Genetic Proclivities of Two-Component Modulated Aerobiosis
Hamzat Ibiyeye Tijani,
Idris Abdulrahman,
Bashir Mohammed Abubakar,
Sulaiman Mohammed,
Jibrin Ndejiko Mohammed,
Haruna Saidu,
Hindatu Yusuf
Issue:
Volume 2, Issue 1, February 2014
Pages:
1-6
Received:
11 December 2013
Published:
10 January 2014
Abstract: Great advances have been made in the past five decades in understanding the molecular mechanics of the two-component signal transduction pathway in bacteria but its applications in Medicine and Food Industries are yet to be fully unravelled. We discuss the varying changes in the extracellular environment of bacteria and their possession of multiple Two-Component Systems with each being specialize to react to a specific environmental signal, such as pH, nutrient level, redox state, osmotic pressure, quorum signals, and antibiotics. The sensitivity of this response transmits information between different Two-Component Systems to form a complex signal transduction network. Bacteria’s signal transduction system, referred to as a two-component system, are essential for adaptation to external stimuli. These systems provides a signal transduction pathways widely employed from prokaryotes to eukaryotes. Typically, each two-component system composed of a sensor protein distinctively monitors an external signal(s) and a response regulator (RR) that controls gene expression and other physiological activities which are collectively assembled in a signal transduction pathway. This annex reviews the molecular mechanics underlying the signal transduction systems in prokaryotic organisms. It is not uncommon to hear, either explicitly or implicitly, the statement that “two component regulatory systems are well understood”. Therefore, we examine the current models of the mechanisms of the regulatory systems and provide viable suggestions to further expand its applications in drug efficiency and antibiotic resistance in humans as well as enhancing the shelf-life of products in the food industry. We also outline the challenges that might have quenched possible trials of this application to human health.
Abstract: Great advances have been made in the past five decades in understanding the molecular mechanics of the two-component signal transduction pathway in bacteria but its applications in Medicine and Food Industries are yet to be fully unravelled. We discuss the varying changes in the extracellular environment of bacteria and their possession of multiple...
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Uncertainty Quantification Driven Predictive Multi-Scale Model for Synthesis of Mycotoxins
Sourav Banerjee,
Gabriel Terejanu,
Anindya Chanda
Issue:
Volume 2, Issue 1, February 2014
Pages:
7-12
Received:
3 January 2014
Published:
30 January 2014
Abstract: Many toxic molds synthesize and release an array of poisons, termed mycotoxins that have an enormous impact on human health, agriculture and economy [1]. These molds contaminate our buildings, indoor air and crops, cause life threatening human and animal diseases and reduce agricultural output [2]. In order to design appropriate approaches to minimize the detrimental effects of these fungi, it is essential to develop diagnostic methodologies that can rapidly and accurately determine based on fungal strains and their growth patterns, the extent of mycotoxin mediated damage caused to the environment.Here we developed a novel multi-scale predictive mathematical model that could reliably estimate aflatoxin synthesis from growth features extracted fromAspergillusparasiticus, a well-characterized model for studying mycotoxin biosynthesis. We conducted acoustic imaging experiments to observe and extract the growth features from the biomass profiles of the growing Aspergillus colony growing on an aflatoxin-inducing solid growth medium. We employed the probability-based representation of uncertainty and used Bayes’ theorem to infer the uncertain parameters in our mathematical model using biomass observations of the colony at 24h (aflatoxin is not synthesized yet at this time-point) and 48 hours (aflatoxin synthesis occurs at peak levels). We demonstrate that our model could successfully predict with quantified uncertainties the levels of aflatoxin secreted to the environment by the fungus.
Abstract: Many toxic molds synthesize and release an array of poisons, termed mycotoxins that have an enormous impact on human health, agriculture and economy [1]. These molds contaminate our buildings, indoor air and crops, cause life threatening human and animal diseases and reduce agricultural output [2]. In order to design appropriate approaches to minim...
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Computational Design of Peptide Vaccine against Acinetobacter Baumannii Infection using Comparative Genomic Approach
Ajao Abdullahi Taiwo,
Ajao Jumoke Falilat,
Yakubu Sabo Ezemuel
Issue:
Volume 2, Issue 1, February 2014
Pages:
13-18
Received:
12 January 2014
Published:
10 March 2014
Abstract: The bacterial species Acinetobacter baumannii is a major cause of hospital acquired infection throughout the world and it is increasing public health concern. Infection caused by multidrug resistant A. baumannii is currently among the most difficult to treat due to propensity to acquire mobile genetic element. To date there is no vaccine or specific drug available for its treatment, this necessitate the need for the identification of therapeutic target enzyme and vaccine. Pharmacogenomic and computational biology represent an attractive alternative approach for the identification of common drug target and peptide-vaccine candidates in the pathogen. Vaccine designing is shifted from entire pathogen or whole antigen to peptide or epitope based-vaccines that are specific, safe and easy to produce. Comparative genomic approach was used to identify conserved protein signatures among five genomes. Three outer membrane proteins conserved among the genomes with high vaxijen scores were used to produce both B-cell and T-cell mediated immunity. Propred and propred1 were used to predict promiscuos helper T-Lymphocytes (HTL), Cytotoxic T-Lymphocyte (CTL) epitopes and MHCPred for their binding affinity.Three T-cell epitopes derived from identified B-cells bind to maximum number of MHC class I and class II alleles and specifically bind to HLA alleles such as DRB1*0101 and DRB1*0401.The epitopes are YEKLAAGPS, FYTSQPEDS and YVTGNPLGL with high potential to induce humoral and cell mediated immune responses. These predicted epitopes (small peptide) might be promising candidates for vaccine design against A. baumannii infection, though experimental validation.
Abstract: The bacterial species Acinetobacter baumannii is a major cause of hospital acquired infection throughout the world and it is increasing public health concern. Infection caused by multidrug resistant A. baumannii is currently among the most difficult to treat due to propensity to acquire mobile genetic element. To date there is no vaccine or specifi...
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