Silencing of toxic gene expression by Fis

Bacteria and bacteriophages have evolved DNA modification as a strategy to protect their genomes. Mom protein of bacteriophage Mu modifies the phage DNA, rendering it refractile to numerous restriction enzymes and in turn enabling the phage to successfully invade a variety of hosts. A strong fortification, a combined activity of the phage and host factors, prevents untimely expression of mom and associated toxic effects. Here, we identify the bacterial chromatin architectural protein Fis as an additional player in this crowded regulatory cascade. Both in vivo and in vitro studies described here indicate that Fis acts as a transcriptional repressor of mom promoter. Further, our data shows that Fis mediates its repressive effect by denying access to RNA polymerase at mom promoter. We propose that a combined repressive effect of Fis and previously characterized negative regulatory factors could be responsible to keep the gene silenced most of the time. We thus present a new facet of Fis function in Mu biology. In addition to bringing about overall downregulation of Mu genome, it also ensures silencing of the advantageous but potentially lethal mom gene

Network Security Tool for a Novice

Network security is a complex field that is handled by security professionals who need certain expertise and experience to configure security systems. With the ever increasing size of the networks, managing them is going to be a daunting task. What kind of solution can be used to generate effective security configurations by both security professionals and nonprofessionals alike? In this thesis, a web tool is developed to simplify the process of configuring security systems by translating direct human language input into meaningful, working security rules. These human language inputs yield the security rules that the individual wants to implement in their network. The human language input can be as simple as, "Block Facebook to my son's PC". This tool will translate these inputs into specific security rules and install the translated rules into security equipment such as virtualized Cisco FWSM network firewall, Netfilter host-based firewall, and Snort Network Intrusion Detection. This tool is implemented and tested in both a traditional network and a cloud environment. One thousand input policies were collected from various users such as staff from UNT departments' and health science, including individuals with network security background as well as students with a non-computer science background to analyze the tool's performance. The tool is tested for its accuracy (91%) in generating a security rule. It is also tested for accuracy of the translated rule (86%) compared to a standard rule written by security professionals. Nevertheless, the network security tool built has shown promise to both experienced and inexperienced people in network security field by simplifying the provisioning process to result in accurate and effective network security rules

Sequence-based identification of microbial contaminants in non-parenteral products

Os perfis fenotípicos para identificação microbiana são incomuns para micro-organismos raros, de crescimento lento e exigentes. Na última década, em resultado do uso generalizado de PCR e sequenciação de DNA, a sequenciação do rRNA 16S tem desempenhado papel crucial na identificação precisa do micro-organismo e a descoberta de novos isolados em laboratórios de microbiologia. A região de rRNA 16S é universalmente distribuída entre micro-organismos e é espécie-específica. A genotipagem foi realizada sobre os organismos isolados a partir de formulações farmacêuticas não parenterais. O DNA foi separado dos cinco isolados obtidos a partir das formulações. As regiões alvo dos genes de rRNA foram amplificados por PCR e sequenciados utilizando os iniciadores adequados. Os dados dos sequência foram analisados e alinhados na ordem crescente de distância genética de sequências relevantes contra biblioteca de dados para obter a identidade. A sequência de DNA de árvores filogenéticas confirma a identidade dos isolados como Bacillus-tequilensis, B. subtilis, Staphylococcus haemolyticus e B. amyloliqueficians. Pode-se concluir identificação baseada na sequência do rRNA 16S reduz o tempo por evitar testes bioquímicos e também aumenta a especificidade e a precisão.Phenotypic profiles for microbial identification are unusual for rare, slow-growing and fastidious microorganisms. In the last decade, as a result of the widespread use of PCR and DNA sequencing, 16S rRNA sequencing has played a pivotal role in the accurate identification of microorganisms and the discovery of novel isolates in microbiology laboratories. The 16S rRNA region is universally distributed among microorganisms and is species-specific. Accordingly, the aim of our study was the genotypic identification of microorganisms isolated from non-parenteral pharmaceutical formulations. DNA was separated from five isolates obtained from the formulations. The target regions of the rRNA genes were amplified by PCR and sequenced using suitable primers. The sequence data were analyzed and aligned in the order of increasing genetic distance to relevant sequences against a library database to achieve an identity match. The DNA sequences of the phylogenetic tree results confirmed the identity of the isolates as Bacillus tequilensis, B. subtilis, Staphylococcus haemolyticus and B. amyloliqueficians. It can be concluded that 16S rRNA sequence-based identification reduces the time by circumventing biochemical tests and also increases specificity and accuracy

Innovative Solutions for Agriculture: Sensor-Driven Soil Parameter Monitoring and Deep Learning in Potato Disease Detection

The primary obstacle facing modern agriculture is the lack of advanced technologies capable of efficiently and proactively identifying crop diseases, a gap that is most noticeable while the crop is at the key stem stage. Taking note of this difficulty, the suggested solution calls for the deliberate insertion of cutting-edge sensors at the root level straight into the soil. The objective of this integration is to offer a comprehensive and in-depth evaluation of crucial factors that are necessary for plant health, including temperature dynamics, moisture content, and nutrient levels of soil. While the temperature sensors serve a dual purpose by monitoring the external environment and evaluating the condition of mechanical assets vital to agricultural operations, the soil moisture and index sensors are essential for precisely determining irrigation needs and assessing soil nutrient levels. The project incorporates a cutting-edge Convolutional Neural Network (CNN) deep learning algorithm designed especially for the identification of potato leaf diseases, which represents a significant improvement to disease detection capabilities. This sophisticated algorithm improves the accuracy and efficiency of disease identification by using deep learning to analyze and comprehend complex patterns found in the leaf of the plant. This comprehensive initiative's main goal is to create a seamlessly integrated sensor system that can monitor crop health dynamically, provide real-time insights into critical soil characteristics, and use state-of-the-art CNN deep learning technology to detect potato leaf diseases in the agricultural landscape with extreme precision

Single telomere length analysis in Ustilago maydis, a high-resolution tool for examining fungal telomere length distribution and C-strand 5’-end processing

Telomeres play important roles in genome stability and cell proliferation. Telomere lengths are heterogeneous and because just a few abnormal telomeres are sufficient to trigger significant cellular response, it is informative to have accurate assays that reveal not only average telomere lengths, but also the distribution of the longest and shortest telomeres in a given sample. Herein we report for the first time, the development of single telomere length analysis (STELA)—a PCR-based assay that amplifies multiple, individual telomeres— for Ustilago maydis, a basidiomycete fungus. Compared to the standard telomere Southern technique, STELA revealed a broader distribution of telomere size as well as the existence of relatively short telomeres in wild type cells. When applied to blm∆, a mutant thought to be defective in telomere replication, STELA revealed preferential loss of long telomeres, whose maintenance may thus be especially dependent upon efficient replication. In comparison to blm∆, the trt1∆ (telomerase null) mutant exhibited greater erosion of short telomeres, consistent with a special role for telomerase in re-lengthening extra-short telomeres. We also used STELA to characterize the 5’ ends of telomere C-strand, and found that in U. maydis, they terminate preferentially at selected nucleotide positions within the telomere repeat. Deleting trt1 altered the 5’-end distributions, suggesting that telomerase may directly or indirectly modulate C-strand 5’ end formation. These findings illustrate the utility of STELA as well as the strengths of U. maydis as a model system for telomere research

Production of pullulan using jaggery as substrate by Aureobasidium pullulans MTCC 2195

Shake-flask fermentation, under batch cultivation, was investigated for the production of fungal exopolysaccharide, pullulan using jaggery (a traditional concentrated sugar cane juice) as a carbon substrate by Aureobasidium pullulans MTCC 2195. Change in the initial pH (from 3.0 to 7.0) of media containing jaggery was varied to study the effect of pH in the fermentation and maximum pullulan yield was obtained at a pH of 5.0. An increase in the initial concentrations (50, 75, 100 g/L) of jaggery in the media produced the maximum pullulan content as 21.6, 19.7 and 18.6 g per 100 g of jaggery, respectively, used. A sucrose based defined media were also used for comparison purposes. Fourier Transform InfraRed (FTIR) spectroscopic analysis was done to confirm the functional groups of synthesized pullulan and compared with that of commercial pullulan.Shake-flask fermentation, under batch cultivation, was investigated for the production of fungal exopolysaccharide, pullulan using jaggery (a traditional concentrated sugar cane juice) as a carbon substrate by Aureobasidium pullulans MTCC 2195. Change in the initial pH (from 3.0 to 7.0) of media containing jaggery was varied to study the effect of pH in the fermentation and maximum pullulan yield was obtained at a pH of 5.0. An increase in the initial concentrations (50, 75, 100 g/L) of jaggery in the media produced the maximum pullulan content as 21.6, 19.7 and 18.6 g per 100 g of jaggery, respectively, used. A sucrose based defined media were also used for comparison purposes. Fourier Transform InfraRed (FTIR) spectroscopic analysis was done to confirm the functional groups of synthesized pullulan and compared with that of commercial pullulan

TdcA , a transcriptional activator of the tdcABC operon of Escherichia coli , is a member of the LysR family of proteins

The tdcB and tdcC genes of the tdcABC operon of Escherichia coli encode threonine dehydratase and a threonine-serine permease, respectively. These proteins are involved in transport and metabolism of threonine and serine during anaerobic growth. In this study, we functionally characterized tdcA , which encodes a 35 kDa polypeptide consisting of 312 amino acid residues. Non-polar and partially polar mutations introduced into tdcA drastically reduced the expression of the genes down-stream from tdcA . Complementation studies using single-copy chromosomal integrants of a tdcB-lacZ fusion harboring an in-frame deletion of tdcA with chromosomal or plasmid-borne tdcA + in trans showed complete restoration of tdc operon expression in vivo. The amino acid sequene at the amino-terminal end of TdcA revealed a significant homology to the helix-turn-helix motifs of typical DNA binding proteins. Sequence alignment of TdcA with LysR also showed considerable sequence similarity throughout their entire lengths. Our results suggest that TdcA is related to the LysR family of proteins by common ancestry and, based on its functional role in tdc expression, belongs to the LysR family of transcriptional activators.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47584/1/438_2004_Article_BF00280391.pd

Genome-Wide Screening of Genes Whose Enhanced Expression Affects Glycogen Accumulation in Escherichia coli

Using a systematic and comprehensive gene expression library (the ASKA library), we have carried out a genome-wide screening of the genes whose increased plasmid-directed expression affected glycogen metabolism in Escherichia coli. Of the 4123 clones of the collection, 28 displayed a glycogen-excess phenotype, whereas 58 displayed a glycogen-deficient phenotype. The genes whose enhanced expression affected glycogen accumulation were classified into various functional categories including carbon sensing, transport and metabolism, general stress and stringent responses, factors determining intercellular communication, aggregative and social behaviour, nitrogen metabolism and energy status. Noteworthy, one-third of them were genes about which little or nothing is known. We propose an integrated metabolic model wherein E. coli glycogen metabolism is highly interconnected with a wide variety of cellular processes and is tightly adjusted to the nutritional and energetic status of the cell. Furthermore, we provide clues about possible biological roles of genes of still unknown functions