Anti-MBP monoclonal antibody

Arcobacter butzleri is a foodborne emerging human pathogen, frequently displaying a multidrug resistant character. Still, the lack of comprehensive genome-scale comparative analysis has limited our knowledge on A. butzleri diversification and pathogenicity. Here, we performed a deep genome analysis of A. butzleri focused on decoding its core- and pan-genome diversity and specific genetic traits underlying its pathogenic potential and diverse ecology. A. butzleri (genome size 2.07-2.58 Mbp) revealed a large open pan-genome with 7474 genes (about 50% being singletons) and a small but diverse core-genome with 1165 genes. It presents a plastic virulome (including newly identified determinants), marked by the differential presence of multiple adaptation-related virulence factors, such as the urease cluster ureD(AB)CEFG (phenotypically confirmed), the hypervariable hemagglutinin-encoding hecA, a type I secretion system (T1SS) harboring another agglutinin and a novel VirB/D4 T4SS likely linked to interbacterial competition and cytotoxicity. In addition, A. butzleri harbors a large repertoire of efflux pumps (EPs) and other antibiotic resistant determinants. We unprecedentedly describe a genetic mechanism of A. butzleri macrolides resistance, (inactivation of a TetR repressor likely regulating an EP). Fluoroquinolones resistance correlated with Thr-85-Ile in GyrA and ampicillin resistance was linked to an OXA-15-like beta-lactamase. Remarkably, by decoding the polymorphism pattern of the main antigen PorA, we show that A. butzleri is able to exchange porA as a whole and/or hypervariable epitope-encoding regions separately, leading to a multitude of chimeric PorA presentations that can impact pathogen-host interaction during infection. Ultimately, our unprecedented screening of short sequence repeats indicates that phase variation likely modulates A. butzleri key adaptive functions. In summary, this study constitutes a turning point on A. butzleri comparative genomics revealing that this human gastrointestinal pathogen is equipped with vast and diverse virulence and antibiotic resistance arsenals that open a multitude of phenotypic fingerprints for environmental/host adaptation and pathogenicity.

Over the past few decades, industrial development has caused a dramatic increment in greenhouse gas (GHG) emissions, as a leading cause of climate change. Modifying the industrial plants' environmental performance is the main pillar of improving efficiency that can reduce the waste of resources and make achieving lower-cost global emission reduction targets of the Kyoto protocol's clean development mechanism (CDM) possible. Considering the essentiality of knowledge-based research in increasing the awareness of policymakers by providing better access to accurate and reliable information, an analytical survey on efficiency in oil, gas, and petrochemical industries has been conducted by applying data envelopment analysis (DEA). For this purpose, comprehensive evaluations were elaborated on monthly data for Zagros Petrochemical Company (ZPC), from 2011 to 2017, as a case study. The CO(2)equivalent emissions of fuel combustion in the petrochemical plant's furnaces were calculated according to standard guidelines for calculation and reporting GHG to be used for environmental efficiency estimations. The data envelopment analysis program (DEAP) was applied to estimate efficiencies through the data envelopment analysis-materials balance principle (DEA-MBP) approach, which is a robust approach employed in this study to provide practical solutions to both economic and environmental concerns. Since DEA-MBP is based on the materials balance principle and incorporates by-products, it can reliably explain the best relationship between product quantities, carbon emissions, and external costs. The outcomes revealed that the lower heating value of natural gas and CO(2)emission factor and CO(2)equivalent emissions were 32.87 x 10(-3) GJ/Sm-3, 55.73 x 10(-3) ton/GJ, and 2,376,449 tons, respectively. DEAP analysis also exhibited the technical, environmental, and environmental allocative efficiency scores as 0.976, 0.861, and 0.881, respectively, and estimated distances to efficiency frontiers were 0.024, 0.139, and 0.119, respectively. Ultimately, the carbon prices were found to be about US$83,175,715 and US$71,531,110 under two scenarios (A and B).