Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goal of this study is to investigate the significantly different pathways and genes between ST398 and ST239. Methods: mRNA profiles of ST398 and ST239 at mid-logarithmic growth phase (4h) were generated by deep sequencing, respectively in quadruplicate and duplicate samples, using the Hiseq2000 (Illumina, CA) sequencer. The four samples of ST398 are J-92 (Sample1), W-604 (Sample2), R-1025 (Sample3) and R-1089 (Sample4) and grouped to G1, while the two samples of ST239 are J-95 (Sample5) and J-99 (Sample6) and grouped to G2. The sequence reads of ST398 and ST239 that passed quality filters were respectively aligned to S. aureus subsp. aureus ST398 (RefSeq accession number AM990992) and S. aureus subsp. aureus TW20 (RefSeq accession number NC _017331) using the Burrows-Wheeler Alignment tool (BWA) followed by ANOVA (ANOVA). Only the consistent data between the four ST398 samples and two ST239 samples were reserved for further analysis. qRT–PCR validation was performed using SYBR Green assays. Results: Using an optimized data analysis workflow, RNA-seq analyses revealed four types of significantly differentially expressed genes between ST398 and ST239 (G1 only, G2 only, G1/G2>2, G2/G1>2), and only the type of G1/G2>2 was included in this study. The type of G1/G2>2 included 164 genes in total, in which there are 14 top genes showing G1/G2>5 including essB gene. Conclusions: Our data provide new information to the signicantly different genes between ST239 and ST398, especially the highly expressed genes in ST398 compared to ST239 which might be closely related to the high virulence of ST398.
Project description:Whole genome sequencing data of low risk neuroblastoma tumors and matching controls used to study the evolutionary dynamics of neuroblastoma.
Project description:Long-term laboratory evolution experiments provide a controlled record of evolutionary dynamics and metabolic change in microorganisms. Nevertheless, the correspondence between genetic mutation and phenotypic adaptation remains elusive, partly because of the overwhelming number of genetic changes that accrue after tens-of-thousands of generations. Using a coarse-grained characterization of bacterial physiology applied to Lenski's laboratory-evolved strains of Escherichia coli, we identify an intermediate measure between genotype and phenotype that provides insight into the dynamics of adaptation.
Project description:Previous studies have documented the diversity of genetic background of methicillin-resistant S. aureus (MRSA) strains associated with healthcare (HA-MRSA), community (CA-MRSA) and livestock (LA-MRSA). The accessory and core-variable genome content of those strains remain largely unknown. To compare the composition of accessory and core-variable genome of Belgian MRSA strains according to host, population setting and genetic background, representative strains of HA- (n=21), CA- (n = 13) and ST398 LA-MRSA (n = 18) were characterized by a DNA-microarray (StaphVar Array) composed of oligonucleotide probes targeting ~400 resistance, adhesion and virulence associated genes.ST398 strains displayed very homogenous hybridization profiles (>94% gene content homology) irrespective of their host origin. This “ST398-specific” genomic profile was not distantly demarked from those of certain human-associated lineages but lacked several virulence- and colonization-associated genes harbored by strains of human origin, such as genes encoding proteases, haemolysins or adhesins. No enterotoxin gene was found among ST398 strains. In conclusion, our findings are consistent with a non-human origin of this ST398 lineage but suggest that it might have the potential to adapt further to the human host.
Project description:Long-term laboratory evolution experiments provide a controlled record of evolutionary dynamics and metabolic change in microorganisms. Nevertheless, the correspondence between genetic mutation and phenotypic adaptation remains elusive, partly because of the overwhelming number of genetic changes that accrue after tens-of-thousands of generations. Using a coarse-grained characterization of bacterial physiology applied to Lenski's laboratory-evolved strains of Escherichia coli, we identify an intermediate measure between genotype and phenotype that provides insight into the dynamics of adaptation.