Purification, Cloning, Characterization and Essential Amino Acid Residues Analysis of a New iota-Carrageenase from Cellulophaga sp QY3

ι-Carrageenases belong to family 82 of glycoside hydrolases that degrade sulfated galactans in the red algae known as ι-carrageenans. The catalytic mechanism and some substrate-binding residues of family GH82 have been studied but the substrate recognition and binding mechanism of this family have not been fully elucidated. We report here the purification, cloning and characterization of a new ι-carrageenase CgiA_Ce from the marine bacterium Cellulophaga sp. QY3. CgiA_Ce was the most thermostable carrageenase described so far. It was most active at 50°C and pH 7.0 and retained more than 70% of the original activity after incubation at 50°C for 1 h at pH 7.0 or at pH 5.0–10.6 for 24 h. CgiA_Ce was an endo-type ι-carrageenase; it cleaved ι-carrageenan yielding neo-ι-carrabiose and neo-ι-carratetraose as the main end products, and neo-ι-carrahexaose was the minimum substrate. Sequence analysis and structure modeling showed that CgiA_Ce is indeed a new member of family GH82. Moreover, sequence analysis of ι-carrageenases revealed that the amino acid residues at subsites −1 and +1 were more conserved than those at other subsites. Site-directed mutagenesis followed by kinetic analysis identified three strictly conserved residues at subsites −1 and +1 of ι-carrageenases, G228, Y229 and R254 in CgiA_Ce, which played important roles for substrate binding. Furthermore, our results suggested that Y229 and R254 in CgiA_Ce interacted specifically with the sulfate groups of the sugar moieties located at subsites −1 and +1, shedding light on the mechanism of ι-carrageenan recognition in the family GH82

A linear programming-based method for job shop scheduling

We present a decomposition heuristic for a large class of job shop scheduling problems. This heuristic utilizes information from the linear programming formulation of the associated optimal timing problem to solve subproblems, can be used for any objective function whose associated optimal timing problem can be expressed as a linear program (LP), and is particularly effective for objectives that include a component that is a function of individual operation completion times. Using the proposed heuristic framework, we address job shop scheduling problems with a variety of objectives where intermediate holding costs need to be explicitly considered. In computational testing, we demonstrate the performance of our proposed solution approach

Toll-Like Receptor 3 (TLR3) Plays a Major Role in the Formation of Rabies Virus Negri Bodies

Human neurons express the innate immune response receptor, Toll-like receptor 3 (TLR3). TLR3 levels are increased in pathological conditions such as brain virus infection. Here, we further investigated the production, cellular localisation, and function of neuronal TLR3 during neuronotropic rabies virus (RABV) infection in human neuronal cells. Following RABV infection, TLR3 is not only present in endosomes, as observed in the absence of infection, but also in detergent-resistant perinuclear inclusion bodies. As well as TLR3, these inclusion bodies contain the viral genome and viral proteins (N and P, but not G). The size and composition of inclusion bodies and the absence of a surrounding membrane, as shown by electron microscopy, suggest they correspond to the previously described Negri Bodies (NBs). NBs are not formed in the absence of TLR3, and TLR3−/− mice—in which brain tissue was less severely infected—had a better survival rate than WT mice. These observations demonstrate that TLR3 is a major molecule involved in the spatial arrangement of RABV–induced NBs and viral replication. This study shows how viruses can exploit cellular proteins and compartmentalisation for their own benefit

The eEF1γ Subunit Contacts RNA Polymerase II and Binds Vimentin Promoter Region

Here, we show that the eukaryotic translation elongation factor 1 gamma (eEF1γ) physically interacts with the RNA polymerase II (pol II) core subunit 3 (RPB3), both in isolation and in the context of the holo-enzyme. Importantly, eEF1γ has been recently shown to bind Vimentin mRNA. By chromatin immunoprecipitation experiments, we demonstrate, for the first time, that eEF1γ is also physically present on the genomic locus corresponding to the promoter region of human Vimentin gene. The eEF1γ depletion causes the Vimentin protein to be incorrectly compartmentalised and to severely compromise cellular shape and mitochondria localisation. We demonstrate that eEF1γ partially colocalises with the mitochondrial marker Tom20 and that eEF1γ depletion increases mitochondrial superoxide generation as well as the total levels of carbonylated proteins. Finally, we hypothesise that eEF1γ, in addition to its role in translation elongation complex, is involved in regulating Vimentin gene by contacting both pol II and the Vimentin promoter region and then shuttling/nursing the Vimentin mRNA from its gene locus to its appropriate cellular compartment for translation

Multiple-machine lower bounds for shop-scheduling problems

In order to compute lower bounds for shop scheduling problems, a lot of attention has been paid to adjustment techniques based on one-machine relaxations. We present such a new technique but, following the observation that machines are connected to each other through precedence constraints, we also study techniques that are based on the combination of precedence constraints and disjunctive constraints between operations that are processed on different machines. A computational study of the effectiveness of these new techniques is performed on job-shop and flow-shop instances

Scheduling with tails and deadlines

This paper discusses scheduling problems that combine tails and deadlines or, equivalently, due dates and deadlines. This approach is illustrated to be of practical interest to strengthen some lower bounds in shop scheduling problems. We show that both deadlines and tails can efficiently be modelled via a non-decreasing cost function of the completion time so that we can use the O(n2) algorithm due to Baker, Lawler, Lenstra and Rinnooy Kan for the 1pmtn,prec,rj,fmax problem to solve 1pmtn,prec,rj,dj,qjCmax. For this problem, we present an algorithm with improved complexity of O(e+nlogn) where e is the number of precedence constraints and we present some extensions of this algorithm to solve two parallel machine problems with unit execution time operations

A DFO technique to calibrate queueing models

A crucial step in the modeling of a system is to determine the values of the parameters to use in the model. In this paper we assume that we have a set of measurements collected from an operational system, and that an appropriate model of the system (e.g., based on queueing theory) has been developed. Not infrequently proper values for certain parameters of this model may be difficult to estimate from available data (because the corresponding parameters have unclear physical meaning or because they cannot be directly obtained from available measurements, etc.). Hence, we need a technique to determine the missing parameter values, i.e., to calibrate the model. As an alternative to unscalable "brute force" technique, we propose to view model calibration as a nonlinear optimization problem with constraints. The resulting method is conceptually simple and easy to implement. Our contribution is twofold. First, we propose improved definitions of the "objective function" to quantify the "distance" between performance indices produced by the model and the values obtained from measurements. Second, we develop a customized derivative-free optimization (DFO) technique whose original feature is the ability to allow temporary constraint violations. This technique allows us to solve this optimization problem accurately, thereby providing the "right" parameter values. We illustrate our method using two simple real-life case studies