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1.
Relatively little is known about the small subset of peroxisomal proteins with predicted protease activity. Here, we report that the peroxisomal LON2 (At5g47040) protease facilitates matrix protein import into Arabidopsis (Arabidopsis thaliana) peroxisomes. We identified T-DNA insertion alleles disrupted in five of the nine confirmed or predicted peroxisomal proteases and found only two—lon2 and deg15, a mutant defective in the previously described PTS2-processing protease (DEG15/At1g28320)—with phenotypes suggestive of peroxisome metabolism defects. Both lon2 and deg15 mutants were mildly resistant to the inhibitory effects of indole-3-butyric acid (IBA) on root elongation, but only lon2 mutants were resistant to the stimulatory effects of IBA on lateral root production or displayed Suc dependence during seedling growth. lon2 mutants displayed defects in removing the type 2 peroxisome targeting signal (PTS2) from peroxisomal malate dehydrogenase and reduced accumulation of 3-ketoacyl-CoA thiolase, another PTS2-containing protein; both defects were not apparent upon germination but appeared in 5- to 8-d-old seedlings. In lon2 cotyledon cells, matrix proteins were localized to peroxisomes in 4-d-old seedlings but mislocalized to the cytosol in 8-d-old seedlings. Moreover, a PTS2-GFP reporter sorted to peroxisomes in lon2 root tip cells but was largely cytosolic in more mature root cells. Our results indicate that LON2 is needed for sustained matrix protein import into peroxisomes. The delayed onset of matrix protein sorting defects may account for the relatively weak Suc dependence following germination, moderate IBA-resistant primary root elongation, and severe defects in IBA-induced lateral root formation observed in lon2 mutants.Peroxisomes are single-membrane-bound organelles found in most eukaryotes. Peroxin (PEX) proteins are necessary for various aspects of peroxisome biogenesis, including matrix protein import (for review, see Distel et al., 1996; Schrader and Fahimi, 2008). Most matrix proteins are imported into peroxisomes from the cytosol using one of two targeting signals, a C-terminal type 1 peroxisome-targeting signal (PTS1) or a cleavable N-terminal type 2 peroxisome-targeting signal (PTS2) (Reumann, 2004). PTS1- and PTS2-containing proteins are bound in the cytosol by soluble matrix protein receptors, escorted to the peroxisome membrane docking complex, and translocated into the peroxisome matrix (for review, see Platta and Erdmann, 2007). Once in the peroxisome, many matrix proteins participate in metabolic pathways, such as β-oxidation, hydrogen peroxide decomposition, and photorespiration (for review, see Gabaldon et al., 2006; Poirier et al., 2006).In addition to metabolic enzymes, several proteases are found in the peroxisome matrix. Only one protease, DEG15/Tysnd1, has a well-defined role in peroxisome biology. The rat Tysnd1 protease removes the targeting signal after PTS2-containing proteins enter the peroxisome and also processes certain PTS1-containing β-oxidation enzymes (Kurochkin et al., 2007). Similarly, the Arabidopsis (Arabidopsis thaliana) Tysnd1 homolog DEG15 (At1g28320) is a peroxisomal Ser protease that removes PTS2 targeting signals (Helm et al., 2007; Schuhmann et al., 2008).In contrast with DEG15, little is known about the other eight Arabidopsis proteins that are annotated as proteases in the AraPerox database of putative peroxisomal proteins (Reumann et al., 2004; Carter et al., 2004; Shimaoka et al., 2004), which, in combination with the minor PTS found in both of these predicted proteases (Reumann, 2004), suggests that these enzymes may not be peroxisomal. Along with DEG15, only two of the predicted peroxisomal proteases, an M16 metalloprotease (At2g41790), which we have named PXM16 for peroxisomal M16 protease, and a Lon-related protease (At5g47040/LON2; Ostersetzer et al., 2007), are found in the proteome of peroxisomes purified from Arabidopsis suspension cells (Eubel et al., 2008). DEG15 and LON2 also have been validated as peroxisomally targeted using GFP fusions (Ostersetzer et al., 2007; Schuhmann et al., 2008).

Table I.

Putative Arabidopsis proteases predicted or demonstrated to be peroxisomal
AGI IdentifierAliasProtein ClassT-DNA Insertion AllelesPTSLocalization EvidenceLocalization References
At1g28320DEG15PTS2-processing proteaseSALK_007184 (deg15-1)SKL>aGFPReumann et al., 2004; Helm et al., 2007; Eubel et al., 2008; Schuhmann et al., 2008)
Proteomics
Bioinformatics
At2g41790PXM16Peptidase M16 family proteinSALK_019128 (pxm16-1)PKL>bProteomicsReumann et al., 2004, 2009; Eubel et al., 2008)
SALK_023917 (pxm16-2)Bioinformatics
At5g47040LON2Lon protease homologSALK_128438 (lon2-1)SKL>aGFPReumann et al., 2004, 2009; Ostersetzer et al., 2007; Eubel et al., 2008)
SALK_043857 (lon2-2)Proteomics
Bioinformatics
At2g18080Ser-type peptidaseSALK_020628SSI>cBioinformatics(Reumann et al., 2004)
SALK_102239
At2g35615Aspartyl proteaseSALK_090795ANL>bBioinformatics(Reumann et al., 2004)
SALK_036333
At3g57810Ovarian tumor-like Cys proteaseSKL>aBioinformatics(Reumann et al., 2004)
At4g14570Acylaminoacyl-peptidase proteinCKL>bBioinformatics (peroxisome)(Reumann et al., 2004; Shimaoka et al., 2004)
Proteomics (vacuole)
At4g20310Peptidase M50 family proteinRMx5HLdBioinformatics(Reumann et al., 2004)
At4g36195Ser carboxypeptidase S28 familySSM>bBioinformatics (peroxisome)(Carter et al., 2004; Reumann et al., 2004)





Proteomics (vacuole)

Open in a separate windowaMajor PTS1 (Reumann, 2004).bMinor PTS1 (Reumann, 2004).cValidated PTS1 (Reumann et al., 2007).dMinor PTS2 (Reumann, 2004).PXM16 is the only one of the nine Arabidopsis M16 (pitrilysin family) metalloproteases (García-Lorenzo et al., 2006; Rawlings et al., 2008) containing a predicted PTS. M16 subfamilies B and C contain the plastid and mitochondrial processing peptidases (for review, see Schaller, 2004), whereas PXM16 belongs to M16 subfamily A, which includes insulin-degrading peptidases (Schaller, 2004). A tomato (Solanum lycopersicum) M16 subfamily A protease similar to insulin-degrading enzymes with a putative PTS1 was identified in a screen for proteases that cleave the wound response peptide hormone systemin (Strassner et al., 2002), but the role of Arabidopsis PXM16 is unknown.Arabidopsis LON2 is a typical Lon protease with three conserved domains: an N-terminal domain, a central ATPase domain in the AAA family, and a C-terminal protease domain with a Ser-Lys catalytic dyad (Fig. 1A; Lee and Suzuki, 2008). Lon proteases are found in prokaryotes and in some eukaryotic organelles (Fig. 1C) and participate in protein quality control by cleaving unfolded proteins and can regulate metabolism by controlling levels of enzymes from many pathways, including cell cycle, metabolism, and stress responses (for review, see Tsilibaris et al., 2006). Four Lon homologs are encoded in the Arabidopsis genome; isoforms have been identified in mitochondria, plastids, and peroxisomes (Ostersetzer et al., 2007; Eubel et al., 2008; Rawlings et al., 2008). Mitochondrial Lon protesases are found in a variety of eukaryotes (Fig. 1A) and function both as ATP-dependent proteases and as chaperones promoting protein complex assemblies (Lee and Suzuki, 2008). LON2 is the only Arabidopsis Lon isoform with a canonical C-terminal PTS1 (SKL-COOH; Ostersetzer et al., 2007) or found in the peroxisome proteome (Eubel et al., 2008; Reumann et al., 2009). Functional studies have been conducted with peroxisomal Lon isoforms found in the proteome of peroxisomes purified from rat hepatic cells (pLon; Kikuchi et al., 2004) and the methylotrophic yeast Hansenula polymorpha (Pln; Aksam et al., 2007). Rat pLon interacts with β-oxidation enzymes, and a cell line expressing a dominant negative pLon variant has decreased β-oxidation activity, displays defects in the activation processing of PTS1-containing acyl-CoA oxidase, and missorts catalase to the cytosol (Omi et al., 2008). H. polymorpha Pln is necessary for degradation of a misfolded, peroxisome-targeted version of dihydrofolate reductase and for degradation of in vitro-synthesized alcohol oxidase in peroxisomal matrix extracts, but does not contribute to degradation of peroxisomally targeted GFP (Aksam et al., 2007).Open in a separate windowFigure 1.Diagram of LON2 protein domains, gene models for LON2, PXM16, DEG15, PED1, PEX5, and PEX6, and phylogenetic relationships of LON family members. A, Organization of the 888-amino acid LON2 protein. Locations of the N-terminal domain conserved among Lon proteins, predicted ATP-binding Walker A and B domains (black circles), active site Ser (S) and Lys (K) residues (asterisks), and the C-terminal Ser-Lys-Leu (SKL) peroxisomal targeting signal (PTS1) are shown (Lee and Suzuki, 2008). B, Gene models for LON2, PXM16, DEG15, PED1, PEX5, and PEX6 and locations of T-DNA insertions (triangles) or missense alleles (arrows) used in this study. Exons are depicted by black boxes, introns by black lines, and untranslated regions by gray lines. C, Phylogenetic relationships among LON homologs. Sequences were aligned using MegAlign (DNAStar) and the ClustalW method. The PAUP 4.0b10 program (Swofford, 2001) was used to generate an unrooted phylogram from a trimmed alignment corresponding to Arabidopsis LON2 residues 400 to 888 (from the beginning of the ATPase domain to the end of the protein). The bootstrap method was performed for 500 replicates with distance as the optimality criterion. Bootstrap values are indicated at the nodes. Predicted peroxisomal proteins have C-terminal PTS1 signals in parentheses and are in light-gray ovals. Proteins in the darker gray oval have N-terminal extensions and include mitochondrial and chloroplastic proteins. Sequence identifiers are listed in Supplemental Table S2.In this work, we examined the roles of several putative peroxisomal proteases in Arabidopsis. We found that lon2 mutants displayed peroxisome-deficient phenotypes, including resistance to the protoauxin indole-3-butyric acid (IBA) and age-dependent defects in peroxisomal import of PTS1- and PTS2-targeted matrix proteins. Our results indicate that LON2 contributes to matrix protein import into Arabidopsis peroxisomes.  相似文献   

2.
3.
The intraflagellar transport machinery is required for the assembly of cilia. It has been investigated by biochemical, genetic, and computational methods that have identified at least 21 proteins that assemble into two subcomplexes. It has been hypothesized that complex A is required for retrograde transport. Temperature-sensitive mutations in FLA15 and FLA17 show defects in retrograde intraflagellar transport (IFT) in Chlamydomonas. We show that IFT144 and IFT139, two complex A proteins, are encoded by FLA15 and FLA17, respectively. The fla15 allele is a missense mutation in a conserved cysteine and the fla17 allele is an in-frame deletion of three exons. The flagellar assembly defect of each mutant is rescued by the respective transgenes. In fla15 and fla17 mutants, bulges form in the distal one-third of the flagella at the permissive temperature and this phenotype is also rescued by the transgenes. These bulges contain the complex B component IFT74/72, but not α-tubulin or p28, a component of an inner dynein arm, which suggests specificity with respect to the proteins that accumulate in these bulges. IFT144 and IFT139 are likely to interact with each other and other proteins on the basis of three distinct genetic tests: (1) Double mutants display synthetic flagellar assembly defects at the permissive temperature, (2) heterozygous diploid strains exhibit second-site noncomplemention, and (3) transgenes confer two-copy suppression. Since these tests show different levels of phenotypic sensitivity, we propose they illustrate different gradations of gene interaction between complex A proteins themselves and with a complex B protein (IFT172).CILIA and flagella are microtubule-based organelles that are found on most mammalian cells. They provide motility to cells and participate in many sensory processes. Defects in or loss of cilia/flagella cause a variety of human diseases that include polycystic kidney disease, retinal degeneration, infertility, obesity, respiratory defects, left–right axis determination, and polydactyly (Fliegauf et al. 2007). Mouse mutants demonstrate that cilia are essential for viability, neural tube closure, and bone development (Eggenschwiler and Anderson 2007; Fliegauf et al. 2007). Cilia and flagella are also present in protists, algae, moss, and some fungi.The assembly and maintenance of cilia and flagella require intraflagellar transport (IFT) (Kozminski et al. 1995). IFT involves the movement of 100- to 200-nm-long protein particles from the basal body located in the cell body to the tip of the flagella using the heterotrimeric kinesin-2 (anterograde movement) (Kozminski et al. 1995) and movement back to the cell body (retrograde movement) using the cytoplasmic dynein complex (Pazour et al. 1999; Porter et al. 1999). IFT particles change their direction of movement as well as their size, speed, and frequency at the ends of the flagella as they switch from anterograde to retrograde movement (Iomini et al. 2001). Biochemical isolation of IFT particles reveals that they are composed of at least 16 proteins and that these particles can be dissociated into two complexes in vitro by changing the salt concentration (Cole et al. 1998; Piperno et al. 1998). Recent genetic and bioinformatics analysis adds at least 7 more proteins to the IFT particle (Follit et al. 2009) (Eggenschwiler and Anderson 2007).

TABLE 1

Proteins and gene names for the intraflagellar transport particles in Chlamydomonas, C. elegans, and mouse
ProteinMotifChlamydomonas geneC. elegans geneMouse geneReferences to worm and mouse genes
Complex A
IFT144WDFLA15
IFT140WDche-11Qin et al. (2001)
IFT139TRPFLA17dyf-2THM1Efimenko et al. (2006); Tran et al. (2008)
IFT122WDIFTA-1Blacque et al. (2006)
IFT121WDdaf-10Bell et al. (2006)
IFT43
Complex B
IFT172WDFLA11osm-1WimpleHuangfu et al. (2003); Pedersen et al. (2005); Bell et al. (2006)
IFT88TRPIFT88osm-5Tg737/PolarisPazour et al. (2000); Qin et al. (2001)
IFT81Coilift-81CDV1Kobayashi et al. (2007)
IFT80WDche-2Wdr56Fujiwara et al. (1999)
IFT74/72Coilift-74Cmg1Kobayashi et al. (2007)
IFT57/55Coilche-13HippiHaycraft et al. (2003)
IFT54Microtubule binding domain MIP-T3dyf-11Traf3IP1Kunitomo and Iino (2008); Li et al. (2008); Omori et al. (2008); Follit et al. (2009)
IFT52ABC typeBLD1osm-6Ngd2Brazelton et al. (2001); Bell et al. (2006)
IFT46IFT46dyf-6Bell et al. (2006); Hou et al. (2007)
IFT27G proteinNot presentRabl4
IFT25Hsp20Not presentHSP16.1Follit et al. (2009)
IFT22G proteinIFTA-2Rabl5Schafer et al. (2006)
IFT20CoilFollit et al. (2006)
FAP22Cluamp related proteindyf-3Cluamp1Murayama et al. (2005); Follit et al. (2009)
DYF13


dyf-13
Ttc26
Blacque et al. (2005)
Open in a separate window—, no mutant found to date in Chlamydomonas.A collection of temperature-sensitive mutant strains that fail to assemble flagella at the restrictive temperature of 32° was isolated in Chlamydomonas (Huang et al. 1977; Adams et al. 1982; Piperno et al. 1998; Iomini et al. 2001). Analysis of the flagella at 21° permits the measurement of the velocity and frequency of IFT particles in the mutant strains. This analysis suggested that assembly has four phases: recruitment to the basal body, anterograde movement (phases I and II), retrograde movement, and return to the cytoplasm (phases III and IV) (Iomini et al. 2001). Different mutants were classified as defective in these four phases. However, because different alleles of FLA8 were classified as defective in different phases (Iomini et al. 2001; Miller et al. 2005), we combined mutants with IFT defects into just two classes. The first group (phases I and II) includes mutant strains that show decreased anterograde velocities, a decreased ratio of anterograde to retrograde particles, and an accumulation of complex A proteins at the basal body. This group includes mutations in the FLA8 and FLA10 genes, which encode the two motor subunits of kinesin-2 (Walther et al. 1994; Miller et al. 2005), as well as mutations in three unknown genes (FLA18, FLA27, and FLA28). The second group includes mutant strains that show the reciprocal phenotype (phases III and IV); these phenotypes include decreased retrograde velocities, an increased ratio of anterograde to retrograde particles, and an accumulation of complex B proteins in the flagella. With the exception of the FLA11 gene, which encodes IFT172, a component of complex B (Pedersen et al. 2005), the gene products in this class are unknown (FLA2, FLA15, FLA16, FLA17, and FLA24). One might predict that mutations in this group would map to genes that encode complex A or retrograde motor subunits. Interestingly, IFT particles isolated from fla11, fla15, fla16, and fla17-1 flagella show depletion of complex A polypeptides (Piperno et al. 1998; Iomini et al. 2001). The inclusion of IFT172 in this class is explained by the observations that IFT172 plays a role in remodeling the IFT particles at the flagellar tip to transition from anterograde to retrograde movement (Pedersen et al. 2005). The remaining mutant strains do not show obvious defects in velocities, ratios, or accumulation at 21° and may reflect a less severe phenotype at the permissive temperature or a non-IFT role for these genes.Direct interactions occur between components of complex B. IFT81 and IFT74/72 interact to form a scaffold required for IFT complex B assembly (Lucker et al. 2005). IFT57 and IFT20 also interact with each other and kinesin-2 (Baker et al. 2003). While physical interactions are being used to define IFT particle architecture, genetic interactions among loci encoding IFT components should be instructive regarding their function as well. To probe retrograde movement and its function, we have identified the gene products encoded by two retrograde defective mutant strains. They are FLA15 and FLA17 and encode IFT144 and IFT139, respectively. The genetic interactions of these loci provide interesting clues about the assembly of the IFT particles and possible physical interactions in the IFT particles.  相似文献   

4.
5.
6.
The capacity for phenotypic evolution is dependent upon complex webs of functional interactions that connect genotype and phenotype. Wrinkly spreader (WS) genotypes arise repeatedly during the course of a model Pseudomonas adaptive radiation. Previous work showed that the evolution of WS variation was explained in part by spontaneous mutations in wspF, a component of the Wsp-signaling module, but also drew attention to the existence of unknown mutational causes. Here, we identify two new mutational pathways (Aws and Mws) that allow realization of the WS phenotype: in common with the Wsp module these pathways contain a di-guanylate cyclase-encoding gene subject to negative regulation. Together, mutations in the Wsp, Aws, and Mws regulatory modules account for the spectrum of WS phenotype-generating mutations found among a collection of 26 spontaneously arising WS genotypes obtained from independent adaptive radiations. Despite a large number of potential mutational pathways, the repeated discovery of mutations in a small number of loci (parallel evolution) prompted the construction of an ancestral genotype devoid of known (Wsp, Aws, and Mws) regulatory modules to see whether the types derived from this genotype could converge upon the WS phenotype via a novel route. Such types—with equivalent fitness effects—did emerge, although they took significantly longer to do so. Together our data provide an explanation for why WS evolution follows a limited number of mutational pathways and show how genetic architecture can bias the molecular variation presented to selection.UNDERSTANDING—and importantly, predicting—phenotypic evolution requires knowledge of the factors that affect the translation of mutation into phenotypic variation—the raw material of adaptive evolution. While much is known about mutation rate (e.g., Drake et al. 1998; Hudson et al. 2002), knowledge of the processes affecting the translation of DNA sequence variation into phenotypic variation is minimal.Advances in knowledge on at least two fronts suggest that progress in understanding the rules governing the generation of phenotypic variation is possible (Stern and Orgogozo 2009). The first stems from increased awareness of the genetic architecture underlying specific adaptive phenotypes and recognition of the fact that the capacity for evolutionary change is likely to be constrained by this architecture (Schlichting and Murren 2004; Hansen 2006). The second is the growing number of reports of parallel evolution (e.g., Pigeon et al. 1997; ffrench-Constant et al. 1998; Allender et al. 2003; Colosimo et al. 2004; Zhong et al. 2004; Boughman et al. 2005; Shindo et al. 2005; Kronforst et al. 2006; Woods et al. 2006; Zhang 2006; Bantinaki et al. 2007; McGregor et al. 2007; Ostrowski et al. 2008)—that is, the independent evolution of similar or identical features in two or more lineages—which suggests the possibility that evolution may follow a limited number of pathways (Schluter 1996). Indeed, giving substance to this idea are studies that show that mutations underlying parallel phenotypic evolution are nonrandomly distributed and typically clustered in homologous genes (Stern and Orgogozo 2008).While the nonrandom distribution of mutations during parallel genetic evolution may reflect constraints due to genetic architecture, some have argued that the primary cause is strong selection (e.g., Wichman et al. 1999; Woods et al. 2006). A means of disentangling the roles of population processes (selection) from genetic architecture is necessary for progress (Maynard Smith et al. 1985; Brakefield 2006); also necessary is insight into precisely how genetic architecture might bias the production of mutations presented to selection.Despite their relative simplicity, microbial populations offer opportunities to advance knowledge. The wrinkly spreader (WS) morphotype is one of many different niche specialist genotypes that emerge when experimental populations of Pseudomonas fluorescens are propagated in spatially structured microcosms (Rainey and Travisano 1998). Previous studies defined, via gene inactivation, the essential phenotypic and genetic traits that define a single WS genotype known as LSWS (Spiers et al. 2002, 2003) (Figure 1). LSWS differs from the ancestral SM genotype by a single nonsynonymous nucleotide change in wspF. Functionally (see Figure 2), WspF is a methyl esterase and negative regulator of the WspR di-guanylate cyclase (DGC) (Goymer et al. 2006) that is responsible for the biosynthesis of c-di-GMP (Malone et al. 2007), the allosteric activator of cellulose synthesis enzymes (Ross et al. 1987). The net effect of the wspF mutation is to promote physiological changes that lead to the formation of a microbial mat at the air–liquid interface of static broth microcosms (Rainey and Rainey 2003).Open in a separate windowFigure 1.—Outline of experimental strategy for elucidation of WS-generating mutations and their subsequent identity and distribution among a collection of independently evolved, spontaneously arising WS genotypes. The strategy involves, first, the genetic analysis of a specific WS genotype (e.g., LSWS) to identify the causal mutation, and second, a survey of DNA sequence variation at specific loci known to harbor causal mutations among a collection of spontaneously arising WS genotypes. For example, suppressor analysis of LSWS using a transposon to inactivate genes necessary for expression of the wrinkly morphology delivered a large number of candidate genes (top left) (Spiers et al. 2002). Genetic and functional analysis of these candidate genes (e.g., Goymer et al. 2006) led eventually to the identity of the spontaneous mutation (in wspF) responsible for the evolution of LSWS from the ancestral SM genotype (Bantinaki et al. 2007). Subsequent analysis of the wspF sequence among 26 independent WS genotypes (bottom) showed that 50% harbored spontaneous mutations (of different kinds; see Open in a separate windowFigure 2.—Network diagram of DGC-encoding pathways underpinning the evolution of the WS phenotype and their regulation. Overproduction of c-di-GMP results in overproduction of cellulose and other adhesive factors that determine the WS phenotype. The ancestral SBW25 genome contains 39 putative DGCs, each in principle capable of synthesizing the production of c-di-GMP, and yet WS genotypes arise most commonly as a consequence of mutations in just three DGC-containing pathways: Wsp, Aws, and Mws. In each instance, the causal mutations are most commonly in the negative regulatory component: wspF, awsX, and the phosphodiesterase domain of mwsR (see text).To determine whether spontaneous mutations in wspF are a common cause of the WS phenotype, the nucleotide sequence of this gene was obtained from a collection of 26 spontaneously arising WS genotypes (WSA-Z) taken from 26 independent adaptive radiations, each founded by the same ancestral SM genotype (Figure 1): 13 contained mutations in wspF (Bantinaki et al. 2007). The existence of additional mutational pathways to WS provided the initial motivation for this study.

TABLE 1

Mutational causes of WS
WS genotypeGeneNucleotide changeAmino acid changeSource/reference
LSWSwspFA901CS301RBantinaki et al. (2007)
AWSawsXΔ100-138ΔPDPADLADQRAQAThis study
MWSmwsRG3247AE1083KThis study
WSAwspFT14GI5SBantinaki et al. (2007)
WSBwspFΔ620-674P206Δ (8)aBantinaki et al. (2007)
WSCwspFG823TG275CBantinaki et al. (2007)
WSDwspEA1916GD638GThis study
WSEwspFG658TV220LBantinaki et al. (2007)
WSFwspFC821TT274IBantinaki et al. (2007)
WSGwspFC556TH186YBantinaki et al. (2007)
WSHwspEA2202CK734NThis study
WSIwspEG1915TD638YThis study
WSJwspFΔ865-868R288Δ (3)aBantinaki et al. (2007)
WSKawsOG125TG41VThis study
WSLwspFG482AG161DBantinaki et al. (2007)
WSMawsRC164TS54FThis study
WSNwspFA901CS301RBantinaki et al. (2007)
WSOwspFΔ235-249V79Δ (6)aBantinaki et al. (2007)
WSPawsR222insGCCACCGAA74insATEThis study
WSQmwsR3270insGACGTG1089insDVThis study
WSRmwsRT2183CV272AThis study
WSSawsXC472TQ158STOPThis study
WSTawsXΔ229-261ΔYTDDLIKGTTQThis study
WSUwspFΔ823-824T274Δ (13)aBantinaki et al. (2007)
WSVawsXT74GL24RThis study
WSWwspFΔ149L49Δ (1)aBantinaki et al. (2007)
WSXb???This study
WSYwspFΔ166-180Δ(L51-I55)Bantinaki et al. (2007)
WSZ
mwsR
G3055A
A1018T
This study
Open in a separate windowaP206Δ(8) indicates a frameshift; the number of new residues before a stop codon is reached is in parentheses.bSuppressor analysis implicates the wsp locus (17 transposon insertions were found in this locus). However, repeated sequencing failed to identify a mutation.Here we define and characterize two new mutational routes (Aws and Mws) that together with the Wsp pathway account for the evolution of 26 spontaneously arising WS genotypes. Each pathway offers approximately equal opportunity for WS evolution; nonetheless, additional, less readily realized genetic routes producing WS genotypes with equivalent fitness effects exist. Together our data show that regulatory pathways with specific functionalities and interactions bias the molecular variation presented to selection.  相似文献   

7.
Insertional mutagenesis screens play an integral part in the annotating of functional data for all sequenced genes in the postgenomic era. Chemical mutagenesis screens are highly efficient but identifying the causative gene can be a laborious task. Other mutagenesis platforms, such as transposable elements, have been successfully applied for insertional mutagenesis screens in both the mouse and rat. However, relatively low transposition efficiency has hampered their use as a high-throughput forward genetic mutagenesis screen. Here we report the first evidence of germline activity in the mouse using a naturally active DNA transposon derived from the medaka fish called Tol2, as an alternative system for high-throughput forward genetic mutagenesis screening tool.THE Tol2 (transposable element of Oryzias latipes, number 2) element belongs to the hAT family (hobo of Drosophilia, Activator of maize and Tam3 of snapdragon) of transposons and was the first known autonomously active vertebrate type II transposable element (Koga et al. 1996; Kawakami et al. 1998). Unlike other DNA-type transposons like Sleeping Beauty (SB) (Ivics et al. 1997) or piggyBac (PB) (Fraser et al. 1996), Tol2 does not exhibit any known strong site specificity for integration nor does it exhibit any significant overexpression inhibition activity (Kawakami and Noda 2004; Balciunas et al. 2006) as seen in SB (Geurts et al. 2003). Recently, Tol2 was shown to effectively carry large DNA cargo of up to 10 kb in human and mouse cells without affecting its transposition efficiency (Balciunas et al. 2006). To date, Tol2 has also been demonstrated to transpose efficiently in zebrafish, frog, chicken, mouse cells, and human cells (Kawakami et al. 2000, 2004; Koga et al. 2003; Kawakami and Noda 2004; Balciunas et al. 2006; Hamlet et al. 2006; Sato et al. 2007).Germline mutagenesis using the SB transposon system has been demonstrated in both the mouse (Dupuy et al. 2001; Horie et al. 2001) and rat (Kitada et al. 2007; Lu et al. 2007). In addition, PB germline mutagenesis in mice has also been demonstrated (Ding et al. 2005; Wu et al. 2007). However, the relatively low germline transposition efficiency of both transposon systems reported so far has hampered their use in a high-throughput forward genetic mutagenesis screen (Keng et al. 2005; Kitada et al. 2007).

TABLE 1

Germline transposition frequency in various transposon systems
Transposon systemAverage transposition events per gameteMouse strainReference
SB2FVB/NDupuy et al. (2001)
SB1.25C3H and C57BL/6Horie et al. (2001)
SB1.15C3H and C57BL/6Keng et al. (2005)
PB1.1FVB/NDing et al. (2005)
PB1C57BL/6Wu et al. (2007)
Tol2
3
FVB/N
Present study
Open in a separate windowSB, Sleeping Beauty; PB, piggyBac; Tol2, transposable element of Oryzias latipes, number 2.In search of an alternative tool for high-throughput forward germline mutagenesis screen in mice, a Tol2 transposon insertional mutagenesis system was generated on the basis of a similar strategy used for the SB transposon system (Horie et al. 2003; Keng et al. 2005). In the present study, we successfully demonstrate the novel use of the Tol2 transposon system for germline mutagenesis in mouse. Our results indicate the potential use of this transposon system for a high-throughput, large-scale forward mutagenesis screen in the mouse germline.  相似文献   

8.
9.
The biological, serological, and genomic characterization of a paramyxovirus recently isolated from rockhopper penguins (Eudyptes chrysocome) suggested that this virus represented a new avian paramyxovirus (APMV) group, APMV10. This penguin virus resembled other APMVs by electron microscopy; however, its viral hemagglutination (HA) activity was not inhibited by antisera against any of the nine defined APMV serotypes. In addition, antiserum generated against this penguin virus did not inhibit the HA of representative viruses of the other APMV serotypes. Sequence data produced using random priming methods revealed a genomic structure typical of APMV. Phylogenetic evaluation of coding regions revealed that amino acid sequences of all six proteins were most closely related to APMV2 and APMV8. The calculation of evolutionary distances among proteins and distances at the nucleotide level confirmed that APMV2, APMV8, and the penguin virus all were sufficiently divergent from each other to be considered different serotypes. We propose that this isolate, named APMV10/penguin/Falkland Islands/324/2007, be the prototype virus for APMV10. Because of the known problems associated with serology, such as antiserum cross-reactivity and one-way immunogenicity, in addition to the reliance on the immune response to a single protein, the hemagglutinin-neuraminidase, as the sole base for viral classification, we suggest the need for new classification guidelines that incorporate genome sequence comparisons.Viruses from the Paramyxoviridae family have caused disease in humans and animals for centuries. Over the last 40 years, many paramyxoviruses isolated from animals and people have been newly described (16, 17, 22, 29, 31, 32, 36, 42, 44, 46, 49, 58, 59, 62-64). Viruses from this family are pleomorphic, enveloped, single-stranded, nonsegmented, negative-sense RNA viruses that demonstrate serological cross-reactivity with other paramyxoviruses related to them (30, 46). The subfamily Paramyxovirinae is divided into five genera: Respirovirus, Morbillivirus, Rubulavirus, Henipavirus, and Avulavirus (30). The Avulavirus genus contains nine distinct avian paramyxovirus (APMV) serotypes (Table (Table1),1), and information on the discovery of each has been reported elsewhere (4, 6, 7, 9, 12, 34, 41, 50, 51, 60, 68).

TABLE 1.

Characteristics of prototype viruses APMV1 to APMV9 and the penguin virus
StrainHostDiseaseDistributionFusion cleavagecGI accession no.
APMV1/Newcastle disease virus>250 speciesHigh mortalityWorldwideGRRQKRF45511218
InapparentWorldwideGGRQGRLa11545722
APMV2/Chicken/CA/Yucaipa/1956Turkey, chickens, psittacines, rails, passerinesDecrease in egg production and respiratory diseaseWorldwideDKPASRF169144527
APMV3/Turkey/WI/1968TurkeyMild respiratory disease and moderate egg decreaseWorldwidePRPSGRLa209484147
APMV3/Parakeet/Netherlands/449/1975Psittacines, passerines, flamingosNeurological, enteric, and respiratory diseaseWorldwideARPRGRLa171472314
APMV4/Duck/Hong Kong/D3/1975Duck, geese, chickensNone knownWorldwideVDIQPRF210076708
APMV5/Budgerigar/Japan/Kunitachi/1974Budgerigars, lorikeetsHigh mortality, enteric diseaseJapan, United Kingdom, AustraliaGKRKKRFa290563909
APMV6/Duck/Hong Kong/199/1977Ducks, geese, turkeysMild respiratory disease and increased mortality in turkeysWorldwidePAPEPRLb15081567
APMV7/Dove/TN/4/1975Pigeons, doves, turkeysMild respiratory disease in turkeysUnited States, England, JapanTLPSSRF224979458
APMV8/Goose/DE/1053/1976Ducks, geeseNone knownUnited States, JapanTYPQTRLa226343050
APMV9/Duck/NY/22/1978DucksNone knownWorldwideRIREGRIa217068693
APMV10/Penguin/Falkland Islands/324/2007Rockhopper penguinsNone KnownFalkland IslandsDKPSQRIa300432141
Open in a separate windowaRequires the addition of an exogenous protease.bProtease requirement depends on the isolate examined.cPutative.Six of these serotypes were classified in the latter half of the 1970s, when the most reliable assay available to classify paramyxoviruses was the hemagglutination inhibition (HI) assay (61). However, there are multiple problems associated with the use of serology, including the inability to classify some APMVs by comparing them to the sera of the nine defined APMVs alone (2, 8). In addition, one-way antigenicity and cross-reactivity between different serotypes have been documented for many years (4, 5, 14, 25, 29, 33, 34, 41, 51, 52, 60). The ability of APMVs, like other viruses, to show antigenic drift as it evolves over time (37, 43, 54) and the wide use and availability of precise molecular methods, such as PCR and genome sequencing, demonstrate the need for a more practical classification system.The genetic diversity of APMVs is still largely unexplored, as hundreds of avian species have never been surveyed for the presence of viruses that do not cause significant signs of disease or are not economically important. The emergence of H5N1 highly pathogenic avian influenza (HPAI) virus as the cause of the largest outbreak of a virulent virus in poultry in the past 100 years has spurred the development of surveillance programs to better understand the ecology of avian influenza (AI) viruses in aquatic birds around the globe, and in some instances it has provided opportunities for observing other viruses in wild bird populations (15, 53). In 2007, as part of a seabird health surveillance program in the Falkland Islands (Islas Malvinas), oral and cloacal swabs and serum were collected from rockhopper penguins (Eudyptes chrysocome) and environmental/fecal swab pools were collected from other seabirds.While AI virus has not yet been isolated from penguins in the sub-Antarctic and Antarctic areas, there have been two reports of serum antibodies positive to H7 and H10 from the Adélie species (11, 40). Rare isolations of APMV1, both virulent (45) and of low virulence (8), have been reported from Antarctic penguins. Sera positive for APMV1 and AMPV2 have also been reported (21, 24, 38, 40, 53). Since 1981, paramyxoviruses have been isolated from king penguins (Aptenodytes patagonicus), royal penguins (Eudyptes schlegeli), and Adélie penguins (Pygoscelis adeliae) from Antarctica and little blue penguins (Eudyptula minor) from Australia that cannot be identified as belonging to APMV1 to -9 and have not yet been classified (8, 11, 38-40). The morphology, biological and genomic characteristics, and antigenic relatedness of an APMV recently isolated from multiple penguin colonies on the Falkland Islands are reported here. Evidence that the virus belongs to a new serotype (APMV10) and a demonstration of the advantages of a whole genome system of analysis based on random sequencing followed by comparison of genetic distances are presented. Only after all APMVs are reported and classified will epidemiological information be known as to how the viruses are moving and spreading as the birds travel and interact with other avian species.  相似文献   

10.
11.
Predator-prey relationships among prokaryotes have received little attention but are likely to be important determinants of the composition, structure, and dynamics of microbial communities. Many species of the soil-dwelling myxobacteria are predators of other microbes, but their predation range is poorly characterized. To better understand the predatory capabilities of myxobacteria in nature, we analyzed the predation performance of numerous Myxococcus isolates across 12 diverse species of bacteria. All predator isolates could utilize most potential prey species to effectively fuel colony expansion, although one species hindered predator swarming relative to a control treatment with no growth substrate. Predator strains varied significantly in their relative performance across prey types, but most variation in predatory performance was determined by prey type, with Gram-negative prey species supporting more Myxococcus growth than Gram-positive species. There was evidence for specialized predator performance in some predator-prey combinations. Such specialization may reduce resource competition among sympatric strains in natural habitats. The broad prey range of the Myxococcus genus coupled with its ubiquity in the soil suggests that myxobacteria are likely to have very important ecological and evolutionary effects on many species of soil prokaryotes.Predation plays a major role in shaping both the ecology and evolution of biological communities. The population and evolutionary dynamics of predators and their prey are often tightly coupled and can greatly influence the dynamics of other organisms as well (1). Predation has been invoked as a major cause of diversity in ecosystems (11, 12). For example, predators may mediate coexistence between superior and inferior competitors (2, 13), and differential trajectories of predator-prey coevolution can lead to divergence between separate populations (70).Predation has been investigated extensively in higher organisms but relatively little among prokaryotes. Predation between prokaryotes is one of the most ancient forms of predation (27), and it has been proposed that this process may have been the origin of eukaryotic cells (16). Prokaryotes are key players in primary biomass production (44) and global nutrient cycling (22), and predation of some prokaryotes by others is likely to significantly affect these processes. Most studies of predatory prokaryotes have focused on Bdellovibrionaceae species (e.g., see references 51, 55, and 67). These small deltaproteobacteria prey on other Gram-negative cells, using flagella to swim rapidly until they collide with a prey cell. After collision, the predator cells then enter the periplasmic space of the prey cell, consume the host cell from within, elongate, and divide into new cells that are released upon host cell lysis (41). Although often described as predatory, the Bdellovibrionaceae may also be considered to be parasitic, as they typically depend (apart from host-independent strains that have been observed [60]) on the infection and death of their host for their reproduction (47).In this study, we examined predation among the myxobacteria, which are also deltaproteobacteria but constitute a monophyletic clade divergent from the Bdellovibrionaceae (17). Myxobacteria are found in most terrestrial soils and in many aquatic environments as well (17, 53, 74). Many myxobacteria, including the model species Myxococcus xanthus, exhibit several complex social traits, including fruiting body formation and spore formation (14, 18, 34, 62, 71), cooperative swarming with two motility systems (64, 87), and group (or “wolf pack”) predation on both bacteria and fungi (4, 5, 8, 9, 15, 50). Using representatives of the genus Myxococcus, we tested for both intra- and interspecific variation in myxobacterial predatory performance across a broad range of prey types. Moreover, we examined whether prey vary substantially in the degree to which they support predatory growth by the myxobacteria and whether patterns of variation in predator performance are constant or variable across prey environments. The latter outcome may reflect adaptive specialization and help to maintain diversity in natural populations (57, 59).Although closely related to the Bdellovibrionaceae (both are deltaproteobacteria), myxobacteria employ a highly divergent mode of predation. Myxobacteria use gliding motility (64) to search the soil matrix for prey and produce a wide range of antibiotics and lytic compounds that kill and decompose prey cells and break down complex polymers, thereby releasing substrates for growth (66). Myxobacterial predation is cooperative both in its “searching” component (6, 31, 82; for details on cooperative swarming, see reference 64) and in its “handling” component (10, 29, 31, 32), in which secreted enzymes turn prey cells into consumable growth substrates (56, 83). There is evidence that M. xanthus employs chemotaxis-like genes in its attack on prey cells (5) and that predation is stimulated by close contact with prey cells (48).Recent studies have revealed great genetic and phenotypic diversity within natural populations of M. xanthus, on both global (79) and local (down to centimeter) scales (78). Phenotypic diversity includes variation in social compatibility (24, 81), the density and nutrient thresholds triggering development (33, 38), developmental timing (38), motility rates and patterns (80), and secondary metabolite production (40). Although natural populations are spatially structured and both genetic diversity and population differentiation decrease with spatial scale (79), substantial genetic diversity is present even among centimeter-scale isolates (78). No study has yet systematically investigated quantitative natural variation in myxobacterial predation phenotypes across a large number of predator genotypes.Given the previous discovery of large variation in all examined phenotypes, even among genetically extremely similar strains, we anticipated extensive predatory variation as well. Using a phylogenetically broad range of prey, we compared and contrasted the predatory performance of 16 natural M. xanthus isolates, sampled from global to local scales, as well as the commonly studied laboratory reference strain DK1622 and representatives of three additional Myxococcus species: M. flavescens (86), M. macrosporus (42), and M. virescens (63) (Table (Table1).1). In particular, we measured myxobacterial swarm expansion rates on prey lawns spread on buffered agar (31, 50) and on control plates with no nutrients or with prehydrolyzed growth substrate.

TABLE 1.

List of myxobacteria used, with geographical origin
Organism abbreviation used in textSpeciesStrainGeographic originReference(s)
A9Myxococcus xanthusA9Tübingen, Germany78
A23Myxococcus xanthusA23Tübingen, Germany78
A30Myxococcus xanthusA30Tübingen, Germany78
A41Myxococcus xanthusA41Tübingen, Germany78
A46Myxococcus xanthusA46Tübingen, Germany78
A47Myxococcus xanthusA47Tübingen, Germany78
A75Myxococcus xanthusA75Tübingen, Germany78
A85Myxococcus xanthusA85Tübingen, Germany78
TVMyxococcus xanthusTvärminneTvärminne, Finland79
PAKMyxococcus xanthusPaklenicaPaklenica, Croatia79
MADMyxococcus xanthusMadeira 1Madeira, Portugal79
WARMyxococcus xanthusWarwick 1Warwick, UK79
TORMyxococcus xanthusToronto 1Toronto, Ontario, Canada79
SUL2Myxococcus xanthusSulawesi 2Sulawesi, Indonesia79
KALMyxococcus xanthusKalalauKalalau, HI79
DAVMyxococcus xanthusDavis 1ADavis, CA79
GJV1Myxococcus xanthusGJV 1Unknown35, 72
MXFL1Myxococcus flavescensMx fl1Unknown65
MXV2Myxococcus virescensMx v2Unknown65
CCM8Myxococcus macrosporusCc m8Unknown65
Open in a separate window  相似文献   

12.
Identification of the select agent Burkholderia pseudomallei in macaques imported into the United States is rare. A purpose-bred, 4.5-y-old pigtail macaque (Macaca nemestrina) imported from Southeast Asia was received from a commercial vendor at our facility in March 2012. After the initial acclimation period of 5 to 7 d, physical examination of the macaque revealed a subcutaneous abscess that surrounded the right stifle joint. The wound was treated and resolved over 3 mo. In August 2012, 2 mo after the stifle joint wound resolved, the macaque exhibited neurologic clinical signs. Postmortem microbiologic analysis revealed that the macaque was infected with B. pseudomallei. This case report describes the clinical evaluation of a B. pseudomallei-infected macaque, management and care of the potentially exposed colony of animals, and protocols established for the animal care staff that worked with the infected macaque and potentially exposed colony. This article also provides relevant information on addressing matters related to regulatory issues and risk management of potentially exposed animals and animal care staff.Abbreviations: CDC, Centers for Disease Control and Prevention; IHA, indirect hemagglutination assay; PEP, postexposure prophylacticBurkholderia pseudomallei, formerly known as Pseudomonas pseudomallei, is a gram-negative, aerobic, bipolar, motile, rod-shaped bacterium. B. pseudomallei infections (melioidosis) can be severe and even fatal in both humans and animals. This environmental saprophyte is endemic to Southeast Asia and northern Australia, but it has also been found in other tropical and subtropical areas of the world.7,22,32,42 The bacterium is usually found in soil and water in endemic areas and is transmitted to humans and animals primarily through percutaneous inoculation, ingestion, or inhalation of a contaminated source.8, 22,28,32,42 Human-to-human, animal-to-animal, and animal-to-human spread are rare.8,32 In December 2012, the National Select Agent Registry designated B. pseudomallei as a Tier 1 overlap select agent.39 Organisms classified as Tier 1 agents present the highest risk of deliberate misuse, with the most significant potential for mass casualties or devastating effects to the economy, critical infrastructure, or public confidence. Select agents with this status have the potential to pose a severe threat to human and animal health or safety or the ability to be used as a biologic weapon.39Melioidosis in humans can be challenging to diagnose and treat because the organism can remain latent for years and is resistant to many antibiotics.12,37,41 B. pseudomallei can survive in phagocytic cells, a phenomenon that may be associated with latent infections.19,38 The incubation period in naturally infected animals ranges from 1 d to many years, but symptoms typically appear 2 to 4 wk after exposure.13,17,35,38 Disease generally presents in 1 of 2 forms: localized infection or septicemia.22 Multiple methods are used to diagnose melioidosis, including immunofluorescence, serology, and PCR analysis, but isolation of the bacteria from blood, urine, sputum, throat swabs, abscesses, skin, or tissue lesions remains the ‘gold standard.’9,22,40,42 The prognosis varies based on presentation, time to diagnosis, initiation of appropriate antimicrobial treatment, and underlying comorbidities.7,28,42 Currently, there is no licensed vaccine to prevent melioidosis.There are several published reports of naturally occurring melioidosis in a variety of nonhuman primates (NHP; 2,10,13,17,25,30,31,35 The first reported case of melioidosis in monkeys was recorded in 1932, and the first published case in a macaque species was in 1966.30 In the United States, there have only been 7 documented cases of NHP with B. pseudomallei infection.2,13,17 All of these cases occurred prior to the classification of B. pseudomallei as a select agent. Clinical signs in NHP range from subclinical or subacute illness to acute septicemia, localized infection, and chronic infection. NHP with melioidosis can be asymptomatic or exhibit clinical signs such as anorexia, wasting, purulent drainage, subcutaneous abscesses, and other soft tissue lesions. Lymphadenitis, lameness, osteomyelitis, paralysis and other CNS signs have also been reported.2,7,10,22,28,32 In comparison, human''s clinical signs range from abscesses, skin ulceration, fever, headache, joint pain, and muscle tenderness to abdominal pain, anorexia, respiratory distress, seizures, and septicemia.7,9,21,22

Table 1.

Summary of reported cases of naturally occurring Burkholderia pseudomalleiinfections in nonhuman primates
CountryaImported fromDate reportedSpeciesReference
AustraliaBorneo1963Pongo sp.36
BruneiUnknown1982Orangutan (Pongo pygmaeus)33
France1976Hamlyn monkey (Cercopithecus hamlyni) Patas monkey (Erythrocebus patas)11
Great BritainPhilippines and Indonesia1992Cynomolgus monkey (Macaca fascicularis)10
38
MalaysiaUnknown1966Macaca spp.30
Unknown1968Spider monkey (Brachytelis arachnoides) Lar gibbon (Hylobates lar)20
Unknown1969Pig-tailed macaque (Macaca nemestrina)35
Unknown1984Banded leaf monkey (Presbytis melalophos)25
SingaporeUnknown1995Gorillas, gibbon, mandrill, chimpanzee43
ThailandUnknown2012Monkey19
United StatesThailand1970Stump-tailed macaque (Macaca arctoides)17
IndiaPig-tailed macaque (Macaca nemestrina)
AfricaRhesus macaque (Macaca mulatta) Chimpanzee (Pan troglodytes)
Unknown1971Chimpanzee (Pan troglodytes)3
Malaysia1981Pig-tailed macaque (Macaca nemestrina)2
Wild-caught, unknown1986Rhesus macaque (Macaca mulatta)13
Indonesia2013Pig-tailed macaque (Macaca nemestrina)Current article
Open in a separate windowaCountry reflects the location where the animal was housed at the time of diagosis.Here we describe a case of melioidosis diagnosed in a pigtail macaque (Macaca nemestrina) imported into the United States from Indonesia and the implications of the detection of a select agent identified in a laboratory research colony. We also discuss the management and care of the exposed colony, zoonotic concerns regarding the animal care staff that worked with the shipment of macaques, effects on research studies, and the procedures involved in reporting a select agent incident.  相似文献   

13.
14.
Alexey Yanchukov 《Genetics》2009,182(4):1117-1127
A model of genomic imprinting with complete inactivation of the imprinted allele is shown to be formally equivalent to the haploid model of parental selection. When single-locus dynamics are considered, an internal equilibrium is possible only if selection acts in the opposite directions in males and females. I study a two-locus version of the latter model, in which maternal and paternal effects are attributed to the single alleles at two different loci. A necessary condition for the allele frequency equilibria to remain on the linkage equilibrium surface is the multiplicative interaction between maternal and paternal fitness parameters. In this case the equilibrium dynamics are independent at both loci and results from the single-locus model apply. When fitness parameters are additive, analytic treatment was not possible but numerical simulations revealed that stable polymorphism characterized by association between loci is possible only in several special cases in which maternal and paternal fitness contributions are precisely balanced. As in the single-locus case, antagonistic selection in males and females is a necessary condition for the maintenance of polymorphism. I also show that the above two-locus results of the parental selection model are very sensitive to the inclusion of weak directional selection on the individual''s own genotypes.PARENTAL genetic effects refer to the influence of the mother''s and father''s genotypes on the phenotypes of their offspring, not attributable just to the transfer of genes. Examples have been documented across a wide range of areas of organism biology; see, for example, Wade (1998) and and22 in Rasanen and Kruuk (2007). Parental selection is a more formal concept used in theoretical modeling and concerns situations where the fitness of the offspring depends, besides other factors, on the genotypes of its parent(s) (generalizing from Kirkpatrick and Lande 1989).

TABLE 1

Frequencies of genotypes and fitness parameterizations in model 1
Gametes/haploidsFrequency before selectionFitness
ZygoteMaleFemale
(A)AApfpm1 − α1 − δ
(A)a1/2 A 1/2 apf(1 − pm)11
(a)A1/2 a 1/2 A(1 − pf)pm1 − α1 − δ
(a)aA(1 − pf)(1 − pm)11
Open in a separate windowParentheses in the first column indicate maternal genotype (parental selection model) or inactivation of the maternally derived allele (imprinting model). Whether selection occurs at the diploid (first column) or subsequent haploid (second column) stage does not change the resulting allele frequencies.

TABLE 2

Offspring genotypic proportions from different mating types, sorted among four phenotypic groups/combinations of maternal and paternal effects: model 2
Offspring genotypes/phenotypes
Parental genotypes
Paternal (φ = 1)
Joint (φ = 4)
MaleFemaleABAbaBAbABAbaBab
ABAB1
Ab
aB
ab(1−r)/2r/2r/2(1−r)/2
AbAB
Ab1
aBr/2(1−r)/2(1−r)/2r/2
ab
Offspring genotypes/phenotypes
Parental genotypes
Maternal (φ = 2)
None (φ = 3)
MaleFemaleABAbaBAbABAbaBab
aBAB
Abr/2(1 − r)/2(1 − r)/2r/2
aB1
ab
abAB(1 − r)/2(1 − r)/2
Ab
aB
ab1
Open in a separate windowAnother well-known parent-of-origin phenomenon is genomic imprinting. Here, the level of expression of one of the alleles depends on which parent it is inherited from. Often it is difficult to tell apart the phenotypic patterns due to parental effects and genomic imprinting, and thus a problem arises in the process of identifying the candidate genes for such effects (Hager et al. 2008). Analytic methods (Weinberg et al. 1998; Santure and Spencer 2006; Hager et al. 2008) have been developed to quantify subtle differences between the two. In this article, I point out that a simple mathematical model, first suggested for genomic imprinting at a diploid locus, can be interpreted, without any formal changes, to describe parental selection on haploids.While there has been much progress in understanding the evolution of genomic imprinting (Hunter 2007), including advances in modeling (Spencer 2000, 2008), the population genetics theory of parental effects received less attention. Existing major-locus effect models of parental selection are single-locus, two-allele, and mostly concern uniparental (maternal) selection (Wright 1969; Spencer 2003; Gavrilets and Rice 2006; Santure and Spencer 2006), with only one specific case where the fitness effects of both parents interact studied by Gavrilets and Rice (2006). No attempt to extend this theory into multilocus systems has yet been made. Considering a two-locus model with both parents playing a role in selection on the offspring is called for by the observation that many maternal and paternal effects aim at the different traits or different life stages of their progeny. Among birds, for example, body condition soon after hatching is largely determined by the mother, while paternally transmitted sexual display traits develop much later in life (Price 1998). Such effects are therefore unlikely to be regulated within a single locus. Sometimes the effects are on the same trait, but still attributed to different loci: expression of gene Avy that causes the “agouti” phenotype (yellow fur coat and obesity) in mice is enhanced by maternal epigenetic modification (Rakyan et al. 2003), while paternal mutations at the other locus, MommeD4, contribute to a reverse phenotypic pattern in the offspring (Rakyan et al. 2003). The epigenetic state of the murine AxinFu allele is both maternally and paternally inherited (Rakyan et al. 2003).Focusing selection on haploids reduces the number of genotypes that need to be taken into account, while preserving the main properties of the multilocus system. Genes with haploid expression and a potential of parental effects can be found in two major taxonomic kingdoms. A notable candidate is Spam1 in mice, which is expressed during spermogenesis and encodes a factor that enables sperm to penetrate the egg cumulus (Zheng et al. 2001). This gene remains a target for effectively haploid selection, because its product is not shared via cytoplasm bridges between developing spermatides. Mutations at Spam1 alter performance of the male gametes that carry it and might indirectly, perhaps by altering the timing of fertilization, affect the fitness of the zygote. The highest estimated number of mouse genes expressed in the male gametes is currently 2375 (Joseph and Kirkpatrick 2004), and one might expect some of them to have similar paternal effects. Plants go through a profound haploid stage in their life cycles, and genes involved at this stage have an inevitable effect on the fitness of the future generations. In angiosperms, seed development is known to be controlled by both maternal (Chaudhury and Berger 2001; Yadegari and Drews 2004) and paternal (Nowack et al. 2006) effect genes, expressed, respectively, in female and male gametophytes.Under haploid selection, there can be no overdominance, and thus polymorphism is much more difficult to maintain than in diploid selection models (summarized in Feldman 1971). Nevertheless, differential or antagonistic selection between sexes can lead to a new class of stable internal equilibria in the diploid systems (Owen 1953; Bodmer 1965; Mandel 1971; Kidwell et al. 1977; Reed 2007), and I make use of this property in the haploid models developed below. In the experiment by Chippindale and colleagues (Chippindale et al. 2001), ∼75% of the total fitness variation in the adult stage of Drosophila melanogaster was negatively correlated between males and females, which suggests that a substantial portion of the fruit fly expressed genome is under sexually antagonistic selection. I assume that the effect of either parent on the fitness of the individual depends on the sex of the latter, which in respect to modeling is equivalent to the assumption of differential viability between the sexes in the progeny of the same parent(s). Biological systems that satisfy the latter assumptions can be found among colonial green algae: many members of the order Volvocales are haploid except for the short zygotic stage, and during sexual reproduction, they are also dioecious and anisogametic. I return to this example in the discussion. The possibility that genes expressed in animal gametes may be under antagonistic selection between sexes has been discussed (Bernasconi et al. 2004). For example, a (hypothetical) mutation increasing the ATP production in mitochondria would be beneficial in sperm, because of the increased mobility of the latter, but neutral or detrimental in the egg, due to a higher level of oxidative damage to DNA (Zeh and Zeh 2007).My main purpose was to derive conditions for existence and stability of the internal equilibria of the model(s). I begin with a simple one-locus case, which can be analyzed explicitly, and show how these one-locus results can be extended to the case of two recombining loci with multiplicative fitness. Then, I assume an additive relation between the maternal and paternal effect parameters and study the special cases where parental effects are symmetric.  相似文献   

15.
Plant secretory trichomes have a unique capacity for chemical synthesis and secretion and have been described as biofactories for the production of natural products. However, until recently, most trichome-specific metabolic pathways and genes involved in various trichome developmental stages have remained unknown. Furthermore, only a very limited amount of plant trichome genomics information is available in scattered databases. We present an integrated “omics” database, TrichOME, to facilitate the study of plant trichomes. The database hosts a large volume of functional omics data, including expressed sequence tag/unigene sequences, microarray hybridizations from both trichome and control tissues, mass spectrometry-based trichome metabolite profiles, and trichome-related genes curated from published literature. The expressed sequence tag/unigene sequences have been annotated based upon sequence similarity with popular databases (e.g. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Transporter Classification Database). The unigenes, metabolites, curated genes, and probe sets have been mapped against each other to enable comparative analysis. The database also integrates bioinformatics tools with a focus on the mining of trichome-specific genes in unigenes and microarray-based gene expression profiles. TrichOME is a valuable and unique resource for plant trichome research, since the genes and metabolites expressed in trichomes are often underrepresented in regular non-tissue-targeted cDNA libraries. TrichOME is freely available at http://www.planttrichome.org/.Plant trichomes are epidermal tissues located on the surfaces of leaves, petals, stems, petioles, peduncles, and seed coats depending on species. By virtue of their physical properties (size, density), trichome hairs can directly serve to protect buds of plants from insect damage, reduce leaf temperature, increase light reflectance, prevent loss of water, and reduce leaf abrasion (Wagner, 1991; Wagner et al., 2004).Although the morphology of trichomes varies greatly, they can be generally classified into two types: simple trichomes (STs) and glandular secreting trichomes (GSTs; Wagner et al., 2004). STs of Arabidopsis (Arabidopsis thaliana) have been chosen as models for studying cell fate and differentiation (Wagner, 1991; Breuer et al., 2009; Marks et al., 2009). In Arabidopsis, STs on leaves consist of a unicellular structure with a stalk and three to four branches (Fig. 1B). Although the STs are referred to as “nonglandular” (presumably nonsecreting), expression of genes involved in anthocyanin, flavonoid, and glucosinolate pathways can nevertheless be detected in STs, indicating the roles of STs in the biosynthesis of secondary compounds and defense (Wang et al., 2002; Jakoby et al., 2008). GSTs are found on about one-third of vascular plants. GSTs have a multicellular structure with a stalk terminating in a glandular head (Fig. 1, A and C–G). GSTs are initiated from a single protodermal cell that undergoes vertical enlargement and multiple divisions to give rise to fully developed trichomes. GSTs often produce and accumulate terpenoid and phenylpropanoid oils (Wagner et al., 2004). However, alkaloids, the third major class of plant secondary compounds, are not common in GST exudates (Laue et al., 2000). The amount of exudates produced by GSTs may reach 30% of mature leaf dry weight, as found in certain Australian desert plants (Dell and McComb, 1978). Plant GSTs can impact pathogen defense, pest resistance, pollinator attraction, and water retention based on the phytochemicals they secrete.Open in a separate windowFigure 1.Representative scanning electron microscopy images of trichomes on plants. A, Erect glandular trichome on the stem of M. sativa. B, Nonglandular trichome on a rosette leaf of Arabidopsis. C, Procumbent trichome on the petiole of M. truncatula. D, Field of glandular trichomes on a female bract of Cannabis sativa. E, Glandular trichomes on a bract of H. lupulus. F, Nonglandular trichome on a leaf of M. truncatula. G, Types VI (small arrow) and I (large arrow) trichomes on a leaf of S. lycopersicum. All the scanning electron microscopy images were generated as described previously (Ahlstrand, 1996; Esch et al., 2004) using an Emitech Technologies (www.emitech.co.uk) K1150 cyropreparation system and a Hitachi High Technologies (www.hitachi-hhta.com) S3500N scanning electron microscope. Bars = 100 μm.GSTs on the aerial organ surfaces have a unique capacity for synthesis and secretion of chemicals (largely plant secondary metabolites), and they have been described as “chemical factories” for the production of high-value natural products (Mahmoud and Croteau, 2002; Wagner et al., 2004; Schilmiller et al., 2008). Secondary metabolites play important roles in protecting the plant against insect predation and other biotic challenges (Peter and Shanower, 1998), and they are potential sources for pharmaceutical and nutraceutical product development. For example, the trichome-borne artemisinin from Artemisia annua is still the most effective drug against malaria, and the early steps of its biosynthetic pathway have been extensively studied (Duke et al., 1994; Arsenault et al., 2008). Recently, the mechanisms by which plant glandular trichomes make, transport, store, and secrete a great variety of unique compounds, especially terpenoids and flavoniods, have received extended research interest because of the potential use of these compounds in pharmaceutical and nutraceutical applications. Seminal studies have reported the assignment of gene functions to specific metabolic pathways in glandular trichomes of several plant species, including mint (Mentha × piperita; Alonso et al., 1992; Rajaonarivony et al., 1992; Lange et al., 2000), basil (Ocimum basilicum; Gang et al., 2002; Iijima et al., 2004; Xie et al., 2008), Artemisia (Teoh et al., 2006; Zhang et al., 2008), tomato (Solanum lycopersicum; Fridman et al., 2005; Besser et al., 2009; Schilmiller et al., 2009), and hop (Humulus lupulus; Nagel et al., 2008; Wang et al., 2008).
SpeciesTrichome Structure and ClassificationMetabolites
Arabidopsis thalianaNonglandular trichome, large, single epidermal cells with a stalk and three or four branches on the surface of most shoot-derived organs
Artemisia annuaBiseriate 10-celled glandular trichome, head including three apical cell pairs (Duke and Paul, 1993)Artemisinin, an endoperoxide sesquiterpene lactone
Cistus creticusGlandular trichome composed of a long multicellular stalk of over 200 μm topped by a small glandular head cell; two types of nonglandular trichome: multicellular stellate and simple unicellular spike (Gülz et al., 1996)Labdane-type components, such as ent-3′-acetoxy-13-epi-manoyl oxide and ent-13-epi-manoyl oxide (Falara et al., 2008)
Humulus lupulusPeltate glandular trichome with a glandular head consisting of 30 to 72 cells, four stalk cells, and four basal cells; bulbous glandular trichome, consisting of four (occasionally eight) head glandular cells, two stalk cells, and two basal cells; nonglandular trichome (cystolith hair) with a hard calcium carbonate structure at base of a hair (Oliveira et al., 1988; Nagel et al., 2008)Essential oil, including myrcene, humulene, and caryophyllene; bitter acids, including humulones and lupulones; prenylfalvonoids, including xanthohumol and desmethylxanthohumol (Wang et al., 2008)
Medicago sativaErect glandular trichome containing multicellular stalk typically over 200 μm long topped by a glandular head composed of a few cells with a diameter of approximately 15 μm; nonglandular trichome composed of a short base cell and a unicellular elongated shaft (Ranger and Hower, 2001)N-(3-Methylbutyl) amide of linoleic acid (Ranger et al., 2005)
Mentha × piperitaPeltate glandular trichome consisting of a basal cell, a stalk cell, and disc of eight glandular cells approximately 60 μm in diameter (McCaskill et al., 1992)Essential oils, such as p-menthanes; monoterpenes, including menthone and menthol
Nicotiana tabacumTall glandular trichome, a multicellular stalk topped by unicellular or multicellular head; short glandular trichome, a unicellular stalk topped by multicellular head (Akers et al., 1978)Labdene-diol diterpenes and amphipathic sugar esters (Lin and Wagner, 1994)
Ocimum basilicumPeltate glandular trichome consisting of a base cell, stalk cell, and a four-celled head; capitate glandular trichome, consisting of a single base and stock cell and one- to two-celled head; multicellular nonglandular spiked trichome (Werker et al., 1993)Phenylpropanoid eugenol, monoterpanoid linalool, and phenylpropanoid methylcinnanmate (Xie et al., 2008)
Salvia fruticosaType I consisting of one to two stalk cells and one to two enlarged, rounded to pear-shaped secretory head cells; type II consisting of one to two stalk cells and one elongated head cell as narrow as the stalk cells at its base and slightly enlarged above; type III consisting of two to five elongated stalk cells and rounded head in young leaves, which becomes cup shaped in mature leaves (Werker et al., 1985)Essential oils, such as α-pinene, 1,8-cineole, camphor, and borneol (Arikat et al., 2004)
Solanum habrochaitesType I glandular trichome, large in size with multicellular base; type III, intermediate in size with a single basal cell; type IV, a short, multicellular stalk that secretes droplets of sticky exudate at the tip; type V, short, slender, one to four celled; type VI, short with a two- to four-celled glandular head; type VII, 0.05- to 0.1-mm smaller glandular hair with a four- to eight-celled glandular head; type VI is particularly abundant (Reeves, 1977)Mainly α-santalene, α-bergamotene, and β-bergamotene; small amounts of α-humulene and β-caryophyllene (Besser et al., 2009)
Solanum lycopersicumSame as aboveMonoterpenes (Besser et al., 2009)
Solanum pennellii
Same as above but possesses high density of type IV glandular trichome (Lemke and Mutschler, 1984)
2,3,4-Triacylglucoses (Goffreda et al., 1989)
Open in a separate window“Omics” approaches are being extensively employed for systematically studying the molecular aspects of trichome development, metabolism, and secretion at the “systems biology” level, and data are being rapidly generated; however, currently, only limited omics data for plant trichomes are publicly available in the literature and scattered databases. For example, the National Center for Biotechnology Information (NCBI) dbEST (Boguski et al., 1993) hosts approximately 130,000 ESTs sampled from trichome cDNA libraries of 13 species (as of February 2009) or mixed tissues including trichomes. The public Minimum Information About a Microarray Experiment-compliant (Brazma et al., 2001) repository ArrayExpress (Parkinson et al., 2009) hosts 16 microarray hybridization experiments for Arabidopsis nonglandular trichomes, but there are no glandular trichome microarray data available in public databases so far. Lastly, we could not find large-scale metabolite profile data for plant trichomes from public omics databases, such as the AraCyc and MedicCyc databases (Mueller et al., 2003; Urbanczyk-Wochniak and Sumner, 2007).The omics data in publicly available databases are usually far from comprehensive and not integrated, as most of these data are in raw format. For example, EST/unigene and microarray data sets are not interlinked, and comparative analysis between trichome and nontrichome tissues for the identification of trichome-specific genes is absent. Therefore, to mine useful information such as trichome specificity of gene expression, signal strengths need to be normalized among hybridization experiments from both trichome and nontrichome tissues; to search a specific gene and deduce its potential function(s), sequences from cDNA libraries need to be annotated based on metabolic pathways and further cross-linked to metabolite profiles by catalytic reaction. Such data collection, integration, and mining processes pose great challenges to biologists interested in trichomes.To overcome the above limitations, we have developed TrichOME, an integrated genomic database for plant trichomes. TrichOME integrates omics data, such as EST/unigene sequences, microarray gene expression profiles, metabolite profiles, and literature-mining results. To assemble unigenes and pursue comparative analysis of gene expression, the database has integrated a large amount of EST sequence and gene expression profile data from nontrichome tissues as well. We processed, curated, and annotated the hosted data by referring to multiple popular biological databases to ensure the highest quality. TrichOME provides an interactive Web site (http://www.planttrichome.org/) for searching trichome-related ESTs/unigenes, microarray hybridizations, metabolites, and literature information.  相似文献   

16.
Evolutionary Strata in a Small Mating-Type-Specific Region of the Smut Fungus Microbotryum violaceum          下载免费PDF全文
Antonina A Votintseva  Dmitry A. Filatov 《Genetics》2009,182(4):1391-1396
DNA sequence analysis and genetic mapping of loci from mating-type-specific chromosomes of the smut fungus Microbotryum violaceum demonstrated that the nonrecombining mating-type-specific region in this species comprises ∼25% (∼1 Mb) of the chromosome length. Divergence between homologous mating-type-linked genes in this region varies between 0 and 8.6%, resembling the evolutionary strata of vertebrate and plant sex chromosomes.EVOLUTION of mating types or sex-determining systems often involves the suppression of recombination around the primary sex-determining or mating-type-determining locus. In animals and plants, it is often an entire or almost entire chromosome (Y or W in male or female heterogametic species, respectively) that ceases to recombine with its homologous (X or Z) chromosome (Charlesworth and Charlesworth 2000; Charlesworth 2008). Self-incompatibility loci in plants are also thought to be located in regions of suppressed recombination (Charlesworth et al. 2005; Kamau and Charlesworth 2005; Kamau et al. 2007; Li et al. 2007; Yang et al. 2007). Regardless of the phylogenetic position of a species, such nonrecombining regions are known to follow similar evolutionary trajectories. The nonrecombining region on the sex-specific chromosome expands in several steps, forming evolutionary strata—regions of different X/Y (or Z/W) divergence (Lahn and Page 1999; Handley et al. 2004; Sandstedt and Tucker 2004; Nicolas et al. 2005)—and genes in the nonrecombining regions gradually accumulate deleterious mutations that eventually render them dysfunctional (Charlesworth and Charlesworth 2005; Charlesworth 2008).Fungal mating-type systems are very diverse, with the number of mating types varying from two to several hundred (Casselton 2002). Like sex chromosomes in several animals and plants, suppressed recombination has evolved in regions near fungal mating-type loci, including in Ustilago hordei (Lee et al. 1999), Cryptococcus neoformans (Lengeler et al. 2002), and Neurospora tetrasperma (Menkis et al. 2008). These species have two mating types, but no morphologically distinct sexes. The mating-type locus (the region of suppressed recombination) of C. neoformans is small (∼100 kb) compared with known sex chromosomes and contains only ∼20 genes that, unlike many sex chromosomes (Y or W chromosomes), show no obvious signs of genetic degeneration (Lengeler et al. 2002; Fraser et al. 2004). Judging from the divergence between the homologous genes on the two mating-type-specific chromosomes, C. neoformans started to evolve sex chromosomes a long time ago because silent divergence between the two mating types in the most ancient region exceeds 100% (Fraser et al. 2004). Genes in the younger mating-type-specific region are much less diverged between the two sex chromosomes, suggesting that the evolution of the sex locus in C. neoformans might have proceeded through several steps. The nonrecombining region around the mating-type locus of N. tetrasperma is much larger than in C. neoformans (at least 6.6 Mb), and silent divergence between homologous genes on the mating-type-specific chromosomes ranges from zero to 9%, demonstrating that these mating-type-specific chromosomes evolved recently (Menkis et al. 2008).M. violaceum, which causes anther smut disease in Silene latifolia and other species in the family Caryophyllaceae, has two mating types, A1 and A2 (reviewed by Giraud et al. 2008), which are determined by the presence of mating-type-specific chromosomes (hereafter A1 and A2 chromosomes, or sex chromosomes) in the haploid stage of the life cycle (Hood 2002; Hood et al. 2004). The A1 and A2 chromosomes are distinguishable by size in pulsed-field electrophoresis, and it is possible to isolate individual chromosomes electrophoretically (Hood et al. 2004). Random fragments of A1 and A2 chromosomes have previously been isolated from mating-type-specific bands of pulsed-field separated chromosomes of M. violaceum (Hood et al. 2004). These fragments were assumed to be linked to mating type. The same method was used to isolate fragments of non-mating-type-specific chromosomes. On the basis of the analysis of their sequences, (Hood et al. 2004) proposed that mating-type-specific chromosomes in M. violaceum might be degenerate because they contained a lower proportion of protein-coding genes than other chromosomes. However, it was not determined whether the sequences isolated from the mating-type chromosomes originated from the mating-type-specific or from the recombining regions (Hood et al. 2004), and the relative sizes of these regions are not known for these M. violaceum chromosomes. We tested the mating-type specificity of 86 of these fragments and demonstrate that fewer than a quarter of these loci are located in the mating-type-specific region, suggesting that the nonrecombining region on the A1 and A2 chromosomes is quite small, while the rest of the chromosome probably recombines (like pseudoautosomal regions of sex chromosomes) and is therefore not expected to undergo genetic degeneration. Genetic mapping confirms the presence of two pseudoautosomal regions in the M. violaceum mating-type-specific chromosomes.As these chromosomes are mating type specific in the haploid stage of M. violaceum, mating-type-specific loci (or DNA fragments) can be identified by testing whether they are present exclusively in A1 or A2 haploid strains. We therefore prepared haploid A1 and A2 M. violaceum cultures from S. latifolia plants from two geographically remote locations (accessions Sl405 from Sweden and Sl127 from the French Pyrenees). Haploid sporidial cultures were isolated by a standard dilution method (Kaltz and Shykoff 1997; Oudemans and Alexander 1998). Mating types were determined by PCR amplification of each culture with primers designed for A1 and A2 pheromone receptor genes linked to A1 and A2 mating types (Yockteng et al. 2007). The primers were as follows: 5′-TGGCATCCCTCAATGTTTCC-3′ and 5′-CACCTTTTGATGAGAGGCCG-3′ for the A1 pheromone receptor (GenBank accession no. EF584742) and 5′-TGACGAGAGCATTCCTACCG-3′ and 5′-GAAGCGGAACTTGCCTTTCT-3′ for the A2 pheromone receptor (GenBank accession no. EF584741). Cultures with PCR product amplified only from an A1 or A2 pheromone receptor gene were selected for further use. The mating types of the cultures were verified by conjugating them in all combinations.The GenBank nucleotide database was searched using BLAST for sequences similar to those isolated by Hood et al. (2004). Sequences with similarity to transposable elements (TE) and other repeats were excluded. The resulting set of nonredundant sequences was used to design PCR primers for 98 fragments. Half of these were originally isolated from the A1 and half from the A2 chromosomes and are hereafter called A1-NNN or A2-NNN (where NNN is the locus number; supporting information, Table S1), which does not imply that these loci are A1 or A2 specific, but merely indicates that they were originally isolated from the A1 or A2 chromosomes. Amplification of these regions from new A1 and A2 M. violaceum cultures, independently isolated by ourselves, revealed that only 5 of the 49 loci isolated from the A1 chromosome are indeed A1 specific and only 6 of 49 isolated from the A2 chromosome are A2 specific. All other loci amplified from both A1 and A2 cultures. Figure 1 illustrates some of these results from the Swedish sample (Sl405).Open in a separate windowFigure 1.—Testing of mating-type specificity for loci isolated from A1 and A2 chromosomes. (a) PCR amplifications from haploid cultures from Sl405 using primers designed from six A1-originated loci. Loci in which a PCR product could be amplified only from A1 cultures (boxed) were classified as specific to mating type A1. (b) PCR tests of six A2-originated loci on the same set of haploids as in a. Loci in which a PCR product amplified only from A2 cultures (boxed) were classified as specific to mating type A2. Loci amplified from both A1 and A2 cultures are not mating type specific.The fragments that amplified from both A1 and A2 mating types may be in recombining regions, or they could be present in mating-type-specific regions on both A1 and A2 chromosomes. If they are in recombining regions, the A1- and A2-linked homologs should not be diverged from each other, but if they are in nonrecombining, mating-type-specific regions, the divergence of the A1- and A2-linked homologs should be roughly proportional to the time since recombination stopped in the region. We therefore sequenced and compared PCR fragments amplified from the two mating types of Sl405 or Sl127 cultures (GenBank accession nos. FI855822FI856001). Sequencing of PCR products showed that 12 (4 A1 and 8 A2) loci have more than one copy, and they were excluded from further analysis. Sequences of 61 loci were identical between the A1 and A2 strains, and four loci demonstrated low total divergence (0.24–0.61%) between the two mating types (otintseva and D. Filatov, unpublished results). Thus, these loci might be located in the recombining part of the mating-type-specific chromosomes. Ten of 75 loci that amplified in both mating types demonstrated multiple polymorphisms fixed between the mating types rather than between the locations. Given that the strains that we used in the analysis originated from two geographically distant locations, it is highly unlikely that multiple polymorphisms distinguishing the A1 and A2 sequences arose purely by chance; thus, these loci are probably located in the nonrecombining mating-type-specific region of the M. violaceum A1 and A2 chromosomes.

TABLE 1

Loci from mating-type-specific chromosomes of M. violaceum used for PCR analysis and genetic map construction
With nonzero A1/A2 divergenceb
LociMating type specific<1%>1%With zero A1/A2 divergencebTotal
A1a52 (1)3 (3)35 (3)45 (7)
A2a62 (0)7 (7)26 (3)41 (10)
Subtotal4 (1)10 (10)
Total1114 (11)61 (6)86 (17)
Open in a separate windowaA1, loci originated from the A1 sex chromosome; A2, loci originated from the A2 sex chromosome.bThe number of loci used for genetic map construction is in parentheses.To confirm the mating-type-specific or pseudoautosomal locations of the loci with and without A1/A2 divergence, we conducted genetic mapping in a family of 99 individuals, 50 of which were of mating type A1 and 49 of mating type A2. The family was generated by a cross between A1 and A2 M. violaceum strains from S. latifolia accessions Sl405 (Sweden) and Sl127 (France), respectively. The choice of strains from geographically distant locations was motivated by the hope of maximizing the number of DNA sequence differences between them that can be used as molecular genetic markers in segregation analysis. We inoculated S. latifolia seedlings with sporidial cultures of both mating types. For inoculation, petri dishes with 12-day-old seedlings of S. latifolia were flooded with 2.5 ml of inoculum suspension. Inoculum suspension consisted of equal volumes of the A1 and A2 sporidial cultures that were mixed and conjugated overnight at 14° under rotation (Biere and Honders 1996; Van Putten et al. 2003). Seedlings were potted 3 days after inoculation. Two months later, teliospores were collected from the flowers of the infected plant and grown in petri dishes on 3.6% potato dextrose agar medium. Haploid sporidia formed after meiosis were isolated and grown as separate cultures for DNA extraction. The mating types of single sporidia cultures were identified as described above. The loci analyzed in the segregation analysis were sequenced in the two parental haploid strains and in 99 (50 A1 and 49 A2) haploid strains that were generated in the cross. Single nucleotide differences between the parental strains were used as molecular genetic markers for segregation analysis in the progeny. The genetic map was constructed using MAPMAKER/EXP v3.0 (Lincoln et al. 1992) and MapDisto v1.7 (http://mapdisto.free.fr/).The resulting genetic map is shown in Figure 2. As expected, no recombination was observed between the 10 loci with diverged A1- and A2-linked copies. In addition, one marker with no A1/A2 divergence, A2-397, was also completely linked to the loci with significant A1/A2 divergence. This locus either may be very tightly linked to the nonrecombining mating-type-specific region or may have been added to that region more recently than the loci that had already accumulated some divergence between the alleles in the two mating types. The mating-type-specific pheromone receptor locus (Devier et al. 2009) and 11 mating-type-specific loci are also located in this nonrecombining region (Figure 2). Interestingly, the cluster of nonrecombining markers is flanked on both sides with markers that recombine in meiosis, demonstrating that there are pseudoautosomal regions on both ends of the mating-type-specific chromosomes.Open in a separate windowFigure 2.—Genetic map of the mating-type-determining chromosome in M. violaceum. Genetic distance (in centimorgans) and the relative positions of the markers are shown to the left and the right of the chromosome, respectively. The position of the nonrecombining region corresponds to the cluster of linked markers shown on the right of the figure. Total A1/A2 divergence is shown in parentheses. Eleven mating-type-specific markers (for which sequences are available from only one mating type), located in the nonrecombining mating-type-specific region, are not shown.Our results demonstrate that although the loci reported by Hood et al. (2004) were isolated from the A1 and A2 chromosomes, most of these loci are not located in the nonrecombining mating-type-specific regions. In fact, the nonrecombining region might be relatively small: of 86 tested fragments, only 21 appeared to be either mating type specific or linked to the mating-type locus. Assuming that these loci represent a random set of DNA fragments isolated from the A1 and A2 chromosomes, it is possible to estimate the size of the nonrecombining region using the binomial distribution: the nonrecombining region is expected to be 24.4% (95% CI: 16.7–33.6%) of the chromosome length. As the sizes of the A1 and A2 chromosomes are ∼3.4 and 4.2 Mb long (Hood 2002; Hood et al. 2004), the nonrecombining region might be ∼1 Mb long.Interestingly, total A1/A2 divergence for the 11 loci with A1- and A2-linked copies mapped to the nonrecombining region varied from 0% to 8.6% (Figure 2). In addition, 11 loci amplified from only one mating type. These genes could represent degenerated genes, some of which degenerated in A1 strains, and some in A2 strains. Alternatively, they might be highly diverged genes, such that the PCR primers amplify only one allele, and not the other. Variation in divergence may be the result of the stepwise cessation of recombination between the A1 and A2 chromosomes in M. violaceum, resembling the evolutionary strata reported for human, chicken, and white campion sex chromosomes (Lahn and Page 1999; Handley et al. 2004; Bergero et al. 2007). However, only the differences between the most and the least diverged loci are statistically significant (Devier et al. 2009), the M. violaceum mating-type region has at least three strata: one oldest stratum, including the pheromone receptor locus; a younger stratum with ∼5–9% A1/A2 divergence; and the youngest stratum with 1–4% divergence between the two mating types. There may also be an additional very recently evolved stratum containing the locus named A2-397, which is also present in all A1 strains tested, with no fixed differences between the A1 and A2 strains (No. of sites analyzedWithin A1
Within A2
Fixed differences between A1 and A2A1/A2 divergence (%)LociaSb totalSπ (%)cSπ (%)cA1/A2 divergence <1%A1-23645630020.4410.44A1-0456544000040.61A2-568413220.4820.4800.24A2-411480210.210010.31A1/A2 divergence >1%A1-2176679000091.35A1-12856990010.1881.49A1-199618130010.16122.02A2-4223449000092.62A2-516470140000142.98A2-404508200030.59173.64A2-4355062220.3920.39183.95A2-4734572310.2210.22214.81A2-4573031710.3300165.54A2-5755034750.9930.59398.55
Open in a separate windowaA1, loci originated from the A1 sex chromosome; A2, loci originated from the A2 sex chromosome.bS, number of polymorphic sites.cπ (%), average number of differences per 100 nucleotides.

TABLE 3

P-values for the 2 × 2 G-tests for significance of differences in A1/A2 divergence between the loci in the nonrecombining region
LaSbLocusA2-397A1-217A1-128A1-199A2-422A2-516A2-404A2-435A2-473A2-457
5190A2-397
6679A1-2170.006
5698A1-1280.0060.93
61812A1-1990.00070.410.48
3449A2-4220.00030.170.210.51
47014A2-5160.000030.060.0860.280.76
50817A2-40400.0250.0380.150.550.75
50618A2-43500.0150.0240.1040.450.620.86
45721A2-47300.0010.0030.01630.150.210.340.43
30316A2-45700.00090.00170.00970.090.130.2030.260.69
50339A2-5750000.000010.0020.0020.0030.0060.0550.199
Open in a separate windowP-values <0.05 are in boldface type.aL, the length of the region compared.bS, the number of nucleotide differences observed.As most of the loci isolated from the A1 and A2 chromosomes recombine in meiosis, they are not expected to degenerate. Thus, the observation of a higher proportion of TEs in these loci, compared to other chromosomes (Hood et al. 2004), is unlikely to reflect genetic degeneration attributable to a lack of recombination in these loci. A higher abundance of TEs in the sequences isolated from the A1 and A2 chromosomes, as reported by Hood et al. (2004), may simply reflect variation in the TE density across the genome. Thus, it remains to be seen whether M. violaceum mating-type-specific regions degenerate, similar to vertebrate Y (or W) chromosomes, or remain largely intact, as in C. neoformans (Lengeler et al. 2002). If the latter were the case, it may suggest that nonrecombining regions in fungi do not necessarily follow the same degenerative path as animal Y and W chromosomes. The analysis of sequences from the M. violaceum genome (and perhaps other fungal genomes) will hopefully provide the answer to this question.The lack of degeneration of mating-type-specific regions in C. neoformans may be due to the relatively small size of the nonrecombining regions. The 20 genes present in this region may not be sufficient for the operation of such detrimental population genetic processes as background selection or Muller''s ratchet because the speed of these processes depends critically on the number of active genes linked together (Charlesworth 2008). Larger mating-type-specific regions in M. violaceum might contain more genes; thus, more active genetic degeneration may be expected in this species. Indeed, many strains of M. violaceum show haplolethality linked to one of the mating types (Hood and Antonivics 2000; Thomas et al. 2003; Tellier et al. 2005), which may reflect the accumulation of deleterious mutations in the nonrecombining regions around the mating-type loci. Mating-type specificity of the markers that amplified in only A1 or A2 strains in this study may also reflect genetic degeneration.Another factor that may potentially prevent degeneration of genes linked to mating-type loci in fungi is the haploid expression of genes in these regions. In animals, many Y-linked genes have functional homologs on the X chromosome, and loss of the Y-linked gene may be compensated for by expression of the X-linked homologs. The haploid stage in an animal''s life cycle is very short, and very few genes are actively expressed in animal gametes (Schultz et al. 2003). In plants, on the other hand, a significant proportion of the genome is expressed in pollen (da Costa-Nunes and Grossniklaus 2003), and so the loss of Y-linked genes expressed in gametes may be more detrimental than in animals. Indeed, most genes isolated from the white campion X chromosome have intact Y-linked copies (Filatov 2005; Bergero et al. 2007), but due to the small number of genes available, it is still unclear whether genetic degeneration of Y-linked genes is indeed slower in this species (and in plants generally) compared to animal Y chromosomes. Haploid expression could be an even more powerful force in fungi and other organisms with haploid sexes, such as bryophytes, as most genes are expressed in the haploid stage. Further analysis of genetic degeneration in nonrecombining sex- or mating-type-specific regions in fungi and bryophytes will help to shed light on this question.  相似文献   

17.
Variation in Genomic Recombination Rates Among Heterogeneous Stock Mice          下载免费PDF全文
Beth L. Dumont  Karl W. Broman  Bret A. Payseur 《Genetics》2009,182(4):1345-1349
We used a large panel of pedigreed, genetically admixed house mice to study patterns of recombination rate variation in a leading mammalian model system. We found considerable inter-individual differences in genomic recombination rates and documented a significant heritable component to this variation. These findings point to clear variation in recombination rate among common laboratory strains, a result that carries important implications for genetic analysis in the house mouse.THE rate of recombination—the amount of crossing over per unit DNA—is a key parameter governing the fidelity of meiosis. Recombination rates that are too high or too low frequently give rise to aneuploid gametes or prematurely arrest the meiotic cell cycle (Hassold and Hunt 2001). As a consequence, recombination rates should experience strong selective pressures to lie within the range defined by the demands of meiosis (Coop and Przeworski 2007). Nonetheless, classical genetic studies in Drosophila (Chinnici 1971; Kidwell 1972; Brooks and Marks 1986), crickets (Shaw 1972), flour beetles (Dewees 1975), and lima beans (Allard 1963) have shown that considerable inter-individual variation for recombination rate is present within populations. Recent studies examining the transmission of haplotypes in human pedigrees have corroborated these findings (Broman et al. 1998; Kong et al. 2002; Coop et al. 2008).Here, we use a large panel of heterogeneous stock (HS) mice to study variation in genomic recombination rates in a genetic model system. These mice are genetically admixed, derived from an initial generation of pseudorandom mating among eight common inbred laboratory strains (DBA/2J, C3H/HeJ, AKR/J, A/J, BALB/cJ, CBA/J, C57BL/6J, and LP/J), followed by >50 generations of pseudorandom mating in subsequent hybrid cohorts (Mott et al. 2000; Demarest et al. 2001). The familial relationships among animals in recent generations were tracked to organize the mice into pedigrees. In total, this HS panel includes ∼2300 animals comprising 85 families, 8 of which span multiple generations. The remainder consists of nuclear families (sibships) that range from 1 to 34 sibs, with an average of 9.6 sibs (Valdar et al. 2006) (Mott et al. 2000; Demarest et al. 2001; Shifman et al. 2006).

TABLE 1

Heterogeneous stock mouse pedigrees
PedigreePedigree classNo. of nonoverlapping sibships in the pedigreeNo. of retained sibshipsNo. of meioses
1Multigenerational1717464
2Multigenerational2720728
3Multigenerational2319602
4Multigenerational149254
5Multigenerational119242
6Multigenerational5368
7Multigenerational43100
8Multigenerational2116
9Sibshipa2120
32–85Sibship511146
Total1801323640
Open in a separate windowaThis family was composed of two sibships sharing a common mother but with different fathers.With the exception of several founding individuals, most of these HS mice have been genotyped at 13,367 single nucleotide polymorphisms (SNPs) across the genome (available at http://gscan.well.ox.ac.uk/). Although the publicly available HS genotypes have passed data quality filters (Shifman et al. 2006), we took several additional measures to ensure the highest possible accuracy of base calls. First, data were cleansed of all non-Mendelian inheritances, and genotypes with quality scores <0.4 were removed. Genotypes that resulted in tight (<10 cM in sex-specific distance) double recombinants were also omitted because strong positive crossover interference in the mouse renders such closely spaced crossovers biologically very unlikely (Broman et al. 2002). A total of 10,195 SNPs (including 298 on the X chromosome) passed these additional quality control criteria; the results presented below consider only this subset of highly accurate (>99.98%) and complete (<0.01% missing) genotypes. The cleaned data are publicly available (at http://cgd.jax.org/mousemapconverter/).We used the chrompic program within CRI-MAP (Lander and Green 1987; Green et al. 1990) to estimate the number of recombination events in parental meioses. The algorithm implemented in chrompic first phases parent and offspring genotypes using a maximum-likelihood approach. Next, recombination events occurring in the parental germline are identified by comparing parent and offspring haplotypes across the genome (Green et al. 1990). For example, a haplotype that first copies from one maternal chromosome and then switches to copying from the other maternal chromosome signals a recombination event in the maternal germline.chrompic is very memory intensive and cannot handle the multigenerational pedigrees and the large sibships included in the HS panel. To circumvent these computational limitations, several modifications to the data were implemented. First, the eight multigenerational pedigrees were split into 102 nonoverlapping sibships, retaining grandparental information when available (Cox et al. 2009). Finally, large sibships were subdivided: sibships with >13 progeny were split into two groups: those with >26 progeny were split into three groups and those with >39 sibs were split into four groups. Partitioning large sibships by units of 10, 11, or 12, rather than 13, had no effect on the estimation of crossover counts, suggesting that the estimates were robust to the unit of subdivision. These subdivided families were used only for haplotype inference; all other analyses treated whole sibships as focal units. In total, we analyzed 132 nonoverlapping sibships, ranging in size from 2 to 48 sibs (mean = 13.9). This data set encompassed 3640 meioses—300–2000% more meioses than previously studied human pedigrees (Broman et al. 1998; Kong et al. 2002; Coop et al. 2008)—providing excellent power to detect recombination rate variation among individuals.The recombination rate for the maternal (or paternal) parent of a given sibship was estimated as the average number of recombination events in the haploid maternal (or paternal) genomes transmitted to her (or his) offspring. Our analyses treat males and females separately, as previous observations in mice (Murray and Snell 1945; Mallyon 1951; Reeves et al. 1990; Dietrich et al. 1996; Shifman et al. 2006; Paigen et al. 2008), along with findings from this study, point to systematically higher recombination rates in female than in male mice (this study: P < 2.2 × 10−16, Mann–Whitney U-Test comparing autosomal crossover counts in the 131 HS females to those in the 131 HS males).There is considerable recombination rate heterogeneity among the 131 mothers and 131 fathers in the HS pedigrees (Figure 1). The female with the highest recombination rate had an average of nearly twice as many crossovers per meiosis compared with the lowest (female range: 9.0–17.3; mean = 13.3; SD = 3.28). Similarly, the least actively recombining male had only 55% the amount of recombination as the male with the highest recombination rate (male range: 7.7–14.7; mean = 11.7; SD = 2.76). These average values are similar to previously reported recombination counts in house mice, determined using both cytological (Dumas and Britton-Davidian 2002; Koehler et al. 2002) and genetic (Dietrich et al. 1996) approaches. Note that the recombination rates that we report reflect the number of exchange events visible in genetic data. Under the assumption of no chromatid interference, the expected number of crossovers that occur at meiosis is equal to twice these values.Open in a separate windowFigure 1.—Variation in recombination frequency in HS mice. The mean number of recombination events per transmitted gamete in each mother (A; n = 131) and father (B; n = 131) was inferred by comparing parent and offspring genotypes at >10,000 autosomal and X-linked markers using the CRIMAP chrompic computer program. Error bars span ±2 SEs.To test for variation in recombination within the HS females and within the HS males, we performed a one-way ANOVA using parental identity as the factor and the recombination count for a single haploid genome transmission on the pedigree as the response variable. Significance of the resultant F-statistic was empirically assessed by randomizing parental identity with respect to individual recombination counts, recomputing the F-statistic on the permuted data set, and determining the quantile position of the observed F-statistic along the distribution of 106 F-statistics derived from randomization. There is highly significant variation for genomic recombination rate among HS females (F = 1.7842, P < 10−6; Figure 1A) and males (F = 2.3103, P < 10−6; Figure 1B).We next examined patterns of recombination rate inheritance using the eight complex families to test for heritability of this trait. We fit a polygenic model of inheritance using the polygenic command within SOLAR v.4, accounting for the uneven relatedness among individuals through a matrix of pairwise coefficients of relatedness (Almasy and Blangero 1998). Sex was included as a covariate in the model to account for the well-established differences between male and female recombination rates in mice (Murray and Snell 1945; Mallyon 1951; Reeves et al. 1990; Dietrich et al. 1996; Shifman et al. 2006; Paigen et al. 2008). Recombination rates show significant narrow-sense heritability (h2 = 0.46; SE = 0.20; P = 0.008), indicating that variation for recombination rate among HS mice is partly attributable to additive genetic variation. This result agrees with previous evidence for genetic effects on recombination rate variation in the house mouse (Reeves et al. 1990; Shiroishi et al. 1991; Koehler et al. 2002).In summary, we have shown that HS mice differ significantly in their genomic recombination rates and have demonstrated that this variation is heritable. These findings indicate that interstrain variation for genomic average recombination rate exists among at least two of the eight progenitor strains of the HS stock, mirroring observations of significant variation among inbred laboratory strains for many other quantitative characters (Grubb et al. 2009). Indeed, cytological analyses have already revealed significant differences in recombination frequencies between A/J and C57BL/6J males (Koehler et al. 2002), two of the HS founding strains.This interstrain variation in genomic recombination rate carries important practical implications for genetic analysis in the house mouse. Most notably, crosses using inbred mouse strains with high recombination rates will provide higher mapping resolution than crosses using strains with reduced recombination rates. However, the strategic use of high-recombination-rate strains will not necessarily expedite the fine mapping of loci. The distribution of recombination events in mice is not uniform across chromosomes and appears to be strain specific (Paigen et al. 2008; Grey et al. 2009; Parvanov et al. 2009).The history of the classical inbred mouse strains as inferred from pedigrees (Beck et al. 2000), sequence comparisons to wild mice (Salcedo et al. 2007), and genomewide phylogenetic analyses (Frazer et al. 2007; Yang et al. 2007) suggests that much of the interstrain variation for recombination rate arises from genetic polymorphism among Mus domesticus individuals in nature. However, many other factors have likely shaped recombination rate variation among the classical strains, including inbreeding, artificial selection, and hybridization with closely related species (Wade and Daly 2005). These aspects of the laboratory mouse''s history challenge comparisons between recombination rate variation in the HS panel and human populations and provide strong motivation for studies of recombination rate variation in natural populations of house mice.Although we find a strong genetic component to inter-individual variation in recombination rate, a large fraction (∼54%) of the phenotypic variation for recombination is not explained by additive genetic variation alone. Sampling error and other forms of genetic variation (e.g., dominance and epistasis) likely combine to account for some of the residual variation. In addition, micro-environmental differences within the laboratory setting (Koren et al. 2002) and life history differences among families, including parental age (Koehler et al. 2002; Kong et al. 2004), might contribute to variation in recombination rates among the HS mice.Identifying the genetic loci that underlie recombination rate differences among the HS mice (and hence in the eight founding inbred strains) presents a logical next step in the research program initiated here. The complicated pedigree structure, relatively small number of animals with recombination rate estimates (n = 262), and potentially sex-specific genetic architecture of this trait (Kong et al. 2008; Paigen et al. 2008) will pose challenges to this analysis. Nonetheless, dissecting the genetic basis of recombination rate variation is a pursuit motivated by its potential to lend key insights into several enduring questions. Why do males and females differ in the rate and distribution of crossover events? What are the evolutionary mechanisms that give rise to intraspecific polymorphism and interspecific divergence for recombination rate? What are the functional consequences of recombination rate variation? Alternative experimental approaches, including those that combine the power of QTL mapping with immunocytological assays for measuring recombination rates in situ (Anderson et al. 1999), promise to offer additional clues onto the genetic mechanisms that give rise to variation in this important trait.  相似文献   

18.
Immunomodulation by Mesenchymal Stem Cells in Veterinary Species     
Danielle D Carrade  Dori L Borjesson 《Comparative medicine》2013,63(3):207-217
Mesenchymal stem cells (MSC) are adult-derived multipotent stem cells that have been derived from almost every tissue. They are classically defined as spindle-shaped, plastic-adherent cells capable of adipogenic, chondrogenic, and osteogenic differentiation. This capacity for trilineage differentiation has been the foundation for research into the use of MSC to regenerate damaged tissues. Recent studies have shown that MSC interact with cells of the immune system and modulate their function. Although many of the details underlying the mechanisms by which MSC modulate the immune system have been defined for human and rodent (mouse and rat) MSC, much less is known about MSC from other veterinary species. This knowledge gap is particularly important because the clinical use of MSC in veterinary medicine is increasing and far exceeds the use of MSC in human medicine. It is crucial to determine how MSC modulate the immune system for each animal species as well as for MSC derived from any given tissue source. A comparative approach provides a unique translational opportunity to bring novel cell-based therapies to the veterinary market as well as enhance the utility of animal models for human disorders. The current review covers what is currently known about MSC and their immunomodulatory functions in veterinary species, excluding laboratory rodents.Abbreviations: AT, adipose tissue; BM, Bone marrow; CB, umbilical cord blood; CT, umbilical cord tissue; DC, dendritic cell; IDO, indoleamine 2;3-dioxygenase; MSC, mesenchymal stem cells; PGE2, prostaglandin E2; VEGF, vascular endothelial growth factorMesenchymal stem cells (MSC, alternatively known as mesenchymal stromal cells) were first reported in the literature in 1968.39 MSC are thought to be of pericyte origin (cells that line the vasculature)21,22 and typically are isolated from highly vascular tissues. In humans and mice, MSC have been isolated from fat, placental tissues (placenta, Wharton jelly, umbilical cord, umbilical cord blood), hair follicles, tendon, synovial membrane, periodontal ligament, and every major organ (brain, spleen, liver, kidney, lung, bone marrow, muscle, thymus, pancreas, skin).23,121 For most current clinical applications, MSC are isolated from adipose tissue (AT), bone marrow (BM), umbilical cord blood (CB), and umbilical cord tissue (CT; 11,87,99 Clinical trials in human medicine focus on the use of MSC both for their antiinflammatory properties (graft-versus-host disease, irritable bowel syndrome) and their ability to aid in tissue and bone regeneration in combination with growth factors and bone scaffolds (clinicaltrials.gov).131 For tissue regeneration, the abilities of MSC to differentiate and to secrete mediators and interact with cells of the immune system likely contribute to tissue healing (Figure 1). The current review will not address the specific use of MSC for orthopedic applications and tissue regeneration, although the topic is covered widely in current literature for both human and veterinary medicine.57,62,90

Table 1.

Tissues from which MSC have been isolated
Tissue source (reference no.)
SpeciesFatBone marrowCord bloodCord tissueOther
Cat1348356
Chicken63
Cow13812108
Dog973, 5978, 119139Periodontal ligament65
Goat66964
Horse26, 13037, 40, 12367130Periodontal ligament and gingiva88
Nonhuman primate28, 545
Pig1351147014, 20, 91
Rabbit1288032Fetal liver93
Sheep849542, 55
Open in a separate windowOpen in a separate windowFigure 1.The dual roles of MSC: differentiation and modulation of inflammation.Long-term studies in veterinary species have shown no adverse effects with the administration of MSC in a large number of animals.9,10,53 Smaller, controlled studies on veterinary species have shown few adverse effects, such as minor localized inflammation after MSC administration in vivo.7,15,17,45,86,92,98 Private companies, educational institutions, and private veterinary clinics (including Tufts University, Cummins School of Veterinary Medicine, University of California Davis School of Veterinary Medicine, VetStem, Celavet, Alamo Pintado Equine Medical Center, and Rood and Riddle Equine Hospital) offer MSC as a clinical treatment for veterinary species. Clinical uses include tendon and cartilage injuries, tendonitis, and osteoarthritis and, to a lesser extent, bone regeneration, spinal cord injuries, and liver disease in both large and small animals.38,41,113 Even with this broad clinical use, there have been no reports of severe adverse effects secondary to MSC administration in veterinary patients.  相似文献   

19.
Complexation and Toxicity of Copper in Higher Plants. II. Different Mechanisms for Copper versus Cadmium Detoxification in the Copper-Sensitive Cadmium/Zinc Hyperaccumulator Thlaspi caerulescens (Ganges Ecotype)     
Ana Mijovilovich  Barbara Leitenmaier  Wolfram Meyer-Klaucke  Peter M.H. Kroneck  Birgit G?tz  Hendrik Küpper 《Plant physiology》2009,151(2):715-731
The cadmium/zinc hyperaccumulator Thlaspi caerulescens is sensitive toward copper (Cu) toxicity, which is a problem for phytoremediation of soils with mixed contamination. Cu levels in T. caerulescens grown with 10 μm Cu2+ remained in the nonaccumulator range (<50 ppm), and most individuals were as sensitive toward Cu as the related nonaccumulator Thlaspi fendleri. Obviously, hyperaccumulation and metal resistance are highly metal specific. Cu-induced inhibition of photosynthesis followed the “sun reaction” type of damage, with inhibition of the photosystem II reaction center charge separation and the water-splitting complex. A few individuals of T. caerulescens were more Cu resistant. Compared with Cu-sensitive individuals, they recovered faster from inhibition, at least partially by enhanced repair of chlorophyll-protein complexes but not by exclusion, since the content of Cu in their shoots was increased by about 25%. Extended x-ray absorption fine structure (EXAFS) measurements on frozen-hydrated leaf samples revealed that a large proportion of Cu in T. caerulescens is bound by sulfur ligands. This is in contrast to the known binding environment of cadmium and zinc in the same species, which is dominated by oxygen ligands. Clearly, hyperaccumulators detoxify hyperaccumulated metals differently compared with nonaccumulated metals. Furthermore, strong features in the Cu-EXAFS spectra ascribed to metal-metal contributions were found, in particular in the Cu-resistant specimens. Some of these features may be due to Cu binding to metallothioneins, but a larger proportion seems to result from biomineralization, most likely Cu(II) oxalate and Cu(II) oxides. Additional contributions in the EXAFS spectra indicate complexation of Cu(II) by the nonproteogenic amino acid nicotianamine, which has a very high affinity for Cu(II) as further characterized here.Many heavy metals are well known to be essential microelements for plants, but elevated concentrations of these metals cause toxicity (for review, see Prasad and Hagemeyer, 1999; Küpper and Kroneck, 2005), as explained in more detail in our companion article (Küpper et al., 2009) on copper (Cu) complexation and toxicity in Crassula helmsii. Plants developed a number of strategies to resist this toxicity, including active efflux, sequestration, and binding of heavy metals inside the cells by strong ligands. Among the zinc (Zn) and cadmium (Cd) hyperaccumulators (Brooks, 1998; Lombi et al., 2000), the best known species is Thlaspi caerulescens, which has been proposed as a hyperaccumulator model species by several authors (Assunção et al., 2003; Peer et al., 2003, 2006). An enhanced uptake of metals into the root symplasm was found in T. caerulescens compared with the related nonaccumulator Thlaspi arvense (Lasat et al., 1996, 1998), and a reduced sequestration into the root vacuoles was associated with the higher root-to-shoot translocation efficiency of T. caerulescens (Shen et al., 1997; Lasat et al., 1998). This is likely related to elevated expression of xylem-loading transporters in the roots (Papoyan and Kochian, 2004; Weber et al., 2004). One of these, the Cd/Zn-pumping P1b-type ATPase TcHMA4, was recently purified as a protein, which revealed posttranslational processing, and its biochemical characterization showed Cd and Zn transport affinity in the submicromolar range (Parameswaran et al., 2007). Studies of cellular metal compartmentation have shown that in most hyperaccumulators, the metal is sequestered preferentially into compartments where it does no harm to the metabolism. These are, in most cases studied so far, the epidermal vacuoles (Küpper et al., 1999, 2001; Frey et al., 2000; Bidwell et al., 2004; Broadhurst et al., 2004), where concentrations of several hundred mmol L−1 can be reached in the large metal storage cells (Küpper et al., 1999, 2001). The latter showed that hyperaccumulation must be mediated by active pumping of the heavy metals into their storage sites, which was shown to be achieved by an extremely increased expression of metal transport proteins in leaves of hyperaccumulators compared with nonaccumulators (Pence et al., 2000; Assunção et al., 2001; Becher et al., 2004; Papoyan and Kochian, 2004; Küpper et al., 2007b). Strong sulfur (S) ligands like phytochelatins were shown not to be relevant for Cd detoxification in the Cd hyperaccumulator T. caerulescens. Phytochelatin levels are lower in this plant than in the related nonaccumulator T. arvense (Ebbs et al., 2002), inhibition of phytochelatin synthase in hyperaccumulators does not affect their Cd resistance (Schat et al., 2002), and direct measurements of the Cd ligands by EXAFS (Küpper et al., 2004). Thus, the main detoxification strategy in hyperaccumulators is clearly not binding to strong ligands but sequestration of the hyperaccumulated heavy metals. However, the nonproteogenic amino acid nicotianamine (NA) seems to play an important role in metal homeostasis of plants. According to several studies, it binds iron, Zn, and Cu, mainly for long-distance transport in the vascular bundle (Stephan and Scholz, 1993; Pich et al., 1994; Schmidke and Stephan, 1995; Stephan et al., 1996, Pich and Scholz, 1996; von Wiren et al., 1999; Liao et al., 2000), and NA synthase has been shown to be highly overexpressed in hyperaccumulators compared with nonaccumulator plants (Becher et al., 2004; Weber et al., 2004; van de Mortel et al., 2006, 2008).

Table I.

Explanation of technical terms
Technical TermExplanation/Definition
Antenna connectivityThe likelihood of energy transfer between antennae of different photosystems (PSII and/or PSI)
DWDebye-Waller factor of the EXAFS refinements, accounts for both structural and thermal disorder of the metal ion coordination shells (Binstead et al., 1992)
EFFermi energy of the EXAFS refinements, defines the threshold for the EXAFS spectra (Rehr and Albers, 2000)
EXAFSExtended x-ray absorption fine structure
FIFit index of the EXAFS refinements = sum of the square of the residuals (this is what is minimized in the refinement)
F0Minimal fluorescence yield of a dark-adapted sample, fluorescence in nonactinic measuring light
FmMaximum fluorescence yield of a dark-adapted sample after supersaturating irradiation pulse
FmMaximum fluorescence yield of a light-adapted sample after supersaturating irradiation pulse
FpFluorescence yield at the P level of the induction curve after the onset of actinic light exposure
Fv = FmF0Variable fluorescence
Fv/Fm = (FmF0)/FmMaximal dark-adapted quantum yield of PSII photochemistry
ΦPSII = Φe = (Fm′ − Ft′)/FmThe light-acclimated efficiency of PSII (Genty et al., 1989). In this article, the use of this parameter is extended to the relaxation period after the end of actinic light to analyze the return of the system to its dark-acclimated state as measured by Fv/Fm.
kWave number of the photoelectron, proportional to the square of the energy difference from the threshold energy (Efermi)
k-rangeEnergy range above the x-ray absorption edge of the metal where EXAFS was analyzed.
Light saturationMeasured by the increased amplitude of Fp relative to Fm after subtraction of F0. (FpF0)/(FmF0) is mostly dependent on the ratio of functional antenna molecules to functional reaction centers and electron transport chains. Under constant actinic irradiance for measuring Fp, a large antenna capturing photons and delivering them to its reaction center will cause more of the “electron traffic jam” that leads to Fp than a small antenna.
Multiple scatteringContributions in EXAFS that originate not from direct interaction between the central ion and another atom, but from interactions between the different atoms of a ligand molecule. This can only be observed in very rigid (parts of) ligand molecules, e.g. the imidazole ring of His. Further, the contribution is most significant for forward scattering at angles close to 180°, which is the case for the atoms in an imidazole ring.
NPQ = (FmFm′)/FmNonphotochemical quenching, in this article used as an acronym for the name of this phenomenon. In this article, we measure nonphotochemical quenching as qCN = “complete nonphotochemical quenching of Chl fluorescence”, i.e. with normalization to Fm.
ZAtomic number
Open in a separate windowUnder metal-induced stress, the heavy metal accumulation pattern changes. Under such conditions, heavy metal (Cd, nickel) accumulation was enhanced in a few cells of the mesophyll (Küpper et al., 2000a, 2001). The same cells contained elevated levels of magnesium, which was interpreted as a defense against substitution of Mg2+ in chlorophyll (Chl; Küpper et al., 1996, 1998, 2002) by heavy metals. Recently, it was found that this heterogeneity of Cd accumulation is a transient phenomenon in T. caerulescens under Cd-toxicity stress, correlating with a heterogeneity in photosynthesis and disappearing when the plants acclimate to the stress (Küpper et al., 2007a). It was postulated that this transient heterogeneity constitutes an emergency defense against Cd toxicity by sacrificing a few mesophyll cells as additional storage sites until the metal sequestration in the epidermis is sufficiently up-regulated. Furthermore, this acclimation response showed that at least part of the Cd resistance of T. caerulescens is inducible (Küpper et al., 2007a).While Cd resistance of T. caerulescens is strongly enhanced compared with related nonaccumulator plants, T. caerulescens is known to be sensitive to Cu to a similar extent as nonaccumulator plants, limiting its application for phytoremediating soils with mixed contamination (Walker and Bernal, 2004; Benzarti et al., 2008).In contrast to other metals, the speciation (redox state and coordination) of Cu in plant tissues is poorly understood, despite the detailed structural and functional knowledge about numerous Cu-dependent enzymes and Cu chaperones (for review, see Pilon et al., 2006). This is most likely due to the difficulty of measuring Cu speciation. The concentrations of Cu in plant tissue are too small for NMR and were too small for EXAFS for a long time. Methods relying on fractionation or homogenization of fresh tissues (e.g. for chromatography) cause breaking of intracellular membranes. This brings weakly bound metal that was localized in the vacuole into contact with the various strong ligands of the cytoplasm, causing artifactual changes of speciation. To our knowledge, so far only one EXAFS study on Cu speciation in plant tissues used environmental Cu concentrations: Polette et al. (2000) studied Cu speciation in the Cu-resistant Cu indicator plant Larrea tridentata. In their EXAFS measurements on samples frozen in liquid nitrogen, they found evidence for a Cu(II)-phytochelatin complex involved in transport and an unknown Cu complex involved in Cu storage. A second study using the same sample preparation method (that due to the formation of a gas layer around the sample slows freezing, resulting in ice formation with the risk of membrane damage) investigated the Cu-tolerant Cu-excluder plant Elsholtzia splendens (Shi et al., 2008). Unfortunately, these authors applied very high, physiologically not relevant Cu levels (300 μm) in their nutrient solution in order to force enough Cu into the tissues to get an acceptable signal-noise level in their EXAFS data within the limited synchrotron beam time. In two further Cu-EXAFS studies on plant tissues (Gardea-Torresdey et al., 2001, on L. tridentata; Sahi et al., 2007, on Sesbania drummondii), strong artifacts were most likely introduced by drying of tissues. Drying disrupts membranes as discussed above and can remove aquo ligands from metal ions (Schünemann et al., 1999). Additionally, extremely high Cu concentrations in the nutrient solution were applied to the plants (1,000 and 10,000 μm by Gardea-Torresdey et al., 2001; 400–5,000 μm by Sahi et al., 2007). Thus, the biological relevance of these studies has to be questioned.In this study, we addressed two related questions, both in comparison with the Cu accumulator C. helmsii described by Küpper et al. (2009). How do environmentally relevant (10 μm) toxic levels of Cu affect T. caerulescens? And how does the plant try to defend itself by binding the Cu ions? This was done by investigating mechanisms of Cu-induced inhibition of photosynthesis and analyzing the complexation of Cu in leaves. The latter was done in order to find out whether T. caerulescens utilizes different mechanisms for detoxification of the nonaccumulated Cu in comparison with the hyperaccumulated Cd. The speciation of Cu was analyzed by EXAFS, which is an element-specific method and therefore particularly suited for analyzing the in vivo ligand environment of metals in plants. Furthermore, in contrast to most other methods, it is applicable to intact frozen-hydrated plant tissues, which were first used by Salt et al. (1995). Moreover, EXAFS beamlines can now reach much lower metal concentrations than heteronuclear NMR (Ascone et al., 2003). So far, metal NMR was applied only in the case of Cd in T. caerulescens (Ueno et al., 2005), but although the concentration of this hyperaccumulated metal in the tissue was about 100 times higher than that of Cu, the NMR signal obtained was so weak that only the most abundant ligand type (organic acids, confirming previous EXAFS work [Küpper et al. 2004]) could be detected; everything else was drowned in noise. Thus, EXAFS is the method of choice for identifying ligands of both Cu(I) and Cu(II) in intact tissues in the absence of artifacts introduced by sample preparation (see above). EXAFS model complexes were prepared as references, and among these, Cu(II)-NA was characterized in more detail by UV/VIS and electron paramagnetic resonance (EPR) spectroscopy in view of its importance for Cu(II) binding in T. caerulescens. Inhibition of photosynthesis was investigated, as in our C. helmsii study, by the two-dimensional (imaging) microscopic in vivo measurement of the transients of Chl variable fluorescence with a recently described instrument, the fluorescence kinetic microscope (FKM; Küpper et al., 2007a). This was complemented with data on Cu accumulation, changes in pigment composition, and plant growth.  相似文献   

20.
A Targeted Multilocus Genotyping Assay for Lineage,Serogroup, and Epidemic Clone Typing of Listeria monocytogenes     
Todd J. Ward  Thomas Usgaard  Peter Evans 《Applied and environmental microbiology》2010,76(19):6680-6684
A 30-probe assay was developed for simultaneous classification of Listeria monocytogenes isolates by lineage (I to IV), major serogroup (4b, 1/2b, 1/2a, and 1/2c), and epidemic clone (EC) type (ECI, ECIa, ECII, and ECIII). The assay was designed to facilitate rapid strain characterization and the integration of subtype data into risk-based inspection programs.Listeria monocytogenes is a facultative intracellular pathogen that can cause serious invasive illness (listeriosis) in humans and other animals. L. monocytogenes is responsible for over 25% of food-borne-disease-related deaths attributable to known pathogens and is a leading cause of food recalls due to microbial adulteration (12, 21). However, not all L. monocytogenes subtypes contribute equally to human illness, and substantial differences in the ecologies and virulence attributes of different L. monocytogenes subtypes have been identified (9, 13, 14, 23, 24, 33, 35, 36). Among the four major evolutionary lineages of L. monocytogenes, only lineages I and II are commonly isolated from contaminated food and human listeriosis patients (19, 27, 29, 33). Lineage I strains are overrepresented among human listeriosis isolates, particularly those associated with epidemic outbreaks, whereas lineage II strains are overrepresented in foods and the environment (13, 14, 24). Lineage III strains account for approximately 1% of human listeriosis cases but are common among animal listeriosis isolates and appear to be a host-adapted group that is poorly adapted to food-processing environments (6, 34-36). The ecological and virulence attributes of lineage IV are poorly understood, as this lineage is rare and was only recently described based on a small number of strains (19, 26, 29, 33).L. monocytogenes is differentiated into 13 serotypes; however, four major serogroups (4b, 1/2b, 1/2a, and 1/2c) from within lineages I and II account for more than 98% of human and food isolates (16, 31). Serogroups refer to evolutionary complexes typified by a predominant serotype but which include very rare serotypes that represent minor evolutionary variants (7, 9, 33). Phylogenetic analyses have indicated that rare serotypes may have evolved recently, or even multiple times, from one of the major serotypes (9), and numerous molecular methods fail to discriminate minor serotypes as independent groups (1, 4, 7, 9, 18, 22, 33, 38, 39). Serotyping is one of the most common methods for L. monocytogenes subtyping, and serogroup classifications are a useful component of strain characterization because ecotype divisions appear largely congruent with serogroup distinctions (16, 34). Serogroup 4b strains are of particular public health concern because contamination with these strains appears to increase the probability that a ready-to-eat (RTE) food will be implicated in listeriosis (16, 28). Serogroup 4b strains account for approximately 40% of sporadic listeriosis and also are responsible for the majority of listeriosis outbreaks despite being relatively rare contaminants of food products (9, 13, 17, 30, 34). In addition, serogroup 4b strains are associated with more severe clinical presentations and higher mortality rates than other serogroups (11, 16, 20, 31, 34). Serogroups 1/2a and 1/2b are overrepresented among food isolates but also contribute significantly to human listeriosis, whereas serogroup 1/2c rarely causes human illness and may pose a lower risk of listeriosis for humans (16). Serogroup-specific differences in association with human listeriosis are consistent with the prevalence of virulence-attenuating mutations in inlA within these serogroups (32, 34); however, a number of additional factors likely contribute to these differences.Four previously described epidemic clones (ECs; ECI, ECIa, ECII, and ECIII) of L. monocytogenes have been implicated in numerous listeriosis outbreaks and have contributed significantly to sporadic illness (15, 34). ECI, ECIa, and ECII are distinct groups within serogroup 4b that were each responsible for repeated outbreaks of listeriosis in the United States and Europe. ECIII is a lineage II clone of serotype 1/2a that persisted in the same processing facility for more than a decade prior to causing a multistate outbreak linked to contaminated turkey (15, 25). While there has been speculation that epidemic clones possess unique adaptations that explain their frequent involvement in listeriosis outbreaks (9, 34, 37), it is not clear that epidemic clones are more virulent than other strains with the same serotype. However, contamination of RTE food with EC strains would be cause for increased concern due to the previous involvement of these clones in major outbreaks of listeriosis (16).As a result of the L. monocytogenes subtype-specific differences in ecology, virulence, and association with human illness, molecular subtyping technologies have the potential to inform assessments of relative risk and to improve risk-based inspection programs. The objective of the present study was to develop a single assay for rapid and accurate classification of L. monocytogenes isolates by lineage, major serogroup, and epidemic clone in order to facilitate strain characterization and the integration of subtype data into inspection programs that are based on assessment of relative risk.A database of more than 5.3 Mb of comparative DNA sequences from 238 L. monocytogenes isolates (9, 33-35) was scanned for single nucleotide polymorphisms that could be used to differentiate lineages, major serogroups, and epidemic clones via a targeted multilocus genotyping (TMLGT) approach. The acronym TMLGT is used to distinguish this approach from previously published multilocus genotyping (MLGT) assays that were lineage specific and designed for haplotype discrimination (9, 33). To provide for simultaneous interrogation of the selected polymorphisms via TMLGT, six genomic regions (Table (Table1)1) were coamplified in a multiplex PCR. While the previous MLGT assays were based on three lineage-specific multiplexes and required prior identification of lineage identity, TMLGT was designed to target variation across all of the lineages simultaneously and is based on a unique set of amplicons. PCR was performed in 50-μl volumes with 1× High Fidelity PCR buffer (Invitrogen Life Technologies), 2 mM MgSO4, 100 μM deoxynucleoside triphosphate (dNTP), 300 nM primer, 1.5 U Platinum Taq high-fidelity DNA polymerase (Invitrogen Life Technologies), and 100 ng of genomic DNA. PCR consisted of an initial denaturation of 90 s at 96°C, followed by 40 cycles of 30 s at 94°C, 30 s at 50°C, and 90 s at 68°C. Amplification products were purified using Montage PCR cleanup filter plates (Millipore) and served as a template for allele-specific primer extension (ASPE) reactions utilizing subtype-specific probes.

TABLE 1.

Primers used in multiplex amplification for the TMLGT assay
AmpliconPositionaGene(s)PrimerSequence (5′-3′)b
INLa455381-456505inlAinl2-a1GTCCTTGATAGTCTACTG
inl2-a2ACCAAATTAGTAATCTAGCAC
INLb457726-458752inlBinl-f1dGAATTRTTTAGYCAAGAATGT
inlb-rCTACCGGRACTTTATAGTAYG
LMO325116-326096lmo0298-lmo0300lmo-a1AAGGCTTACAAGATGGCT
lmo1a-1rAAATAATAYGTGATACCGAC
VGCa205366-206622plcA, hlyplca-fCTCATCGTATCRTGTGTACC
hly-rTCTGGAAGGTCKTGTAGGTTC
VGCb208447-209465mplra_mpl-fGTGGAYAGAACTCATAAAGG
ra_mpl-rACTCCCTCCTYGTGATASGCT
VGCc209728-211239actAvgc1a-2fTTCMATRCCAGCAGAACG
vgc1a-2rGCAGACCTAATAGCAATGTTG
Open in a separate windowaCorresponding nucleotide positions in the complete genome sequence of L. monocytogenes strain EGD-e (GenBank accession number NC_003210).bSee IUPAC codes for definition of degenerate bases.ASPE was performed in multiplex reactions including 30 probes, with each lineage (I to IV), major serogroup (4b, 1/2b, 1/2a, and 1/2c), and epidemic clone (ECI, ECIa, ECII, and ECIII) targeted by two different probes (Table (Table2).2). In addition, positive-control probes were included to confirm the presence of each amplicon in the multiplex PCR. As serogroups and epidemic clones are nested within a particular lineage, probes for these groups were designed to be specific within the appropriate lineage and values for these probes were evaluated only for isolates of the appropriate lineage. For example, serogroup 1/2a probes were evaluated only for isolates that were positive for lineage II probes. ASPE probes were designed with a unique 5′ sequence tag specific to individual sets of xMAP fluorescent polystyrene microspheres (Luminex Corporation) used to sort extension products. Extension and hybridization reactions were performed as described previously (9) except microspheres were twice pelleted by centrifugation (4 min at 2,250 × g) and resuspended in 75 μl 1× TM buffer prior to being pelleted and resuspended in 100 μl 1× TM buffer containing 2 μg/ml streptavidin-R-phycoerythrin (Invitrogen Life Technologies). Samples were incubated for 15 min at 37°C prior to detecting the microsphere complexes with a Luminex 100 flow cytometer (Luminex Corporation). The median fluorescence intensity (MFI) from biotinylated extension products attached to 100 microspheres was measured for each probe. The average MFI from three template-free control samples was also determined and subtracted from the raw MFI of each sample to account for background fluorescence. Probe performance was initially evaluated via the index of discrimination (ID) as described by Ducey et al. (9), and probes with ID values less than 2.0 were redesigned.

TABLE 2.

TMLGT probes and probe performance data
ProbebTarget (n)cProbe sequencedIDeSensitivity (%)Specificity (%)
VGCb-21Lineage I (506)AATCCTTTCTTTAATCTCAAATCAgcggaagcttgggaagcggtc7.3100100
VGCa-94Lineage ICTTTCTATCTTTCTACTCAATAATcaacccgatgttcttcctgtc51.7100100
VGCc-8Lineage II (340)AATCCTTTTACATTCATTACTTACattagctgattcgctttcct14.1100100
INLb-51Lineage IITCATTTCAATCAATCATCAACAATagcgccaataaagctggc21.9100100
VGCb-19Lineage III (50)TCAATCAATTACTTACTCAAATACccgctattaaaatgtactcca31.0100100
VGCb-29Lineage IIIAATCTTACTACAAATCCTTTCTTTggtataccgctattaaaatgt45.1100100
LMO-17Lineage IV (10)CTTTAATCCTTTATCACTTTATCAgaaccaaacaatgttattggt11.8100100
VGCa-27Lineage IVCTTTTCAAATCAATACTCAACTTTttaacgacggtaacgtgccac58.3100100
INLb-84Serogroup 4b (213)TCAACTAACTAATCATCTATCAATggtaaaaatatgcgaatattg9.7100100
INLb-85Serogroup 4bATACTACATCATAATCAAACATCActcgtgaacaagctttcc5.5100100
INLb-16Serogroup 1/2b (293)AATCAATCTTCATTCAAATCATCAggtaaaaatatgcgtatctta11.7100100
INLb-100Serogroup 1/2bCTATCTTTAAACTACAAATCTAACgtgaataagctatcggtctat13.0100100
LMO-42Serogroup 1/2a (268)CTATCTTCATATTTCACTATAAACtggcgttgctgrctaagtttg6.6100100
VGCb-40Serogroup 1/2aCTTTCTACATTATTCACAACATTAaatcaagcsgctcatatgaag10.410098.6
LMO-9Serogroup 1/2c (72)TAATCTTCTATATCAACATCTTACtttactggtgaaatggcg13.5100100
VGCb-5Serogroup 1/2cCAATTCAAATCACAATAATCAATCaagattacgaatcgcttccac20.898.6100
LMO-10ECI (111)ATCATACATACATACAAATCTACAatgattaaaagtcagggaaag19.0100100
LMO-28ECICTACAAACAAACAAACATTATCAAaatcgaggcttacgaacgt23.7100100
VGCc-80ECIa (44)CTAACTAACAATAATCTAACTAACactacaacgaaaacagcgc10.7100100
VGCa-35ECIaCAATTTCATCATTCATTCATTTCAgttacttttatgtcgagt9.2100100
LMO-12ECII (35)TACACTTTCTTTCTTTCTTTCTTTataccgattatttggacggtt3.8100100
LMO-30ECIITTACCTTTATACCTTTCTTTTTACgacttgtagcagttgatttcaa7.5100100
VGCc-45ECIII (10)TCATTTCACAATTCAATTACTCAActcttatttgcttttgttggtc21.110099.4
INLa-3ECIIITACACTTTATCAAATCTTACAATCgagcttaatgaaaatcagcta17.010099.4
INLa-1INLa controlCTTTAATCTCAATCAATACAAATCagaagtggaagctgggaaNAaNANA
INLb-13INLb controlCAATAAACTATACTTCTTCACTAAtgcacctaaacctccgacNANANA
LMO-88LMO controlTTACTTCACTTTCTATTTACAATCccgtttccttatgccacaNANANA
VGCa-23VGCa controlTTCAATCATTCAAATCTCAACTTTcaagycctaagacgccaatcgNANANA
VGCb-25VGCb controlCTTTTCAATTACTTCAAATCTTCAgcatgcgttagttcatgrccaNANANA
VGCc-82VGCc controlTACATACACTAATAACATACTCATgactgcatgctagaatctaagNANANA
Open in a separate windowaNA, not applicable for positive amplicon control probes.bLuminex microsphere sets (Luminex Corporation) used for hybridization reactions are indicated following the hyphen.cn, number of isolates representing the target subtype among the 906 tested isolates.dThe 5′ sequence tag portions of extension probes are capitalized. See IUPAC codes for definitions of degenerate bases.eID, index of discrimination.Validation of the TMLGT assay was performed using 906 L. monocytogenes isolates for which the lineage, major serogroup, and epidemic clone type had been determined independently (see Table S1 in the supplemental material). A subset of 92 isolates, including at least five isolates from each lineage, serogroup, and epidemic clone type, was used to evaluate the discriminatory power of subtype-specific probes and the repeatability of the assay (see Table S1). Two independent runs of the 30-probe TMLGT assay produced identical results for these 92 isolates. In addition, genotypes matched expectations for all isolate/probe combinations, and the fluorescence intensities for positive genotypes (those targeted by a particular probe) were 3.8 to 58.3 (mean, 18.5) times as high as background values for isolates with negative genotypes (those not targeted by a particular probe) (Table (Table2).2). The performances of individual probes also were assessed in terms of sensitivity and specificity, where sensitivity is defined as the percentage of positive samples that produced positive results and specificity indicates the percentage of negative samples that produce negative results (5). Based on results from all 906 isolates analyzed by TMLGT, probe sensitivity was at least 98.6% and 23 of the 24 subtype-specific probes exhibited 100% sensitivity (Table (Table2).2). The specificities for all probes were also greater than 98.6%, and 21 of the 24 subtype-specific probes exhibited 100% specificity (Table (Table22).All but three of the 906 isolates in the validation panel were fully and accurately typed relative to lineage, serogroup, and epidemic clone by using the TMLGT assay (typeability, 99.9%; accuracy of isolate assignment, 99.8%). One of the lineage II isolates, NRRL B-33880, could not be assigned to a serogroup based on the TMLGT results because this isolate was positive for one of the serogroup 1/2a probes (VGCb-40) and one of the serogroup 1/2c probes (LMO-9). This isolate was previously identified as a member of serogroup 1/2c based on mapping lineage-specific MLGT data onto a multilocus phylogeny (34) but produced a serogroup 1/2a-specific banding pattern (data not shown) with the multiplex PCR assay described by Doumith et al. (7). Similar strains, including the common laboratory strain EGD-e, were found to have genomes that are more similar to serogroup 1/2c strains than to strains from the 1/2a serogroup (8, 33) and likely represent intermediates in the evolution of the 1/2c clade from 1/2a ancestors. There is a poor correlation between genomic and antigenic variation for such isolates (34), consistent with the ambiguous results produced by application of the TMLGT assay to NRRL B-33880. The two other problematic isolates, NRRL B-33555 and NRRL B-33559, were accurately identified based on TMLGT data as lineage II isolates from the 1/2a serogroup. However, these two isolates were positive for both ECIII-specific probes in the TMLGT assay but have lineage-specific MLGT haplotypes (Lm2.46), indicating that they are representatives of a sister group closely related to ECIII (33).In 2005, the Food Safety and Inspection Service (FSIS) implemented an approach to inspection that includes consideration of relative risk in order to determine L. monocytogenes sampling frequency among establishments that produce certain RTE products. This approach incorporates information on production volume, outgrowth potential in the product, steps taken to prevent postlethality contamination, and FSIS sampling history. However, L. monocytogenes subtype-specific variation in ecology and virulence indicates that information on the lineage, major serogroup, and epidemic clone identities of isolates could be used to inform assessments of relative risk and to improve inspection programs that are based on consideration of risk. Several PCR-based methods have been described for differentiation of various combinations of these subgroups (1-3, 5, 7, 10, 35, 37); however, these approaches have focused on a single subgroup or a smaller set of subgroups than is differentiated by TMLGT analysis. Although we previously developed a set of three MLGT assays that can be used to differentiate all of the major serogroups and epidemic clones of L. monocytogenes (9, 33, 34), those assays did not include probes for lineage discrimination and require identification of the lineage prior to application of one of three unique sets of probes. In addition, the MLGT assays were designed to maximize strain discrimination, as opposed to subgroup identification, and require the use of at least twice as many probes as is needed for TMLGT analysis. MLGT data analysis is also more complicated than analysis of TMLGT data, and serogroup or epidemic clone type identification via MLGT requires phylogenetic analyses to place novel haplotypes within an established phylogenetic framework.In the present study, we developed the first assay for simultaneous discrimination of the four lineages, the four major serogroups, and the four previously described epidemic clones of L. monocytogenes. The assay includes multiple markers for each of these subtype probes as well as control probes to ensure that negative probe data were not the result of amplification failure, providing a high degree of internal validation required for use in inspection programs that consider risk in making sampling decisions. In addition, the utility of the assay has been validated with a large and diverse panel of 906 isolates, including 567 isolates from FSIS surveillance of RTE products and processing facilities (see Table S1 in the supplemental material). Data produced by the TMLGT assay are amenable to high-throughput analysis, and a simple spreadsheet utility has been developed to semiautomate subtype identifications and to alert investigators to potentially conflicting probe data (available upon request). In addition to having a potential application in inspection programs, the TMLGT assay provides a rapid and accurate means of characterizing L. monocytogenes isolates from different environments, which would facilitate pathogen tracking and improve understanding of L. monocytogenes ecology.   相似文献   

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