Relatedness between the two-component lantibiotics lacticin 3147 and staphylococcin C55 based on structure, genetics and biological activity

BACKGROUND: Two component lantibiotics, such as the plasmid-encoded lacticin 3147 produced by Lactococcus lactis DPC3147 and staphylococcin C55 produced by Staphylococcus aureus C55, represent an emerging subgroup of bacteriocins. These two bacteriocins are particularly closely related, exhibiting 86% (LtnA1 and C55α) and 55% (LtnA2 and C55β) identity in their component peptides. The aim of this study was to investigate, for the first time for any two component bacteriocins, the significance of the relatedness between these two systems. RESULTS: So close is this relatedness that the hybrid peptide pairs LtnA1:C55β and C55α:LtnA2 were found to have activities in the single nanomolar range, comparing well with the native pairings. To determine whether this flexibility extended to the associated post-translational modification/processing machinery, the staphylococcin C55 structural genes were directly substituted for their lacticin 3147 counterparts in the ltn operon on the large conjugative lactococcal plasmid pMRC01. It was established that the lacticin LtnA1 post-translational and processing machinery could produce functionally active C55α, but not C55β. In order to investigate in closer detail the significance of the differences between LtnA1 and C55α, three residues in LtnA1 were replaced with the equivalent residues in C55α. Surprisingly, one such mutant LtnA1-Leu21Ala was not produced. This may be significant given the positioning of this residue in a putative lipid II binding loop. CONCLUSION: It is apparent, despite sharing striking similarities in terms of structure and activity, that these two complex bacteriocins display some highly dedicated features particular to either system

Salivaricin G32, a Homolog of the Prototype Streptococcus pyogenes

Salivaricin G32, a 2667 Da novel member of the SA-FF22 cluster of lantibiotics, has been purified and characterized from Streptococcus salivarius strain G32. The inhibitory peptide differs from the Streptococcus pyogenes—produced SA-FF22 in the absence of lysine in position 2. The salivaricin G32 locus was widely distributed in BLIS-producing S. salivarius, with 6 (23%) of 26 strains PCR-positive for the structural gene, slnA. As for most other lantibiotics produced by S. salivarius, the salivaricin G32 locus can be megaplasmid encoded. Another member of the SA-FF22 family was detected in two Streptococcus dysgalactiae of bovine origin, an observation supportive of widespread distribution of this lantibiotic within the genus Streptococcus. Since the inhibitory spectrum of salivaricin G32 includes Streptococcus pyogenes, its production by S. salivarius, either as a member of the normal oral microflora or as a commercial probiotic, could serve to enhance protection of the human host against S. pyogenes infection

Temporal Modulation of Traveling Waves in the Flow Between Rotating Cylinders With Broken Azimuthal Symmetry

The effect of temporal modulation on traveling waves in the flows in two distinct systems of rotating cylinders, both with broken azimuthal symmetry, has been investigated. It is shown that by modulating the control parameter at twice the critical frequency one can excite phase-locked standing waves and standing-wave-like states which are not allowed when the system is rotationally symmetric. We also show how previous theoretical results can be extended to handle patterns such as these, that are periodic in two spatial direction.Comment: 17 pages in LaTeX, 22 figures available as postscript files from http://www.esam.nwu.edu/riecke/lit/lit.htm

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

Design and construction of the MicroBooNE Cosmic Ray Tagger system

The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the detector records many cosmic muon tracks in each beam-related detector trigger that can be misidentified as signals of interest. To reduce these cosmogenic backgrounds, we have designed and constructed a TPC-external Cosmic Ray Tagger (CRT). This sub-system was developed by the Laboratory for High Energy Physics (LHEP), Albert Einstein center for fundamental physics, University of Bern. The system utilizes plastic scintillation modules to provide precise time and position information for TPC-traversing particles. Successful matching of TPC tracks and CRT data will allow us to reduce cosmogenic background and better characterize the light collection system and LArTPC data using cosmic muons. In this paper we describe the design and installation of the MicroBooNE CRT system and provide an overview of a series of tests done to verify the proper operation of the system and its components during installation, commissioning, and physics data-taking

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal

Determination of muon momentum in the MicroBooNE LArTPC using an improved model of multiple Coulomb scattering

We discuss a technique for measuring a charged particle's momentum by means of multiple Coulomb scattering (MCS) in the MicroBooNE liquid argon time projection chamber (LArTPC). This method does not require the full particle ionization track to be contained inside of the detector volume as other track momentum reconstruction methods do (range-based momentum reconstruction and calorimetric momentum reconstruction). We motivate use of this technique, describe a tuning of the underlying phenomenological formula, quantify its performance on fully contained beam-neutrino-induced muon tracks both in simulation and in data, and quantify its performance on exiting muon tracks in simulation. Using simulation, we have shown that the standard Highland formula should be re-tuned specifically for scattering in liquid argon, which significantly improves the bias and resolution of the momentum measurement. With the tuned formula, we find agreement between data and simulation for contained tracks, with a small bias in the momentum reconstruction and with resolutions that vary as a function of track length, improving from about 10% for the shortest (one meter long) tracks to 5% for longer (several meter) tracks. For simulated exiting muons with at least one meter of track contained, we find a similarly small bias, and a resolution which is less than 15% for muons with momentum below 2 GeV/c. Above 2 GeV/c, results are given as a first estimate of the MCS momentum measurement capabilities of MicroBooNE for high momentum exiting tracks

Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC

The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.Comment: 36 pages, 20 figure

Measurement of cosmic-ray reconstruction efficiencies in the MicroBooNE LArTPC using a small external cosmic-ray counter

The MicroBooNE detector is a liquid argon time projection chamber at Fermilab designed to study short-baseline neutrino oscillations and neutrino-argon interaction cross-section. Due to its location near the surface, a good understanding of cosmic muons as a source of backgrounds is of fundamental importance for the experiment. We present a method of using an external 0.5 m (L) x 0.5 m (W) muon counter stack, installed above the main detector, to determine the cosmic-ray reconstruction efficiency in MicroBooNE. Data are acquired with this external muon counter stack placed in three different positions, corresponding to cosmic rays intersecting different parts of the detector. The data reconstruction efficiency of tracks in the detector is found to be $\epsilon_{\mathrm{data}}=(97.1\pm0.1~(\mathrm{stat}) \pm 1.4~(\mathrm{sys}))\%$, in good agreement with the Monte Carlo reconstruction efficiency $\epsilon_{\mathrm{MC}} = (97.4\pm0.1)\%$. This analysis represents a small-scale demonstration of the method that can be used with future data coming from a recently installed cosmic-ray tagger system, which will be able to tag $\approx80\%$ of the cosmic rays passing through the MicroBooNE detector.Comment: 19 pages, 12 figure

A Deep Neural Network for Pixel-Level Electromagnetic Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber

We have developed a convolutional neural network (CNN) that can make a pixel-level prediction of objects in image data recorded by a liquid argon time projection chamber (LArTPC) for the first time. We describe the network design, training techniques, and software tools developed to train this network. The goal of this work is to develop a complete deep neural network based data reconstruction chain for the MicroBooNE detector. We show the first demonstration of a network's validity on real LArTPC data using MicroBooNE collection plane images. The demonstration is performed for stopping muon and a $\nu_\mu$ charged current neutral pion data samples