Vladimir vimr9/13/2023 ![]() Ybt, also known as the high-pathogenicity island in the 102 kb pgm locus ( Fetherston and Perry, 1994), is necessary for iron acquisition at the flea bite site and in the lymphatic system. pestis, and at least two (Ybt and Yfe) of them have been proven essential to its full virulence ( Gao et al., 2008 Sebbane et al., 2010). Several iron acquisition systems have been characterized or annotated in Y. ![]() Iron acquisition is critical to the survival of pathogenic bacteria during infection. Iron is well established as an essential nutrient chelated by mammalian proteins, lessening its availability to invading pathogens. pestis in macrophages ( Zhou and Yang, 2009). RipABC, MgtCB, Ugd, Yfe, and Feo have been shown to be required for the replication of Y. pseudotuberculosis ( Pujol and Bliska, 2003). Interestingly, the ability to survive and replicate in macrophages is conserved in Y. pestis, a facultatively intracellular pathogen. ![]() pestis completely avirulent, even when the bacteria are directly introduced into the bloodstream ( Viboud and Bliska, 2005).Įscaping from macrophages at the early stage of infection is a vital step for Y. The loss of T3SS is sufficient to render Y. pestis is encoded by a 70 kb plasmid, termed as pCD1, which is also found in two other pathogenic Yersinia species, Y. pestis injects effectors into the cytosol of eukaryotic cells when docking on the surface of host cells, thereby suppressing phagocytosis and host inflammatory response. pestis is composed of a secretion machinery, a set of translocation proteins, a control system, and six Yop effector proteins ( Cornelis, 2002). Type III secretion system (T3SS) is a well-known anti-host system responsible for the virulence of many pathogenic bacteria. pseudotuberculosis, a gastrointestinal pathogen. pestis shares some virulence determinants with its ancestor, Y. pseudotuberculosis no earlier than 26,000 years ago ( Achtman et al., 1999 Morelli et al., 2010). Population genetics analysis revealed that Y. pseudotuberculosis are nearly identical at the genomic level, they cause very different diseases. These findings provided the opportunity to uncover virulence-associated genes due to the avirulent nature of 91001 in humans through comparative genomics ( Zhou et al., 2004a). pestis strain whole genomes, KIM and 91001, were decoded ( Lindler et al., 1998 Perry et al., 1998 Deng et al., 2002 Song et al., 2004). pestis (strain CO92) offered unprecedented opportunities for understanding the virulence traits of this deadly pathogen ( Parkhill et al., 2001). pestis, such as plasmids (pCD1, pMT1, and pPCP1) and chromosomal loci ( pgm locus and pH6 antigen coding genes), have already been identified as virulence-associated even before its genome was decoded ( Perry and Fetherston, 1997). We aim to provide a summary of the applications of omics strategies in studying Yersinia pestis, particularly in revealing its virulence. A multitude of extensive reviews introducing different omics technologies exist ( Morrison et al., 2006 Kolker, 2009 Holmes et al., 2010 Knox, 2010 Mahapatra, 2010 Ning and Lo, 2010 Wild, 2010), and we do not intend to repeatedly introduce these concepts and their related techniques in this review. The word “trans-omics” is also used to describe this type of studies ( Tuohy et al., 2009 Yang et al., 2011b Ogata et al., 2012). Combining omics strategies to elucidate specific features of an organism has become a trend, providing a unique opportunity to gain holistic understanding of the physiological and pathological characterization of the studied organism. The development of high-throughput technologies often yields large datasets that require extensive bioinformatic integration to apply omics in biological research. A detailed discussion on omics can be found in the Wikipedia website ( ). Omics is a collective concept of high-throughput studies for understanding life ( Morrison et al., 2006) using the integrative strategies of genomics, proteomics, transcriptomics, and metabolomics, as well as the newly developed omics strategies of RNomics ( Bhattacharjee et al., 2012), lipidomics ( Hartler et al., 2012), kinomics ( Kindrachuk et al., 2012), glycomics ( Turnbull and Sasisekharan, 2010), peptomics ( Olsen et al., 2002), antigenomics ( Levesque et al., 2012), chemomics ( Wang et al., 2008), etc.
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