expression network composition strongly suggests a shifting pattern of PP2C7 gene functions, including possible regulation of starch metabolism for one homologue set in Arabidopsis and rice. Distinct plant PP2C7 sub-clades demonstrate novel amino terminal protein sequences upon motif analysis, consistent with a shifting pattern of regulation of protein function. More broadly, neither the major events in PP2C sequence evolution, nor the origin of the diversity of metal binding characteristics currently observed in different PP2C lineages, are clearly understood. Identification of the PP2C7 sequence clade has allowed us to provide a better understanding of both of these issues. Phylogenetic analysis and sequence comparisons using Hidden Markov Models strongly suggest that PP2Cs originated in Bacteria (Group II PP2C sequences), entered Eukaryotes through the ancestral mitochondrial endosymbiosis, elaborated in Eukaryotes, then re-entered Bacteria through an inter-domain gene transfer, ultimately producing bacterial Group I PP2C sequences. A key evolutionary event, occurring first in ancient Eukaryotes, was the acquisition of a conserved aspartate in classic Motif 5. This has been inherited subsequently by PP2C7s, eukaryotic PP2Cs and bacterial Group I PP2Cs, where it is crucial to the formation of a third metal binding pocket, and catalysis.     

An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions,Information Flow,and Peer-To-Peer Networks

Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner’s management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of ‘harvest readiness’ and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior.     

Designing Cell-Targeted Therapeutic Proteins Reveals the Interplay between Domain Connectivity and Cell Binding

The therapeutic efficacy of cytokines is often hampered by severe side effects due to their undesired binding to healthy cells. One strategy for overcoming this obstacle is to tether cytokines to antibodies or antibody fragments for targeted cell delivery. However, how to modulate the geometric configuration and relative binding affinity of the two domains for optimal activity remains an outstanding question. As a result, many antibody-cytokine complexes do not achieve the desired level of cell-targeted binding and activity. Here, we address these design issues by developing a computational model to simulate the dynamics and binding kinetics of natural and engineered fusion proteins such as antibody-cytokine complexes. To verify the model, we developed a modular system in which an antibody fragment and a cytokine are conjugated via a DNA linker that allows for programmable linker geometry and protein spatial configuration. By assembling and testing several anti-CD20 antibody fragment-interferon α complexes, we showed that varying the linker length and cytokine binding affinity controlled the magnitude of cell-targeted signaling activation in a manner that agreed with the model predictions, which were expressed as dose-signaling response curves. The simulation results also revealed that there is a range of cytokine binding affinities that would achieve optimal therapeutic efficacy. This rapid prototyping platform will facilitate the rational design of antibody-cytokine complexes for improved therapeutic outcomes.     

Estimating Haplotype Effects for Survival Data

Summary Genetic association studies often investigate the effect of haplotypes on an outcome of interest. Haplotypes are not observed directly, and this complicates the inclusion of such effects in survival models. We describe a new estimating equations approach for Cox's regression model to assess haplotype effects for survival data. These estimating equations are simple to implement and avoid the use of the EM algorithm, which may be slow in the context of the semiparametric Cox model with incomplete covariate information. These estimating equations also lead to easily computable, direct estimators of standard errors, and thus overcome some of the difficulty in obtaining variance estimators based on the EM algorithm in this setting. We also develop an easily implemented goodness‐of‐fit procedure for Cox's regression model including haplotype effects. Finally, we apply the procedures presented in this article to investigate possible haplotype effects of the PAF‐receptor on cardiovascular events in patients with coronary artery disease, and compare our results to those based on the EM algorithm.     

Microbial arsenic: from geocycles to genes and enzymes

Arsenic compounds have been abundant at near toxic levels in the environment since the origin of life. In response, microbes have evolved mechanisms for arsenic resistance and enzymes that oxidize As(III) to As(V) or reduce As(V) to As(III). Formation and degradation of organoarsenicals, for example methylarsenic compounds, occur. There is a global arsenic geocycle, where microbial metabolism and mobilization (or immobilization) are important processes. Recent progress in studies of the ars operon (conferring resistance to As(III) and As(V)) in many bacterial types (and related systems in Archaea and yeast) and new understanding of arsenite oxidation and arsenate reduction by respiratory-chain-linked enzyme complexes has been substantial. The DNA sequencing and protein crystal structures have established the convergent evolution of three classes of arsenate reductases (that is classes of arsenate reductases are not of common evolutionary origin). Proposed reaction mechanisms in each case involve three cysteine thiols and S-As bond intermediates, so convergent evolution to similar mechanisms has taken place.     

Mercury resistance in a plasmid-bearing strain of Escherichia coli

A strain of Escherichia coli carrying genes determining mercury resistance on a naturally occurring resistance transfer factor (RTF) converts 95% of 10(-5)m Hg(2+) (chloride) to metallic mercury at a rate of 4 to 5 nmoles of Hg(2+) per min per 10(8) cells. The metallic mercury is rapidly eliminated from the culture medium as mercury vapor. The volatilizing activity has a temperature dependence and heat sensitivity characteristic of enzymatic catalysis and is inducible by mercuric chloride. Ag(+) and Au(3+) are markedly inhibitory of mercury volatilization.     

The membrane proteins of the methanol-induced peroxisome of Candida boidinii. Initial characterization and generation of monoclonal antibodies

Peroxisomes are massively induced when methylotrophic yeasts are cultured on methanol as the sole carbon and energy source. An analysis of the protein composition of the peroxisomal membrane and the generation of probes against two peroxisomal membrane proteins (PMPs) have been undertaken. Peroxisomes from Candida boidinii were obtained from sucrose gradients as previously described or from a novel one-step purification of the organelle on a Percoll gradient. The protein composition of the membranes from these two preparations was virtually identical. About 10 proteins comprise nearly all of its protein mass. The most prominent proteins have molecular masses of 120, 100, 47, 31-32 (a triplet), and 20 kDa; significant amounts of alcohol oxidase and dihydroxyacetone synthase, the two abundant matrix proteins, also remain associated with the membrane. Glycosylation of the membrane proteins could not be detected. Exposure of the membrane to chaotropes shows that PMPs 100 and 20 are the most easily removable, whereas PMP 47 appears to be the most tightly associated. Mice were injected with peroxisomal membrane, and hybridoma lines were isolated that produced antibody against PMP 20, PMP 47, and dihydroxyacetone synthase. Indirect immunofluorescence with these monoclonal antibodies confirmed that all three proteins are localized to the peroxisomal cluster. Immunoblotting experiments demonstrated that peroxisomal membrane as well as matrix proteins are induced by methanol.     

Repeated H2O2 exposure drives cell cycle progression in an in vitro model of ulcerative colitis

The production of hydrogen peroxide (H₂O₂) drives tumourigenesis in ulcerative colitis (UC). Recently, we showed that H₂O₂ activates DNA damage checkpoints in human colonic epithelial cells (HCEC) through c‐Jun N‐terminal Kinases (JNK) that induces p21^WAF1. Moreover, caspases circumvented the G1/S and intra‐S checkpoints, and cells accumulated in G2/M. The latter observation raised the question of whether repeated H₂O₂ exposures alter JNK activation, thereby promoting a direct passage of cells from G2/M arrest to driven cell cycle progression. Here, we report that increased proliferation of repeatedly H₂O₂‐exposed HCEC cells (C‐cell cultures) was associated with (i) increased phospho‐p46 JNK, (ii) decreased total JNK and phospho‐p54 JNK and (iii) p21^WAF1 down‐regulation. Altered JNK activation and p21^WAF1 down‐regulation were accompanied by defects in maintaining G2/M and mitotic spindle checkpoints through adaptation, as well as by apoptosis resistance following H₂O₂ exposure. This may cause increased proliferation of C‐cell cultures, a defining initiating feature in the inflammation‐carcinoma pathway in UC. We further suggest that dysregulated JNK activation is attributed to a non‐apoptotic function of caspases, causing checkpoint adaptation in C‐cell cultures. Additionally, loss of cell‐contact inhibition and the overcoming of senescence, hallmarks of cancer, contributed to increased proliferation. Furthermore, there was evidence that p54 JNK inactivation is responsible for loss of cell‐contact inhibition. We present a cellular model of UC and suggest a sinusoidal pattern of proliferation, which is triggered by H₂O₂‐induced reactive oxygen species generation, involving an interplay between JNK activation/inactivation, p21^WAF1, c‐Fos, c‐Jun/phospho‐c‐Jun, ATF2/phospho‐ATF2, β‐catenin/TCF4‐signalling, c‐Myc, CDK6 and Cyclin D2, leading to driven cell cycle progression.