A functional screen identifies lateral transfer of beta-glucuronidase (gus) from bacteria to fungi

Lateral gene transfer (LGT) from prokaryotes to microbial eukaryotes is usually detected by chance through genome-sequencing projects. Here, we explore a different, hypothesis-driven approach. We show that the fitness advantage associated with the transferred gene, typically invoked only in retrospect, can be used to design a functional screen capable of identifying postulated LGT cases. We hypothesized that beta-glucuronidase (gus) genes may be prone to LGT from bacteria to fungi (thought to lack gus) because this would enable fungi to utilize glucuronides in vertebrate urine as a carbon source. Using an enrichment procedure based on a glucose-releasing glucuronide analog (cellobiouronic acid), we isolated two gus(+) ascomycete fungi from soils (Penicillium canescens and Scopulariopsis sp.). A phylogenetic analysis suggested that their gus genes, as well as the gus genes identified in genomic sequences of the ascomycetes Aspergillus nidulans and Gibberella zeae, had been introgressed laterally from high-GC gram(+) bacteria. Two such bacteria (Arthrobacter spp.), isolated together with the gus(+) fungi, appeared to be the descendants of a bacterial donor organism from which gus had been transferred to fungi. This scenario was independently supported by similar substrate affinities of the encoded beta-glucuronidases, the absence of introns from fungal gus genes, and the similarity between the signal peptide-encoding 5' extensions of some fungal gus genes and the Arthrobacter sequences upstream of gus. Differences in the sequences of the fungal 5' extensions suggested at least two separate introgression events after the divergence of the two main Euascomycete classes. We suggest that deposition of glucuronides on soils as a result of the colonization of land by vertebrates may have favored LGT of gus from bacteria to fungi in soils.

Gene transfer to plants by diverse species of bacteria

Agrobacterium is widely considered to be the only bacterial genus capable of transferring genes to plants. When suitably modified, Agrobacterium has become the most effective vector for gene transfer in plant biotechnology1. However, the complexity of the patent landscape2 has created both real and perceived obstacles to the effective use of this technology for agricultural improvements by many public and private organizations worldwide. Here we show that several species of bacteria outside the Agrobacterium genus can be modified to mediate gene transfer to a number of diverse plants. These plant-associated symbiotic bacteria were made competent for gene transfer by acquisition of both a disarmed Ti plasmid and a suitable binary vector. This alternative to Agrobacterium-mediated technology for crop improvement, in addition to affording a versatile ‘open source’ platform for plant biotechnology, may lead to new uses of natural bacteria– plant interactions to achieve plant transformation.

An egg apparatus-specific enhancer of Arabidopsis, identified by enhancer detection

Despite a central role in angiosperm reproduction, few gametophyte-specific genes and promoters have been isolated, particularly for the inaccessible female gametophyte (embryo sac). Using the Ds-based enhancer-detector line ET253, we have cloned an egg apparatus-specific enhancer (EASE) from Arabidopsis (Arabidopsis thaliana). The genomic region flanking the Ds insertion site was further analyzed by examining its capability to control gusA and GFP reporter gene expression in the embryo sac in a transgenic context. Through analysis of a 5' and 3' deletion series in transgenic Arabidopsis, the sequence responsible for egg apparatus-specific expression was delineated to 77 bp. Our data showed that this enhancer is unique in the Arabidopsis genome, is conserved among different accessions, and shows an unusual pattern of sequence variation. This EASE works independently of position and orientation in Arabidopsis but is probably not associated with any nearby gene, suggesting either that it acts over a large distance or that a cryptic element was detected. Embryo-specific ablation in Arabidopsis was achieved by transactivation of a diphtheria toxin gene under the control of the EASE. The potential application of the EASE element and similar control elements as part of an open-source biotechnology toolkit for apomixis is discussed.

Wide-baseline keypoint detection and matching with wide-angle images for vision based localisation

This thesis addresses the problem of detecting and describing the same scene points in different wide-angle images taken by the same camera at different viewpoints. This is a core competency of many vision-based localisation tasks including visual odometry and visual place recognition. Wide-angle cameras have a large field of view that can exceed a full hemisphere, and the images they produce contain severe radial distortion. When compared to traditional narrow field of view perspective cameras, more accurate estimates of camera egomotion can be found using the images obtained with wide-angle cameras. The ability to accurately estimate camera egomotion is a fundamental primitive of visual odometry, and this is one of the reasons for the increased popularity in the use of wide-angle cameras for this task. Their large field of view also enables them to capture images of the same regions in a scene taken at very different viewpoints, and this makes them suited for visual place recognition. However, the ability to estimate the camera egomotion and recognise the same scene in two different images is dependent on the ability to reliably detect and describe the same scene points, or ‘keypoints’, in the images. Most algorithms used for this purpose are designed almost exclusively for perspective images. Applying algorithms designed for perspective images directly to wide-angle images is problematic as no account is made for the image distortion. The primary contribution of this thesis is the development of two novel keypoint detectors, and a method of keypoint description, designed for wide-angle images. Both reformulate the Scale- Invariant Feature Transform (SIFT) as an image processing operation on the sphere. As the image captured by any central projection wide-angle camera can be mapped to the sphere, applying these variants to an image on the sphere enables keypoints to be detected in a manner that is invariant to image distortion. Each of the variants is required to find the scale-space representation of an image on the sphere, and they differ in the approaches they used to do this. Extensive experiments using real and synthetically generated wide-angle images are used to validate the two new keypoint detectors and the method of keypoint description. The best of these two new keypoint detectors is applied to vision based localisation tasks including visual odometry and visual place recognition using outdoor wide-angle image sequences. As part of this work, the effect of keypoint coordinate selection on the accuracy of egomotion estimates using the Direct Linear Transform (DLT) is investigated, and a simple weighting scheme is proposed which attempts to account for the uncertainty of keypoint positions during detection. A word reliability metric is also developed for use within a visual ‘bag of words’ approach to place recognition.

Quantitative PCR assay of sewage-associated Bacteroides markers to assess sewage pollution in an urban lake in Dhaka, Bangladesh

This paper aimed to assess the magnitude of sewage pollution in an urban lake in Dhaka, Bangladesh by using Quantitative PCR (qPCR) of sewage-associated Bacteroides HF183 markers. PCR was also used for the quantitative detection of ruminant wastewater-associated CF128 markers along with the enumeration of traditional fecal indicator bacteria, namely, enterococci. The number of enterococci in lake water samples ranged from 1.1 x 104 to 1.9 x 105 CFU/100 ml of water. From the 20 water samples tested, 14 (70%) and 7 (35%) were PCR positive for the HF183 and CF128 markers, respectively. The numbers of the HF183 and CF128 markers in lake water samples were 3.9 x 104 to 6.3 × 107 and 9.3 x 103 to 6.3 x 105 genomic units (GU)/100 ml of water, respectively. The high numbers of enterococci and the HF183 markers indicate sewage pollution and potential health risks to those who use the lake water for non-potable purposes such as bathing and washing clothes. This is the first study that investigated the presence of microbial source tracking (MST) markers in Dhaka, Bangladesh where diarrhoeal diseases is one of the major causes of childhood mortality. The molecular assay as used in this study can provide valuable information on the extent of sewage pollution, thus facilitating the development of robust strategies to minimise potential health risks.

Improving detection probabilities for pests in stored grains

BACKGROUND: The presence of insects in stored grains is a significant problem for grain farmers, bulk grain handlers and distributors worldwide. Inspections of bulk grain commodities is essential to detect pests and therefore to reduce the risk of their presence in exported goods. It has been well documented that insect pests cluster in response to factors such as microclimatic conditions within bulk grain. Statistical sampling methodologies for grains, however, have typically considered pests and pathogens to be homogeneously distributed throughout grain commodities. In this paper we demonstrate a sampling methodology that accounts for the heterogeneous distribution of insects in bulk grains. RESULTS: We show that failure to account for the heterogeneous distribution of pests may lead to overestimates of the capacity for a sampling program to detect insects in bulk grains. Our results indicate the importance of the proportion of grain that is infested in addition to the density of pests within the infested grain. We also demonstrate that the probability of detecting pests in bulk grains increases as the number of sub-samples increases, even when the total volume or mass of grain sampled remains constant. CONCLUSION: This study demonstrates the importance of considering an appropriate biological model when developing sampling methodologies for insect pests. Accounting for a heterogeneous distribution of pests leads to a considerable improvement in the detection of pests over traditional sampling models.

Spatial variability of soil carbon in forested and cultivated sites: Implications for change detection

The potential to sequester atmospheric carbon in agricultural and forest soils to offset greenhouse gas emissions has generated interest in measuring changes in soil carbon resulting from changes in land management. However, inherent spatial variability of soil carbon limits the precision of measurement of changes in soil carbon and hence, the ability to detect changes. We analyzed variability of soil carbon by intensively sampling sites under different land management as a step toward developing efficient soil sampling designs. Sites were tilled crop-land and a mixed deciduous forest in Tennessee, and old-growth and second-growth coniferous forest in western Washington, USA. Six soil cores within each of three microplots were taken as an initial sample and an additional six cores were taken to simulate resampling. Soil C variability was greater in Washington than in Tennessee, and greater in less disturbed than in more disturbed sites. Using this protocol, our data suggest that differences on the order of 2.0 Mg C ha(-1) could be detected by collection and analysis of cores from at least five (tilled) or two (forest) microplots in Tennessee. More spatial variability in the forested sites in Washington increased the minimum detectable difference, but these systems, consisting of low C content sandy soil with irregularly distributed pockets of organic C in buried logs, are likely to rank among the most spatially heterogeneous of systems. Our results clearly indicate that consistent intramicroplot differences at all sites will enable detection of much more modest changes if the same microplots are resampled.

The QUT-NOISE-TIMIT corpus for the evaluation of voice activity detection algorithms

The QUT-NOISE-TIMIT corpus consists of 600 hours of noisy speech sequences designed to enable a thorough evaluation of voice activity detection (VAD) algorithms across a wide variety of common background noise scenarios. In order to construct the final mixed-speech database, a collection of over 10 hours of background noise was conducted across 10 unique locations covering 5 common noise scenarios, to create the QUT-NOISE corpus. This background noise corpus was then mixed with speech events chosen from the TIMIT clean speech corpus over a wide variety of noise lengths, signal-to-noise ratios (SNRs) and active speech proportions to form the mixed-speech QUT-NOISE-TIMIT corpus. The evaluation of five baseline VAD systems on the QUT-NOISE-TIMIT corpus is conducted to validate the data and show that the variety of noise available will allow for better evaluation of VAD systems than existing approaches in the literature.

Bottlenecks detection of track allocation schemes at rail stations by Petri nets

Robustness of the track allocation problem is rarely addressed in literatures and the obtained track allocation schemes (TAS) embody some bottlenecks. Therefore, an approach to detect bottlenecks is needed to support local optimization. First a TAS is transformed to an executable model by Petri nets. Then disturbances analysis is performed using the model and the indicators of the total trains' departure delays are collected to detect bottlenecks when each train suffers a disturbance. Finally, the results of the tests based on a rail hub linking six lines and a TAS about thirty minutes show that the minimum buffer time is 21 seconds and there are two bottlenecks where the buffer times are 57 and 44 seconds respectively, and it indicates that the bottlenecks do not certainly locate at the area where there is minimum buffer time. The proposed approach can further support selection of multi schemes and robustness optimization.

Rationalizing the SER spectra of bacteria

The SER spectra of riboflavin and FAD are identical and are resonance enhanced at 514 or 532 nm. Signals from FAD/ riboflavin dominated SER spectra whenever these compounds were present with proteins or bacteria. SER spectra of very different bacteria such as Pseudomonas. aeruginosa, Bacillu. subtilis and Geobacillus. stearothermophilus were dominated by signals from FAD, even when these bacteria were added to a preformed colloid. The SERS signal of FAD is greatly reduced at 785 nm, and SER spectra of bacteria excited at 785 nm are quite different than those collected at 514 or 532 nm. This supports the assignment of the peaks in the 514 nm SER spectra of bacteria to FAD rather to amino acids or N-acetylglucosamine. The SER spectra of certain mixes of adenine and FAD showed similar changes to those of bacteria when the excitation was changed from 514/532 nm to 785 nm. The ratio of colloid: bacteria was of critical important for obtaining good SER spectra, and the addition of sodium sulfate was also beneficial. Removal of EPS from bacteria before analysis facilitated interaction with the silver surface, and may be a useful step to include in identification protocols.

Signature analysis on wheel-rail interaction for rail defect detection

Fibre Bragg Grating (FBG) sensors have been installed along an existing line for the purposes of train detection and weight measurement. The results show fair accuracy and high resolution on the vertical force acted on track when the train wheels are rolling upon. While the sensors are already in place and data is available, further applications beyond train detection are explored. This study presents the analysis on the unique signatures from the data collected to characterise wheel-rail interaction for rail defect detection. Focus of this first stage of work is placed on the repeatability of signals from the same wheel-rail interactions while the rail is in healthy state. Discussions on the preliminary results and hence the feasibility of this condition monitoring application, as well as technical issues to be addressed in practice, are given.

Clone Detection in Repositories of Business Process Models

Business process model repositories capture precious knowledge about an organization or a business domain. In many cases, these repositories contain hundreds or even thousands of models and they represent several man-years of effort. Over time, process model repositories tend to accumulate duplicate fragments, as new process models are created by copying and merging fragments from other models. This calls for methods to detect duplicate fragments in process models that can be refactored as separate subprocesses in order to increase readability and maintainability. This paper presents an indexing structure to support the fast detection of clones in large process model repositories. Experiments show that the algorithm scales to repositories with hundreds of models. The experimental results also show that a significant number of non-trivial clones can be found in process model repositories taken from industrial practice.

The development of Lactococcus lactis as an antimicrobial agent

Non-pathogenic lactic acid bacteria are economically important Gram-positive bacteria used extensively in the food industry. Due to their “generally regarded as safe” status, certain species from the genera Lactobacillus and Lactococcus are also considered desirable as candidates for the production and secretion of recombinant proteins, particular those with therapeutic applications. The hypothesis examined by this thesis is that Lactococcus lactis can be modified to be an effective antimicrobial agent. Therefore, the aims of this thesis were to investigate the optimisation of the expression, secretion and/or activities of potential heterologous antimicrobial proteins by the model lactic acid bacterium, Lactococcus lactis subsp. cremoris MG1363. L. lactis strains were engineered to express and secrete the recombinant CyuC surface protein from Lactobacillus reuteri BR11, and a fusion protein consisting of CyuC and lysostaphin using the Sep promoter and secretion signal. CyuC has been characterised as a cystine-binding protein, but has also been demonstrated to have fibronectin binding activity. Lysostaphin is a bacteriolytic enzyme with specific activity against the Gram-positive pathogen, Staphylococcus aureus. These modified L. lactis strains were then investigated to see if they had the ability to inhibit the adhesion of S. aureus to host extracellular matrix (ECM) proteins. It was observed that the cell extracts of the L. lactis strain with the vector only (pGhost9:ISS1) was able to inhibit the adhesion of S. aureus to fibronectin, whilst the cell extracts of the L. lactis strain expressing lysostaphin was able to inhibit adhesion to keratin. Finally, this thesis has identified specific lactococcal genes that affect the secretion of lysostaphin through the use of random transposon mutagenesis. Ten mutants with higher lysostaphin activity contained insertions in four different genes encoding: (i) an uncharacterised putative transmembrane protein (llmg_0609), (ii) an enzyme catalysing the first step in peptidoglycan biosynthesis (murA2), (iii) a homolog of the oxidative defence regulator (trmA), and (iv) an uncharacterised putative enzyme involved in ubiquinone biosynthesis (llmg_2148). The higher lysostaphin activity observed in these mutants was found to be due to higher amounts of lysostaphin being secreted. The findings of this thesis contribute to the development of this organism as an antimicrobial agent and also to our understanding of L. lactis genetics.

Detection of anomalies from user profiles generated from system logs

We describe research into the identification of anomalous events and event patterns as manifested in computer system logs. Prototype software has been developed with a capability that identifies anomalous events based on usage patterns or user profiles, and alerts administrators when such events are identified. To reduce the number of false positive alerts we have investigated the use of different user profile training techniques and introduce the use of abstractions to group together applications which are related. Our results suggest that the number of false alerts that are generated is significantly reduced when a growing time window is used for user profile training and when abstraction into groups of applications is used.

Fast and accurate phonetic spoken term detection

For the first time in human history, large volumes of spoken audio are being broadcast, made available on the internet, archived, and monitored for surveillance every day. New technologies are urgently required to unlock these vast and powerful stores of information. Spoken Term Detection (STD) systems provide access to speech collections by detecting individual occurrences of specified search terms. The aim of this work is to develop improved STD solutions based on phonetic indexing. In particular, this work aims to develop phonetic STD systems for applications that require open-vocabulary search, fast indexing and search speeds, and accurate term detection. Within this scope, novel contributions are made within two research themes, that is, accommodating phone recognition errors and, secondly, modelling uncertainty with probabilistic scores. A state-of-the-art Dynamic Match Lattice Spotting (DMLS) system is used to address the problem of accommodating phone recognition errors with approximate phone sequence matching. Extensive experimentation on the use of DMLS is carried out and a number of novel enhancements are developed that provide for faster indexing, faster search, and improved accuracy. Firstly, a novel comparison of methods for deriving a phone error cost model is presented to improve STD accuracy, resulting in up to a 33% improvement in the Figure of Merit. A method is also presented for drastically increasing the speed of DMLS search by at least an order of magnitude with no loss in search accuracy. An investigation is then presented of the effects of increasing indexing speed for DMLS, by using simpler modelling during phone decoding, with results highlighting the trade-off between indexing speed, search speed and search accuracy. The Figure of Merit is further improved by up to 25% using a novel proposal to utilise word-level language modelling during DMLS indexing. Analysis shows that this use of language modelling can, however, be unhelpful or even disadvantageous for terms with a very low language model probability. The DMLS approach to STD involves generating an index of phone sequences using phone recognition. An alternative approach to phonetic STD is also investigated that instead indexes probabilistic acoustic scores in the form of a posterior-feature matrix. A state-of-the-art system is described and its use for STD is explored through several experiments on spontaneous conversational telephone speech. A novel technique and framework is proposed for discriminatively training such a system to directly maximise the Figure of Merit. This results in a 13% improvement in the Figure of Merit on held-out data. The framework is also found to be particularly useful for index compression in conjunction with the proposed optimisation technique, providing for a substantial index compression factor in addition to an overall gain in the Figure of Merit. These contributions significantly advance the state-of-the-art in phonetic STD, by improving the utility of such systems in a wide range of applications.