In vivo and in vitro characterization of Staphylococcus aureus and Bacillus subtilis polyglycerolphosphate lipoteichoic acid synthases

Staphylococcus aureus lipoteichoic acid (LTA) consists of a 1,3-linked polyglycerolphosphate chain retained in the bacterial membrane by a glycolipid anchor. The LTA backbone is produced by the lipoteichoic acid synthase LtaS, a membrane protein with five transmembrane helices and a large extracellular enzymatic domain (eLtaS). Proteomic studies revealed that LtaS is efficiently cleaved, and here it was demonstrated that the eLtaS domain is released into the culture supernatant as well as partially retained within the cell wall fraction. However, using an in vivo LtaS activity assay, it was shown that only the full-length LtaS enzyme is able to synthesize LTA. Neither expression of a secreted eLtaS variant, created by replacing the N-terminal membrane domain with a conventional signal sequence, nor expression of eLtaS fused to a single or multi-transmembrane domains of other staphylococcal proteins resulted in the production of LTA. These data indicate that the transmembrane domain of LtaS play an essential, yet unknown, role in LtaS enzyme function. In addition, the protease responsible for LtaS cleavage was identified. It was found that a S. aureus strain in which the gene encoding for the essential signal peptidase SpsB was cloned under inducible expression control showed an accumulation of the full-length LtaS enzyme in the absence of the inducer. These data suggest that SpsB is involved in LtaS cleavage. Four LtaS orthologues, YflE, YfnI, YqgS and YvgJ, are present in Bacillus subtilis. Using an in vitro enzyme assay and purified protein, it was determined that all four B. subtilis proteins are Mn2+-dependent metal enzymes that use the lipid phosphatidylglycerol as substrate. It was shown that YflE, YfnI and YqgS are bonafide LTA synthases capable of producing polyglycerolphosphate chains, while YvgJ appears to function as an LTA primase, as indicated by the accumulation of a glycolipid with the expected chromatographic mobility of GroP-Glc2-DAG. Taken together, experimental evidence for the enzyme function of all four B. subtilis LtaStype proteins is provided in this work and it was shown that all four enzymes are involved in the LTA synthesis process

Separable Cosparse Analysis Operator Learning

The ability of having a sparse representation for a certain class of signals has many applications in data analysis, image processing, and other research fields. Among sparse representations, the cosparse analysis model has recently gained increasing interest. Many signals exhibit a multidimensional structure, e.g. images or three-dimensional MRI scans. Most data analysis and learning algorithms use vectorized signals and thereby do not account for this underlying structure. The drawback of not taking the inherent structure into account is a dramatic increase in computational cost. We propose an algorithm for learning a cosparse Analysis Operator that adheres to the preexisting structure of the data, and thus allows for a very efficient implementation. This is achieved by enforcing a separable structure on the learned operator. Our learning algorithm is able to deal with multidimensional data of arbitrary order. We evaluate our method on volumetric data at the example of three-dimensional MRI scans.Comment: 5 pages, 3 figures, accepted at EUSIPCO 201

Learning Co-Sparse Analysis Operators with Separable Structures

In the co-sparse analysis model a set of filters is applied to a signal out of the signal class of interest yielding sparse filter responses. As such, it may serve as a prior in inverse problems, or for structural analysis of signals that are known to belong to the signal class. The more the model is adapted to the class, the more reliable it is for these purposes. The task of learning such operators for a given class is therefore a crucial problem. In many applications, it is also required that the filter responses are obtained in a timely manner, which can be achieved by filters with a separable structure. Not only can operators of this sort be efficiently used for computing the filter responses, but they also have the advantage that less training samples are required to obtain a reliable estimate of the operator. The first contribution of this work is to give theoretical evidence for this claim by providing an upper bound for the sample complexity of the learning process. The second is a stochastic gradient descent (SGD) method designed to learn an analysis operator with separable structures, which includes a novel and efficient step size selection rule. Numerical experiments are provided that link the sample complexity to the convergence speed of the SGD algorithm.Comment: 11 pages double column, 4 figures, 3 table

An algorithm for sums of squares of real polynomials

AbstractWe present an algorithm to determine if a real polynomial is a sum of squares (of polynomials), and to find an explicit representation if it is a sum of squares. This algorithm uses the fact that a sum of squares representation of a real polynomial corresponds to a real, symmetric, positive semi-definite matrix whose entries satisfy certain linear equations

Tabakentwöhnung in der erwachsenen Allgemeinbevölkerung : Evaluation eines internetbasierten Ausstiegsprogramms für Raucher.

Wörmann M. Tabakentwöhnung in der erwachsenen Allgemeinbevölkerung : Evaluation eines internetbasierten Ausstiegsprogramms für Raucher. Bielefeld: Universitätsbibliothek Bielefeld; 2014

Aspects of nonequilibrium in Leptogenesis

Wörmann M. Aspects of nonequilibrium in Leptogenesis. Bielefeld: Universität Bielefeld; 2016

Non-relativistic leptogenesis

Bödeker D, Wörmann M. Non-relativistic leptogenesis. Journal of Cosmology and Astroparticle Physics. 2014;2014(02):016.In many phenomenologically interesting models of thermal leptogenesis the heavy neutrinos are non-relativistic when they decay and produce the baryon asymmetry of the Universe. We propose a non-relativistic approximation for the corresponding rate equations in the non-resonant case, and a systematic way for computing relativistic corrections. We determine the leading order coefficients in these equations, and the first relativistic corrections. The non-relativistic approximation works remarkably well. It appears to be consistent with results obtained using a Boltzmann equation taking into account the momentum distribution of the heavy neutrinos, while being much simpler. We also compute radiative corrections to some of the coefficients in the rate equations. Their effect is of order 1% in the regime favored by neutrino oscillation data. We obtain the correct leading order lepton number washout rate in this regime, which leads to large (~ 20%) effects compared to previous computations