Project description:Neisseria meningitidis is the leading cause of bacterial meningitis and septicemia worldwide. The novel ST-4821 clonal complex caused several serogroup C meningococcal outbreaks unexpectedly during 2003–2005 in China. We fabricated a whole-genome microarray of Chinese N. meningitidis serogroup C representative isolate 053442 and characterized 27 ST-4821 complex isolates which were isolated from different serogroups using comparative genomic hybridization (CGH) analysis. This paper provides important clues which are helpful to understand the genome composition and genetic background of different serogroups isolates, and possess significant meaning to the study of the newly emerged hyperinvasive lineage. Keywords: comparative genomic hybridization
Project description:Neisseria meningitidis is a major cause of bacterial meningitis and septicemia worldwide. Seven new serogroup C meningococci were isolated from two provinces of China in January, 2006. Their PorA VR types were P1.20, 9. Multilocus sequence typing results indicated that they all belonged to ST-7. It is a new serogroup C N. meningitidis sequence type clone identified in China. Here we also present the results of a genomic comparison of these isolates with other 15 N. meningitidis serogroup A and B isolates, which belonged to ST-7, based on comparative genomic hybridization analysis. The data described here would be helpful to monitor the spread of this new serogroup C meningococci sequence type clone in China and worldwide. Keywords: comparative genomic hybridization
2007-10-11 | GSE7331 | GEO
Project description:Genomic surveillance of respiratory viruses USA:WA 2022-2024
Project description:Nucleic acids in wastewater provide a rich source of data for detection and surveillance of microbes. We have longitudinally collected 116 RNA samples from a wastewater treatment plant in Berlin/Germany, from March 2021 to July 2022, and 24 DNA samples from May to July 2022. We tracked human astroviruses, enteroviruses, noroviruses and adenoviruses over time to the level of strains or even individual nucleotide variations, showing how detailed human pathogens can be observed using wastewater. For respiratory pathogens, a broad enrichment panel enabled us to detect waves of RSV, influenza, or common cold coronaviruses in high agreement with clinical data. By applying a profile Hidden Markov Model-based search for novel viruses, we identified more than 100 thousand novel transcript assemblies likely not belonging to known virus species, thus substantially expanding our knowledge of virus diversity. Phylogenetic analysis is shown for bunyaviruses and parvoviruses. Finally, we identify Hundreds of novel protein sequences for CRISPR-associated proteins such as Transposase B, a class of small RNA-guided DNA editing enzymes. Taken together, we present a longitudinal and deep investigation into wastewater-derived genomic sequencing data that underlines the value of sewage surveillance for public health, planetary virome research, and biotechnological potential.
Project description:Baart2007 - Genome-scale metabolic network of
Neisseria meningitidis (iGB555)
This model is described in the article:
Modeling Neisseria
meningitidis metabolism: from genome to metabolic fluxes.
Baart GJ, Zomer B, de Haan A, van
der Pol LA, Beuvery EC, Tramper J, Martens DE.
Genome Biol. 2007; 8(7): R136
Abstract:
BACKGROUND: Neisseria meningitidis is a human pathogen that
can infect diverse sites within the human host. The major
diseases caused by N. meningitidis are responsible for death
and disability, especially in young infants. In general, most
of the recent work on N. meningitidis focuses on potential
antigens and their functions, immunogenicity, and pathogenicity
mechanisms. Very little work has been carried out on Neisseria
primary metabolism over the past 25 years. RESULTS: Using the
genomic database of N. meningitidis serogroup B together with
biochemical and physiological information in the literature we
constructed a genome-scale flux model for the primary
metabolism of N. meningitidis. The validity of a simplified
metabolic network derived from the genome-scale metabolic
network was checked using flux-balance analysis in chemostat
cultures. Several useful predictions were obtained from in
silico experiments, including substrate preference. A minimal
medium for growth of N. meningitidis was designed and tested
successfully in batch and chemostat cultures. CONCLUSION: The
verified metabolic model describes the primary metabolism of N.
meningitidis in a chemostat in steady state. The genome-scale
model is valuable because it offers a framework to study N.
meningitidis metabolism as a whole, or certain aspects of it,
and it can also be used for the purpose of vaccine process
development (for example, the design of growth media). The flux
distribution of the main metabolic pathways (that is, the
pentose phosphate pathway and the Entner-Douderoff pathway)
indicates that the major part of pyruvate (69%) is synthesized
through the ED-cleavage, a finding that is in good agreement
with literature.
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Project description:We performed the genomic sequencing, assembly and annotation of T. pullulans strain CRUB 1754 (Perito Moreno glacier, Argentina), a gene survey of Carbohydrate-active enzymes (CAZymes); and analyzed its secretome by Liquid-Chromatography coupled to tandem Mass Spectrometry (LC-MS/MS) after growth in glucose (GLU) or starch (STA) as main carbon sources.
Project description:We looked at host gene expression signatures common and specfic to occasionally pathogenic N. meningitidis and commensal N. lactamica. We hypothesise that similar host cell responses during early interactions with N. meningitidis and N. lactamica could inform common mechanisms of colonisation of commensals while differential host cell responses could be capable of altering the outcome of the colonisation process.