Backbone Solution Structures of Proteins Using Residual Dipolar Couplings: Application to a Novel Structural Genomics Target

Structural genomics (or proteomics) activities are critically dependent on the availability of high-throughput structure determination methodology. Development of such methodology has been a particular challenge for NMR based structure determination because of the demands for isotopic labeling of proteins and the requirements for very long data acquisition times. We present here a methodology that gains efficiency from a focus on determination of backbone structures of proteins as opposed to full structures with all sidechains in place. This focus is appropriate given the presumption that many protein structures in the future will be built using computational methods that start from representative fold family structures and replace as many as 70% of the sidechains in the course of structure determination. The methodology we present is based primarily on residual dipolar couplings (RDCs), readily accessible NMR observables that constrain the orientation of backbone fragments irrespective of separation in space. A new software tool is described for the assembly of backbone fragments under RDC constraints and an application to a structural genomics target is presented. The target is an 8.7 kDa protein from Pyrococcus furiosus, PF1061, that was previously not well annotated, and had a nearest structurally characterized neighbor with only 33% sequence identity. The structure produced shows structural similarity to this sequence homologue, but also shows similarity to other proteins, which suggests a functional role in sulfur transfer. Given the backbone structure and a possible functional link this should be an ideal target for development of modeling methods

Costs of task allocation with local feedback: Effects of colony size and extra workers in social insects and other multi-agent systems

Adaptive collective systems are common in biology and beyond. Typically, such systems require a task allocation algorithm: a mechanism or rule-set by which individuals select particular roles. Here we study the performance of such task allocation mechanisms measured in terms of the time for individuals to allocate to tasks. We ask: (1) Is task allocation fundamentally difficult, and thus costly? (2) Does the performance of task allocation mechanisms depend on the number of individuals? And (3) what other parameters may affect their efficiency? We use techniques from distributed computing theory to develop a model of a social insect colony, where workers have to be allocated to a set of tasks; however, our model is generalizable to other systems. We show, first, that the ability of workers to quickly assess demand for work in tasks they are not currently engaged in crucially affects whether task allocation is quickly achieved or not. This indicates that in social insect tasks such as thermoregulation, where temperature may provide a global and near instantaneous stimulus to measure the need for cooling, for example, it should be easy to match the number of workers to the need for work. In other tasks, such as nest repair, it may be impossible for workers not directly at the work site to know that this task needs more workers. We argue that this affects whether task allocation mechanisms are under strong selection. Second, we show that colony size does not affect task allocation performance under our assumptions. This implies that when effects of colony size are found, they are not inherent in the process of task allocation itself, but due to processes not modeled here, such as higher variation in task demand for smaller colonies, benefits of specialized workers, or constant overhead costs. Third, we show that the ratio of the number of available workers to the workload crucially affects performance. Thus, workers in excess of those needed to complete all tasks improve task allocation performance. This provides a potential explanation for the phenomenon that social insect colonies commonly contain inactive workers: these may be a ‘surplus’ set of workers that improves colony function by speeding up optimal allocation of workers to tasks. Overall our study shows how limitations at the individual level can affect group level outcomes, and suggests new hypotheses that can be explored empirically

High salt-tolerant protease from a potential biocontrol agent bacillus pumilus M3-16

In this paper, we investigate the characterization and evaluation of the antifungal protease activity from a halotolerant strain M3-16 of Bacillus pumilus, earlier isolated from a shallow salt lake in Tunisia. Protease enzyme was highly induced by the pathogen tested in vitro (27.4 U/ml). This is the first report on high salt-tolerant protease from B. pumilus, since it was active at high salinity (from 5 to 30% NaCl, w/v) as well as in the absence of salinity. This enzyme showed optimal activity at 60 °C and pH 8. At 80 °C and 30 min, the enzyme retained up to 91% and it showed stability over a wide pH range (from pH 5 to 11). The enzyme was found to be monomer with an estimated molecular mass of 31 kDa. The amino acid sequence showed high similarity (94%) to ATP-dependent protease from B. pumilus strain ATCC 7061. Thus, our alkaline thermostable and high salt-tolerant protease induced by a phytopathogenic fungus, could be useful for application in diverse areas such as biotechnology alimentary and agronomy industries