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It has been speculated that the γ-glutamyl transpeptidase (ggt) gene is present only in Neisseria meningitidis and not among related species such as Neisseria gonorrhoeae and Neisseria lactamica, because N. meningitidis is the only bacterium with GGT activity. However, nucleotide sequences highly homologous to the meningococcal ggt gene were found in the genomes of N. gonorrhoeae isolates.
The gonococcal homologue (
- g
- h
- g
This study has shown that the gonococcal ggh gene is a pseudogene of the meningococcal ggt gene, which can also be designated as Ψggt. The gonococcal ggh (Ψggt) gene is the first identified bacterial pseudogene that is transcriptionally active but phenotypically silent.
Two members of the gram-negative diplococci, Neisseria meningitidis and Neisseria gonorrhoeae, are particularly associated with pathological infections. N. meningitidis is specialized for the mucosa of the nasopharynx and causes meningitis and septicemia. N. gonorrhoeae is adapted for the mucosa of the urogenital tract and causes gonorrhoea and pelvic inflammatory diseases. Both species colonize only humans and share a great deal of relatedness at the nucleotide level [1]. This high degree of relatedness is reflected in the many common genetic, biochemical and antigenic features of the two bacteria.
γ-Glutamyl transpeptidase (also called γ-glutamyl aminopeptidase) (EC18.104.22.168; GGT) catalyzes the hydrolysis of γ-glutamyl compounds, and is found in a variety of bacteria such as Escherichia coli [2] and Helicobacter pylori [3,4]. To distinguish N. meningitidis from N. gonorrhoeae, GGT activity is used as one of the identification markers for N. meningitidis because N. meningitidis is positive for this activity but N. gonorrhoeae and related species, e.g., Neisseria lactamica, are not [5]. In fact, the detection of GGT activity is applied for the identification of N. meningitidis in the Gonochek II enzymatic identification system (E-Y Laboratories Inc., U.S.A.) [6-9]. From these empirical facts, it was believed that the gene encoding for GGT should exist only in N. meningitidis, but this has not been proven yet [3].
Recent remarkable progress in the sequencing of various genomes has led to the detection of nucleotide sequences that appear to be phenotypically silent, termed pseudogenes. The pseudogenes are defined as DNA sequences of formerly functional genes rendered nonfunctional by mutations and usually identified by their disrupted open reading frames (ORFs). Pseudogenes have been identified in a variety of eukaryotes, including insects [10], plants [11], and particularly vertebrates [10,12], but are relatively few in the bacterial genomes. Notable exceptions are intracellular bacterial parasites such as Rickettsia prowazekii and Mycobacterium leprae [13], which seem to have lost many genes due to obtaining nutritional supplies from the host cells. Cryptic genes such as the cel operon in E. coli [14-16] and the flagellar master operon in the genus Shigella [17-19] seem to be a kind of pseudogenes, but are different from pseudogenes because the cryptic genes completely retain intact ORFs, which can be occasionally activated by rare genetic events such as mutation, recombination, insertion of elements. As a whole, compared to the pseudogenes in eukaryotes, relatively few pseudogenes have been reported in bacterial genomes [20].
In this study, a gonococcal ggh gene, which is highly homologous to the meningococcal ggt gene, was found to be pseudogene. Sequence analyses of the flanking regions of both the ggt and ggh genes suggest that both genes were derived from a gene in a common ancestor, and subsequently diversified.
The gonococcal ggh gene was highly homologous to the meningococcal ggt gene
Since GGT activity was detected only in N. meningitidis among the related species, it was speculated that the corresponding gene also existed
only in N. meningitidis. However, by BLAST search, the nucleotide sequences highly homologous to the meningococcal
ggt gene were found in the genome of N. gonorrhoeae FA1090 [GenBank:NC_002946]. The overall nucleotide sequence of the meningococcal ggt homologue was approximately 95 % identical to that of the meningococcal ggt gene (data not shown and additional file). Eleven N. gonorrhoeae clinical strains were analyzed by PCR, and the corresponding DNA fragments were amplified
in all of these strains (Figure 1B), indicating that this gene was generally present in N. gonorrhoeae. To analyze whether ggt homologues existed in the genomes of the other neisserial strains, Southern blotting
was performed (Figure 1C). DNA fragments that hybridized with the meningococcal ggt gene were found in the meningococcal and gonococcal genomes (Figure 1C lanes 1–3) but not in the other neisserial genomes (Figure 1C lanes 4–11). These results suggested that the meningococcal ggt homologue was present only in N. gonorrhoeae among the neisserial species examined. The putative gene in N. gonorrhoeae was named ggh (
- g
- h
Figure 1. The presence of a meningococcal ggt gene homologue in N. gonorrhoeae. A. A schematic diagram showing the position of the set of primers used for the detection of ggt gene homologues. The black bar shows the region of the DNA probe used for Southern blotting in panel C. B. Amplification of gonococcal ggh gene by PCR. The genomic DNAs of neisserial species used for PCR were as follows: lane 1, H44/76 (N. meningitidis ggt+); lane 2, NIID113 (N. meningitidis ggt::IS) [49]; lane 3–13, ATCC49226, NIID54, NIID102, NIID103, NIID104, NIID105, NIID106, NIID107, NIID108, NIID109, NIID111 (N. gonorrhoeae). C. Southern blotting using the meningococcal ggt gene as a probe. Two micrograms of purified chromosomal DNA digested with ClaI were subjected to this analysis. Lane 1, H44/76 (N. meningitidis ggt+); lane 2, NIID113 (N. meningitidis ggt::IS) [49]; lane 3, NIID54 (N. gonorrhoeae); lane 4, ATCC23970 (N. lactamica); lane 5, ATCC13120 (N. flavescens); lane 6, ATCC14686 (N. denitrificans); lane 7, ATCC25295 (N. elongata); lane 8, ATCC14687 (N. canis); lane 9, ATCC14685 (N. cinerea); lane 10, NIID16 (N. mucosa); lane 11, NIID17 (N. sicca).
Variations of the nucleotide sequences of ggh genes among clinical isolates
To characterize the gonococcal ggh gene, the ggh genes were amplified from the chromosomal DNA of 11 N. gonorrhoeae strains and sequenced. The nucleotide sequences of the ggt genes from 7 N. meningitidis strains and of the ggh genes from the 11 N. gonorrhoeae strains were aligned, and the distance matrix calculated from these data was displayed as a phylogenetic tree (Figure 2A). The results revealed that the nucleotide sequences of the gonococcal ggh genes were more divergent than those of the meningococcal ggt genes (Figure 2A). Alignment of the nucleotide sequences of the 11 gonococcal ggh genes also showed that the mutations in the ggh gene consisted of the following four polymorphisms: 1) a 6-base insertion (named Type I), 2) an ochre mutation (Type II), 3) a 7-base deletion (Type III), 4) a 46-base insertion (Type IV) (Figure 2B and Table 2). In addition, all of the 11 ggh genes had one-nucleotide substitutions compared to the ggt genes in the same 25 sites (Figure 2B and additional file), with only 2 exceptions: a one-nucleotide variation in NIID109 (48th base A to G) and another in NIID105 (213th base G to A) (Table 2). The one-base substitutions in the common sites of the ggh genes strongly suggested that reconstruction of the ggh gene would have occurred at an early stage after speciation (See Discussion).
Figure 2. A. Split graph showing the relationships among ggt genes in 7 meningococcal strains and ggh genes in 11 gonococcal strains. The sequence data have been submitted to the DDBJ/EMBL/GenBank Databases under the following Accession Numbers:N. meningitidis strains H44/76 [DDBJ:AB089320], H114/90 [DDBJ:AB177989], 2996 [DDBJ:AB177990], NIID68 [DDBJ:AB177991], NIID76 [DDBJ:AB177992], NIID413 [DDBJ:AB177993] and NIID414 [DDBJ:AB177994]; N. gonorrhoeae strains ATCC49226 [DDBJ:AB175023], NIID54 [DDBJ:AB175024], NIID102 [DDBJ:AB193248], NIID103 [DDBJ:AB175025], NIID104 [DDBJ:AB175026], NIID105 [DDBJ:AB193249], NIID106 [DDBJ:AB175027], NIID107 [DDBJ:AB175028], NIID108 [DDBJ:AB193250], NIID109 [DDBJ:AB194328], NIID111 [DDBJ:AB193251]. The scale bar represents uncorrected distances, and a fit parameter is also shown. B. Alignment of the nucleotide sequences containing 4 kinds of differences in the ggt and ggh genes of N. meningitidis strains H44/76 and H114/90; N. gonorrhoeae strains ATCC49226, NIID54, NIID103 and NIID106, respectively. Sequence identity is represented as *, polymorphism among the sequences of the 6 strains is indicated by the appropriate letter, and the absence of a base is shown by a hyphen (-). The nucleotide substitution for an ochre (Type II) mutation is shown in bold. Boxes at the Type I and Type III mutations indicate the tandem repeat. The tetranucleotide repeat in type I is also shown as a gray box. The newly deduced start codon of the meningococcal GGT is shown in underlined bold.
Table 2. Mutation types found in the ggh genes of 11 N. gonorrhoeae strains
Putative amino acid sequences in hypothetical coding region of the ggh genes
Due to the ochre (Type II) and 7-base deletion (Type III) mutations, the ORF in each ggh gene was completely disrupted by the formation of 8 or 20 stop codons (Figure 3A). In fact, none of the gonococcal isolates showed any GGT activity (data not shown and [5,9]), indicating that there was no expression of functional GGT-like protein in N. gonorrhoeae. All of these results showed that the gonococcal ggh gene was a pseudogene of the functional ggt gene in N. meningitidis. On the other hand, if the two types of mutations (Types II and III) in the ggh genes were artificially corrected, the hypothetical amino acid sequences were approximately 97 % identical to those of the meningococcal ggt genes and were highly conserved among the gonococcal ggh genes (Figure 3B). This result also supported the idea that the ggh and ggt genes were derived from a common ancestral gene and that the translational inactivation of the gonococcal ggh gene was solely due to the ochre (Type II) and the frame-shift mutations caused by the 7-base deletion (Type III).
Figure 3. A. Positions of stop codons in the hypothetical ORF in the ggh gene. Black squares indicate the positions of stop codons and white squares indicate the ochre (Type II) mutation shown in Figure 2B. * indicates the position of the 7-bp deletion (Type III) mutation in the ggh gene. B. Putative translated products from the corrected nucleotide sequences of the ggh genes. The Type IV insertional mutation shown in Figure 2B is removed and the site of Type III deletion is replaced by the letter B. The site of the ochre (Type II) mutation is shown as X. The identical amino acid sequences between N. meningitidis and N. gonorrhoeae are shown in a black box and amino acid sequences common to only N. gonorrhoeae are shown in a gray box.
The genetic organization of the ggt- and ggh-flanking regions in the genomes of N. meningitidis and N. gonorrhoeae
By using the information in the database for N. meningitidis strain MC58 [21], N. gonorrhoeae strain FA1090 and N. lactamica (the neisserial species most closely related to the above two species) ST-640 strain, the flanking regions of the meningococcal ggt and the gonococcal ggh genes were further analyzed. The ggt and ggh genes were both localized in the identical gene cluster of fbp-ggt (or ggh)-glyA-opcA-dedA-abcZ in the genomes of N. meningitidis and N. gonorrhoeae, respectively (Figure 4). The fbp-glyA-dedA-abcZ locus was also found in the genome of N. lactamica but lacked the ggt and opcA homologues (Figure 4). This highly conserved genetic organization implied that a DNA island containing an original ggt gene was first incorporated into an ancestor's genome of the above three species and subsequently diversified after the speciation (see Discussion).
Figure 4. Genetic organization of the genes around the ggt and ggh genes in N. meningitidis strain MC58 [21], N. gonorrhoeae strain FA1090 [47] and N. lactamica strain ST-640 [48]. Black arrows and the open bar indicate coding and non-coding genes, respectively.
The expression of the ggh gene in N. gonorrhoeae
The hitherto identified bacterial pseudogenes are not expressed transcriptionally or translationally [20,22-24]. To examine the ggh transcriptional expression, dot blot analysis was first performed and RNA that hybridized with the ggt probe was detected in the total RNAs of 4 N. gonorrhoeae strains (Figure 5A). The transcriptional expression was also confirmed by RT-PCR, and the products were amplified with all 3 sets of primers from total RNA of all 4 N. gonorrhoeae strains tested (Figure 5B). These results strongly suggested that the full-length ggh gene transcript was expressed in N. gonorrhoeae. Primer extension analysis further revealed that the gonococcal ggh RNA was transcribed from the same starting point as the meningococcal ggt mRNA (Figure 5C and 5D). All of these results indicated that the gonococcal ggh gene was transcriptionally active though it was a pseudogene.
Figure 5. Transcriptional expression of the ggh genes. A. Dot blot analysis using the meningococcal ggt gene as a probe. One to 16 micrograms of RNAs isolated from H44/76, HT1089 (H44/76 Δggt::spc) [39], ATCC49226, NIID54, NIID103 and NIID106 were subjected to this analysis. B. RT-PCR to detect the transcripts of the gonococcal ggh genes. The schematic figure in the box depicts the position of the primers used in this experiment (see Table 1). RT-PCR was performed without reverse transcriptase (RTase) (lanes 1 to 5) or with RTase (lanes 6 to 10). Lanes 1 and 6, H44/76 (N. meningitidis); lanes 2 and 7, ATCC49226 (N. gonorrhoeae); lanes 3 and 8, NIID54 (N. gonorrhoeae); lanes 4 and 9, NIID103 (N. gonorrhoeae); lanes 5 and 10, NIID106 (N. gonorrhoeae). The marker in the left-most lane is φ X174 DNA digested with HaeIII. Primer sets used for RT-PCR are shown on the left side, and the corresponding PCR products are indicated by arrows on the right side. C. Primer extension analysis to detect the transcriptional start point of the ggt and ggh genes. Total RNA extracted from H44/76 (N. meningitidis), ATCC49226 and NIID106 (N. gonorrhoeae) was used for the primer extension with AMV reverse transcriptase XL and biotin-labeled oligonucleotide ggt-ext-2. The arrow on the right side indicates the transcriptional start site. D. Alignment of the nucleotide sequences of the upstream regions of the ggt and ggh genes. The sequence data have been deposited in the DDBJ/EMBL/GenBank Databases under the following Accession Numbers:N. meningitidis strains H44/76 [DDBJ:AB193252], H114/90 [DDBJ:AB193253], N. gonorrhoeae strains ATCC49226 [DDBJ:AB193254], NIID54 [DDBJ:AB193255], NIID103 [DDBJ:AB193296], NIID106 [DDBJ:AB193256]. An identical nucleotide is represented as *. The transcriptional start site is shown in bold as +1. The putative -35, -10 elements and Shine-Dalgarno sequence (SD) are depicted in the box, and the ideal -35 and -10 nucleotide sequences are shown above the boxes. The previously predicted start codon (ATG) [25] and newly predicted start codon (GTG) of the meningococcal {\it ggt} gene are underlined. The amino acid sequence deduced from the putative start codon GTG (shown in bold) in the meningococcal {\it ggt} gene is also shown under the corresponding nucleotide sequences.
To further study the translational expression of the truncated GGT-like protein in N. gonorrhoeae, Western blotting was performed with anti-meningococcal GGT rabbit antiserum [25]. When the same amounts of the whole cell extracts were analyzed (Figure 6B), approximately 15-kDa bands were detected in the extracts of NIID103 and NIID106 N. gonorrhoeae strains (Figure 6A lanes 5 and 7). Because the 15-kDa protein was not observed in the Δggh background of NIID103 and NIID106 (Figure 6A lanes 6 and 8), the 15-kDa protein was thought to be the ggh gene product whose translation was terminated at the 145th codon (Figure 3B). However, the 15-kDa protein was not found in the extracts of the ATCC49226 and NIID54 N. gonorrhoeae strains (Figure 6A, lanes 3 and 4) and seemed not to be expressed in any of the other gonococcal strains (see Discussion).
Figure 6. Western blotting with anti-meningococcal GGT rabbit antiserum [25] (A) and Coomassie Brilliant Blue staining (B) of the whole cell extracts after SDS-PAGE. Bacterial whole cell extracts equivalent to 0.025 OD600 were analyzed. Lane 1, N. meningitidis strain H44/76; lane 2, HT1089 (H44/76 Δggt::spc); lane 3, ATCC49226 (N. gonorrhoeae); lane 4, NIID54 (N. gonorrhoeae); lane 5, NIID103 (N. gonorrhoeae); lane 6, HT1195 (NIID103 Δggh::spc); lane 7, NIID106 (N. gonorrhoeae); lane 8, HT1196 (NIID106 Δggh::spc). Black arrows show the bands corresponding to the processed small and large subunits of meningococcal GGT and the gray arrow indicates the 15-kDa band corresponding to the truncated protein product of the gonococcal ggh gene. M stands for molecular weight marker.
In this study, it was shown that the gonococcal ggh gene is a member of bacterial pseudogenes, and is transcribed but not properly translated so that active ggh protein product is not produced. 11Fh-mtTFA [26], OsMu4-2 [27], NA88-A [28], Makorin1-p1 [29], Dnm3a2 [30] and pseudoNOS [31] genes are known to be transcriptionally active eukaryotic pseudogenes. In neisseriae, the gonococcal porA and ΨopcB genes have been reported as neisserial pseudogenes [1,32,33]. The porA pseudogene contains mutations in the promoter and the coding regions, and is not translated [24]. While some hypothetical bacterial pseudogenes with repetitive runs of A and T are speculated to be potentially expressed by transcriptional slippage [34], the expression, including the transcription, has not been proven yet. To our knowledge, the gonococcal ggh gene is the first identified bacterial pseudogene that is transcriptionally active.
The 15-kDa derivative of the putative ggh protein product is detected in the NIID103 and NIID106 N. gonorrhoeae strains but not in the ATCC49226 and NIID54 N. gonorrhoeae strains (Figure 6A). Since the predicted amino acid sequences of the putative 15-kDa proteins seem to be similar among the 4 gonococcal strains, the reason why the 15-kDa protein was not detected in ATCC49226 and NIID54 is not clear. The 15-kDa protein might be degraded in ATCC49226 and NIID54 backgrounds but not in NIID103 and NIID106 backgrounds. It seems unlikely that the 15-kDa protein encoded by the ggh gene has an essential function for N. gonorrhoeae because the 15-kDa protein is not always detected in any of gonococcal strains (Figure 6A).
Why does the gonococcal ggh gene still retain the transcriptional activity? There are some examples in which RNAs transcribed from pseudogenes have some biological functions: antisense RNA expressed from the pseudoNOS gene hybridizes with nNOS (nitric oxide synthase) mRNA, resulting in the suppression of the nNOS gene expression in the neurons of the snail Lymnaea stagnalis [31]. RNA of Makorin1-1p, a pseudogene of Makorin1, regulates the Makorin1 mRNA stability, which is important for the correct formation of the kidneys and bone in mice [29]. Some eukaryotic genes may be duplicated and one of the plural genes may be subsequently reconstructed due to its redundancy, resulting in a pseudogene. However, since a bacterial pseudogene generally does not have a functional counterpart (wild-type gene) in a single organism, the ggh RNA does not seem to have the same kind of biological function as the pseudoNOS and Makorin1-1p genes. In fact, we could not find any prominent phenotype for a Δggh gonococcal mutant (unpublished data). However, we cannot exclude the possibility that the ggh RNA has some biological function(s) in other milieus such as the urogenital tract and further analyses will be required to address this possibility.
The ggt and ggh genes are located in the fbp-ggt (ggh)-glyA-opcA-dedA-abcZ common gene cluster in the genomes of both N. meningitidis and N. gonorrhoeae (Figure 4) [23]. The genome of N. lactamica lacks ggt and opcA homologues in the fbp-glyA-dedA-abcZ locus (Figure 4 and [23]). It would not be the result of chance that the two ggt (or ggh) and opcA genes are located in the same respective sites of the fbp-glyA-dedA-abcZ gene locus of both N. meningitidis and N. gonorrhoeae but not in that of N. lactamica. Moreover, it is also unlikely that a nonfunctional ggh gene was horizontally transferred into the gonococcal fbp-glyA-opcA-dedA-abcZ gene cluster since such a pseudogene could not have been sustained due to the lack of selection [23]. Therefore, it seems more probable that the fbp-ggt-glyA-opcA-dedA-abcZ gene cluster was present in an ancestor of the three neisserial species, and has been subsequently diversified independently among the three species, as shown for the opcA gene [23]. During the diversification, the meningococcal ggt gene has been maintained in an active state while the gonococcal ggh gene has been reconstructed by insertion, deletion and substitutions, resulting in the translational inactivation. In N. lactamica, the ggt and opcA homologues might have been lost because of their dispensability for N. lactamica (see below).
It is also interesting that the ggh gene has not been fully deleted from the gonococcal genome. The kinds and sites of mutations in the ggh genes are relatively few and highly conserved, respectively, among the gonococcal isolates (Figure 2B, Table 2 and additional file). It is also noted that, while in general the RNA polymerase-binding sites and SD regions of pseudogenes are highly degraded, there are also a few exceptions in species such as Y. pestis that could have emerged in recent evolutionary times [35]. Since the ribosome-binding sites (Shine-Dalgarno regions) of the gonococcal ggh gene are identical to those of the meningococcal ggt gene and the RNA polymerase-binding sites are almost completely conserved (with a one-nucleotide difference) (Figure 5D), it is speculated that the reconstruction of the ggh gene may have occurred in relatively recent evolutionary times. From the evolutional viewpoint, the drastic deletion of the approximately 2-kb DNA region containing the ggh gene in N. gonorrhoeae may not have been likely to occur in such a short period. Alternatively, deletion of the 2-kb DNA region may not be more advantageous for gonococcal evolution than reconstruction involving short deletions, insertions and substitutions.
The maintenance of a functional ggt gene in N. meningitidis would have some advantages for its survival. N. meningitidis causes meningitis, which is due to the meningococcal invasion into the human central nervous system, including cerebrospinal fluid (CSF) [36-38]. It has been shown that meningococcal GGT has a physiological function of acquiring cysteine from environmental γ-glutamyl-cysteinyl peptides under cysteine-limited environments such as the CSF [39]. Almost all (98.8 %) meningococcal isolates from humans are positive for GGT activity [40]. All of these results suggest that the GGT activity is important for N. meningitidis but not for N. gonorrhoeae. The dispensability of GGT activity for N. gonorrhoeae seems to be consistent with the fact that a cysteine-limited milieu such as the CSF in humans is not a natural gonococcal habitat. However, it is not very likely that the milieu of CSF exerts selective pressure for an active ggt gene because human CSF is not a relevant milieu for human-to-human spread of meningococcus [41]. We believe that the meningococcal GGT must have some unknown essential function(s) for N. meningitidis and further studies will elucidate the function(s).
Our data on the ggh gene indicate that the ggh gene in N. gonorrhoeae is a pseudogene of the functional ggt gene in N. meningitidis. To our knowledge, the ggh gene is the first reported bacterial pseudogene that is transcriptionally active but phenotypically silent. Our findings may also contribute to understanding the speciation of N. meningitidis and N. gonorrhoeae.
Bacterial strains and growth conditions
Seven N. meningitidis strains (H44/76, H114/90, 2996, NIID68, NIID76, NIID413 and NIID414) were described in our previous reports [42,43]. Ten N. gonorrhoeae strains (NIID54, NIID102, NIID103, NIID104, NIID105, NIID106, NIID107, NIID108, NIID109 and NIID111), one N. mucosa strain (NIID16) and one N. sicca strain (NIID17) were clinical isolates donated by T. Kuroki and Y. Watanabe. All of the clinical strains were mutually independent: they were isolated in different periods and from different persons who lived in different areas of Japan. The following 7 neisserial strains were obtained from ATCC (species / ATCC no.): N. gonorrhoeae / ATCC49226; N. lactamica / ATCC23970; N. flavescence / ATCC13120; N. denitrificans / ATCC14686; N. elongata / ATCC25295; N. canis / ATCC14687; N. cinerea / ATCC14685. All of the strains were stored by the gelatin disc method [42] and cultivated on GC agar (Becton-Dickinson) supplemented with 1 % IsovitaleX enrichment (Becton-Dickinson) at 37°C in 5 % CO2, or in GC broth (1.5 % proteose-peptone, 0.5 % NaCl, 0.05 % soluble starch, 0.1 % K2HPO4, 0.4 % KH2PO4, 1 % IsoVitaleX, 5 mM NaHCO3 10 mM MgCl2) at 37°C with shaking.
Isolation of chromosomal DNA, PCR, Southern blotting and dot blotting
Isolation of chromosomal DNA, PCR, Southern blotting and dot blotting were performed as described in our previous report [43].
Nucleotide sequence determination and analyses
The ggt and ggh genes were amplified with a set of primers (ggt-3 and ggt-4) by PCR, and the resulting products were purified using High Pure PCR Product Purification Kit (Roche) as templates for sequencing. The sequencing was performed as described previously [25]. Primers used for sequencing are listed in Table 1. Raw data from the ABI sequencer were assembled with the program DNASIS ver. 3.2 (HITACHI, Japan). The sequence alignment was performed with GENETYX-MAC ver.11 (GENETYX, Japan). Phylogenetic analyses were performed by constructing a distance matrix of nucleotide mismatches using the web site of the Belozersky Institute at Moscow State University [44] and visualized by Split decomposition analysis with the program SPLITSTREE, version 3.2 [45].
Table 1. Oligonucleotides used in this study
Construction of Δggh::spc N. gonorrhoeae mutants
HT1195 (NIID103 Δggh::spc) and HT1196 (NIID106 Δggh::spc), in which a spectinomycin resistance gene (spc) was inserted into the ggh gene, were constructed as follows: A 2-kb fragment containing the ggh gene of NIID103 or NIID106 was amplified by PCR and cloned in the SmaI site of pUC18 (Takara Bio) to construct pHT412 or pHT413, respectively. A blunted 1-kb fragment containing the spc gene [25] was inserted into the EcoRV sites of pHT412 and pHT413, respectively. The EcoRV sites are located at 277 bp and 1642 bp (NIID103 [DDBJ:AB175025]) and at 271 bp and 1590 bp (NIID106 [DDBJ:AB175027]) downstream from the transcriptional start point of each ggh gene, respectively (see Figure 5D). The resulting plasmids were named pHT414 and pHT415, respectively. Five hundred nanograms of the plasmids linearized by digestion with EcoRI were transformed into NIID103 and NIID106, respectively, as described previously [43]. Spectinomycin-resistant clones were selected on GC agar plates containing 75 μg/ml spectinomycin. The resulting mutants were isolated as Δggh::spc NIID103 (HT1195), and Δggh::spc NIID106 (HT1196), respectively. The allelic exchange was confirmed by PCR and Southern blotting.
Bacteria grown on GC agar plates were suspended in 20 ml of GC broth to an OD600 of 0.1 and continuously cultured to mid-log phase (OD600 of ~ 0.6) at 37°C with shaking. The total RNA was isolated from the harvested bacteria as previously described [46] with an additional treatment with DNase I. RT-PCR was performed using one step RT-PCR Kit Ver. 1.1 (Takara Bio, Japan) with approximately 2 μg of total RNA according to the manufacturer's instructions. The products were visualized by electrophoresis in a 2 % agarose gel followed by ethidium bromide staining.
Primer extension analysis
Fifty micrograms of total RNA and 5 pmol of biotin-labeled primer (ggt-ext-2) were hybridized in 20 μl of buffer (10 mM Tris-HCl, pH 8.0, 1 mM EDTA, 250 mM KCl). The hybridized RNA-DNA probe was treated with 35 units of AMV reverse transcriptase (RTase) XL (Takara Bio) in a reaction mixture (250 μM dNTPs, 1 × AMV reverse transcriptase XL buffer) at 37°C for 30 min. The ethanol-precipitated DNA product was dissolved in 20 μl of formamide dye (80 % formamide, 10 mM NaOH, 1 mM EDTA, 0.025 % bromophenol blue, 0.025 % xylene cyanol). Sequencing of the ggt and ggh genes with the ggt-ext-2 primer was performed by using ΔTh polymerase sequencing high -cycle- (TOYOBO, Japan). Aliquots of the reaction products were analyzed by electrophoresis on 8 % acrylamide-7 M urea gel followed by capillary blotting to Hybond-N+ (Amersham). The bands were visualized with Imaging high (TOYOBO) according to the manufacturer's protocol.
SDS-PAGE and Western blotting
SDS-PAGE and Western blotting were performed as described previously [43] using 1 × 103-fold diluted anti-GGT polyclonal rabbit antiserum [25] and 2 × 103-fold diluted horseradish peroxidase-conjugated secondary antibody (Amersham)
GGT, γ-glutamyl transpeptidase; IS, insertional sequence; ORF, open reading frame; RTase, reverse transcriptase
Authors' contributions
HT carried out all of the studies including molecular genetic studies, sequence determination, sequence analyses and drafting the manuscript. HW made a critical reading of the manuscript and final approval of the version to be published.
Additional File 1. Alignment of the nucleotide sequences within the ggt and ggh genes of N. meningitidis H44/76 [DDBJ:AB089320]; N. meningitidis H119/90 [DDBJ: AB211221]; N. gonorrhoeae ATCC49226 [DDBJ:AB175023]; N. gonorrhoeae NIID103 [DDBJ:AB175025] and N. gonorrhoeae NIID106 [DDBJ:AB175029] strains, respectively. Sequence identity is represented as *, polymorphism within the sequences of the 5 strains is indicated by the appropriate letter, and the absence of a base is shown with a hyphen (-).
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We thank T. Kuroki and Y. Watanabe for donating neisserial clinical isolates. The data from the gonococcal genome sequencing project at the University of Oklahoma [47] and the genome sequence of Neisseria lactamica at the Sanger Institute are gratefully acknowledged. The N. lactamica genome sequence was generated by the Sanger Institute Pathogen Sequencing Unit [48]. This work was supported by grants from the Ministry of Health, Labor and Welfare of Japan and from the Ministry of Education, Culture, Sports, Science and Technology of Japan (Grant no. 13770142 and 16790265).
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Genetics 1998, 150(1):157-171. PubMed Abstract | Publisher Full Text
Loguercio LL, Wilkins TA: Structural analysis of a hmg-coA-reductase pseudogene: insights into evolutionary processes affecting the hmgr gene family in allotetraploid cotton (Gossypium hirsutum L.).
Curr Genet 1998, 34(4):241-249. PubMed Abstract | Publisher Full Text
Mighell AJ, Smith NR, Robinson PA, Markham AF: Vertebrate pseudogenes.
FEBS Lett 2000, 468(2-3):109-114. PubMed Abstract | Publisher Full Text
Lawrence JG, Hendrix RW, Casjens S: Where are the pseudogenes in bacterial genomes?
Trends Microbiol 2001, 9(11):535-540. PubMed Abstract | Publisher Full Text
Hall BG, Yokoyama S, Calhoun DH: Role of cryptic genes in microbial evolution.
Mol Biol Evol 1983, 1(1):109-124. PubMed Abstract | Publisher Full Text
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J Bacteriol 1996, 178(13):3722-3726. PubMed Abstract | Publisher Full Text | PubMed Central Full Text
Al Mamun AA, Tominaga A, Enomoto M: Cloning and characterization of the region III flagellar operons of the four Shigella subgroups: genetic defects that cause loss of flagella of Shigella boydii and Shigella sonnei.
J Bacteriol 1997, 179(14):4493-4500. PubMed Abstract | Publisher Full Text | PubMed Central Full Text
Tominaga A, Mahmoud MA, Mukaihara T, Enomoto M: Molecular characterization of intact, but cryptic, flagellin genes in the genus Shigella.
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Tettelin H, Saunders NJ, Heidelberg J, Jeffries AC, Nelson KE, Eisen JA, Ketchum KA, Hood DW, Peden JF, Dodson RJ, Nelson WC, Gwinn ML, DeBoy R, Peterson JD, Hickey EK, Haft DH, Salzberg SL, White O, Fleischmann RD, Dougherty BA, Mason T, Ciecko A, Parksey DS, Blair E, Cittone H, Clark EB, Cotton MD, Utterback TR, Khouri H, Qin H, Vamathevan J, Gill J, Scarlato V, Masignani V, Pizza M, Grandi G, Sun L, Smith HO, Fraser CM, Moxon ER, Rappuoli R, Venter JC: Complete genome sequence of Neisseria meningitidis serogroup B strain MC58.
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Zhu P, Morelli G, Achtman M: The opcA and ψopcB regions in Neisseria: genes, pseudogenes, deletions, insertion elements and DNA islands.
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Lees-Murdock DJ, McLoughlin GA, McDaid JR, Quinn LM, O'Doherty A, Hiripi L, Hack CJ, Walsh CP: Identification of 11 pseudogenes in the DNA methyltransferase gene family in rodents and humans and implications for the functional loci.
Genomics 2004, 84(1):193-204. PubMed Abstract | Publisher Full Text
Korneev SA, Park JH, O'Shea M: Neuronal expression of neural nitric oxide synthase (nNOS) protein is suppressed by an antisense RNA transcribed from an NOS pseudogene.
J Neurosci 1999, 19(18):7711-7720. PubMed Abstract | Publisher Full Text
Dehio C, Gray-Owen SD, Meyer TF: The role of neisserial Opa proteins in interactions with host cells.
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Nassif X, Pujol C, Morand P, Eugene E: Interactions of pathogenic Neisseria with host cells. Is it possible to assemble the puzzle?
Mol Microbiol 1999, 32(6):1124-1132. PubMed Abstract | Publisher Full Text
Baranov PV, Hammer AW, Zhou J, Gesteland RF, Atkins JF: Transcriptional slippage in bacteria: distribution in sequenced genomes and utilization in IS element gene expression.
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Hart CA, Rogers TR: Meningococcal disease.
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van Deuren M, Brandtzaeg P, van der Meer JW: Update on meningococcal disease with emphasis on pathogenesis and clinical management.
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Takahashi H, Hirose K, Watanabe H: Necessity of meningococcal γ-glutamyl aminopeptidase for the Neisseria meningitidis growth in rat cerebrospinal fluid (CSF) and CSF mimicking medium.
J Bacteriol 2004, 186(1):244-247. PubMed Abstract | Publisher Full Text | PubMed Central Full Text
Takahashi H, Kuroki T, Watanabe Y, Dejsirilert S, Saengsuk L, Yamai S, Watanabe H: Reliability of the detection of meningococcal γ-glutamyl transpeptidase as an identification marker for Neisseria meningitidis.
Microbiol Immunol 2004, 48(6):485-487. PubMed Abstract | Publisher Full Text
Takahashi H, Kuroki T, Watanabe Y, Tanaka H, Inouye H, Yamai S, Watanabe H: Characterization of Neisseria meningitidis isolates collected from 1974 to 2003 in Japan by multilocus sequence typing.
J Med Microbiol 2004, 53:657-662. PubMed Abstract | Publisher Full Text
Takahashi H, Watanabe H: A broad-host-range vector of incompatibility group Q can work as a plasmid vector in Neisseria meningitidis: a new genetical tool.
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phylogenic tree prediction [http://www.genebee.msu.ru/services/phtree_reduced.html] webcite
Huson DH: SplitsTree: analyzing and visualizing evolutionary data.
Bioinformatics 1998, 14(1):68-73. PubMed Abstract | Publisher Full Text
Takahashi H, Inada T, Postma P, Aiba H: CRP down-regulates adenylate cyclase activity by reducing the level of phosphorylated IIA(Glc), the glucose-specific phosphotransferase protein, in Escherichia coli.
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Takahashi H, Tanaka H, Inouye H, Kuroki T, Watanabe Y, Yamai S, Watanabe H: Isolation from a healthy carrier and characterization of a Neisseria meningitidis strain that is deficient in γ-glutamyl aminopeptidase activity.
J Clin Microbiol 2002, 40(8):3035-3037. PubMed Abstract | Publisher Full Text | PubMed Central Full Text


text:
Climate Change Trade Measures:
Considerations for U.S. Policy Makers
GAO-09-724R: Published: Jul 8, 2009. Publicly Released: Jul 8, 2009.
Additional Materials:
- Full Report:
- Accessible Text:
(202) 512-4347
Office of Public Affairs
(202) 512-4800
Global climate change is one of the most significant long-term policy challenges facing the United States, and policies to mitigate climate change will have important economic, social, and environmental implications. Members of Congress have introduced several bills to address the problem of climate change, many of which establish domestic emissions pricing by requiring firms that emit greenhouse gases either to pay a tax or to hold emission allowances. Whichever approach is taken, domestic emissions pricing could produce environmental benefits by encouraging U.S. firms to reduce their emissions of greenhouse gases. But such pricing could also harm U.S. firms' competitiveness, especially in energy-intensive industries where firms compete internationally. Additionally, there could be increased emissions abroad if production were to increase in other countries as a result of increased domestic costs of production resulting from a U.S. climate policy (carbon leakage). To help reduce impacts on U.S. firms and prevent carbon leakage, several climate change bills have also included trade measures or output-based rebates. The bills have included trade measures that would require importers to purchase emission allowances or pay a border tax for the greenhouse gas emissions associated with their imports. They have also designed output-based rebates to financially rebate industries for the costs incurred under a domestic emissions pricing system.
Estimating the potential effects of domestic emissions pricing for industries in the United States is complex. If the United States were to regulate greenhouse gas emissions, production costs could rise for certain industries and could cause output, profits, or employment to fall. Within these industries, some of these adverse effects could arise through an increase in imports, a decrease in exports, or both. Estimates of adverse competitiveness effects are generally larger for industries that are both relatively energy and trade intensive. In 2007, these industries accounted for about 4.5 percent of domestic output. Estimates of the effects vary because of key assumptions required by economic models. For example, models generally assume a price for U.S. carbon emissions, but do not assume a similar price by other nations. In addition, the models generally do not incorporate all policy provisions, such as legislative proposals related to trade measures and rebates that are based on levels of production. Proposed legislation suggests that industries vulnerable to competitiveness effects should be considered differently. Industries for which competitiveness measures would apply are identified on the basis of their energy and trade intensity. Most of the industries that meet these criteria are in primary metals, nonmetallic minerals, paper, and chemicals, although significant variation exists for product groups (sub-industries) within each industry. Additional variation arises on the basis of the type of energy used and the extent to which foreign competitors' greenhouse gas emissions are regulated. To illustrate variability in characteristics that make industries vulnerable to competitiveness effects, we selected example sub-industries within primary metals, non metallic minerals, paper products, and chemicals based on multiple factors. For example, we selected sub-industries that met both the energy and trade intensity criteria, examples that met only one criterion, and examples that met neither, but had significant imports from countries without greenhouse-gas pricing. Trade measures have been proposed to help address potential industry and environmental effects of a domestic emissions pricing system; however, questions exist about their proposed effectiveness. Supporters argue that trade measures may help prevent a decline in output by U.S. producers, prevent carbon leakage, and create leverage for other countries to reduce emissions. Opponents raise concerns that trade measures may motivate retaliatory actions, undermine efforts to secure multilateral consensus, and generate little leverage. In addition, potential implementation challenges may exist. A unilateral U.S. trade measure could have important international implications on U.S. bilateral and multilateral trade relations. For example, other countries could view U.S. trade measures as trade restrictions or sanctions, which could lead them to implement restrictions against U.S. exports. Attention also has focused on the potential for trade measures or output-based rebates to be challenged under World Trade Organization (WTO) rules. Assessing the international trade implications is difficult for a number of reasons. One is that it depends in part upon how other nations reduce their carbon emissions, and whether they perceive any U.S. measures as likely to affect their exports. In addition, the outcome of any WTO challenge, if any, would be uncertain and may depend on how the measure is implemented.
Jun 25, 2015
Combating Terrorism:Foreign Terrorist Organization Designation Process and U.S. Agency Enforcement ActionsGAO-15-629: Published: Jun 25, 2015. Publicly Released: Jun 25, 2015.
Export-Import Bank:Dual-Use Export Monitoring Guidance Revised and ImplementedGAO-15-611: Published: Jun 25, 2015. Publicly Released: Jun 25, 2015.
Jun 17, 2015
Nonproliferation:State Needs to Establish a Reporting Process That Would Minimize the Delays That May Affect Sanctions on Trade with Iran, North Korea, and SyriaGAO-15-703T: Published: Jun 17, 2015. Publicly Released: Jun 17, 2015.
Nonproliferation:State Should Minimize Reporting Delays That May Affect Sanctions on Trade with Iran, North Korea, and SyriaGAO-15-519: Published: May 22, 2015. Publicly Released: Jun 17, 2015.
Jun 8, 2015
Electronic Cigarettes:Imports, Tariffs, and Data CollectionGAO-15-491R: Published: May 7, 2015. Publicly Released: Jun 8, 2015.
Jun 4, 2015
Foreign Aid:USAID Has Taken Steps to Safeguard Government-to-Government Funding but Could Further Strengthen AccountabilityGAO-15-377: Published: Jun 4, 2015. Publicly Released: Jun 4, 2015.
Jun 3, 2015
Haiti Reconstruction:USAID Has Achieved Mixed Results and Should Enhance Sustainability PlanningGAO-15-517: Published: Jun 3, 2015. Publicly Released: Jun 3, 2015.
May 19, 2015
Afghanistan:Embassy Construction Cost and Schedule Have Increased, and Further Facilities Planning Is NeededGAO-15-410: Published: May 19, 2015. Publicly Released: May 19, 2015.
May 14, 2015
United Nations Renovations:Original Scope Reduced and Project Over Budget, but Lessons Learned Could Improve Future ProjectsGAO-15-414: Published: May 14, 2015. Publicly Released: May 14, 2015.
International Education Assistance:USAID Has Implemented Primary Grade Reading Programs but Has Not Yet Measured Progress toward Its Strategic GoalGAO-15-479: Published: May 7, 2015. Publicly Released: May 14, 2015.
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C# 2.0Elsevier Science 2005; US$ 31.95
You don?t need coddling; you don?t need to be told what you already know. What you need is a book that uses your experience as a Java or C++ programmer to give you a leg up into the challenges and rewards of C#. And this Practical Guide is precisely what you?re after. Written by a team that boasts extensive experience teaching C# to professionals,... more...
Microsoft Visual C# .NET 2003 UnleashedPearson Education 2004; US$ 47.99
Microsoft Visual C# .NET 2003 Unleashed is a comprehensive reference and learning guide for the .NET Framework, using C# as the instructional language. You will be exposed to everything from low-level information on the Garbage Collector to advanced concepts like creating applications that use Enterprise Services, creating Web Services and even advanced... more...
C# 2005 For DummiesWiley 2005; US$ 19.99
C# is Microsoft's object-oriented programming language designed for improving productivity in the development of Web applications Fully revised for C# 2005, this book begins with creating a C# program, then moves into C# and object-oriented programming fundamentals, Windows programming with C# and Visual Studio, and debugging and error handling... more...
Sams Teach Yourself Visual C# 2005 in 24 Hours, Complete Starter KitPearson Education 2007; US$ 31.99
This is the eBook version of the printed book. If the print book includes a CD-ROM, this content is not included within the eBook version. Looking to break into C# programming? Sams Teach Yourself Visual C# 2005 in 24 Hours, Complete Starter Kit is a valuable resource. You will start by learning the basics of the Visual C# environment and begin... more...
Microsoft Visual C# 2005 UnleashedPearson Education 2006; US$ 47.99
Setting the standard for a premium C# reference, Microsoft Visual C# 2005 Unleashed provides practical examples for virtually every aspect of the C# programming language. The book is structured for progressive learning, so it can be read cover-to-cover or used as a comprehensive reference guide. You will be exposed to everything from low-level information... more...
Mastering Visual C# .NETWiley 2006; US$ 49.99
Get Everything You Can Out of Visual C# and the .NET Framework Mastering Visual C# .NET is the best resource for getting everything you can out of the new C# language and the .NET Framework. You'll master C# language essentials, quickly taking advantage of the many improvements it offers over C++ and see tons of examples that show you all the ways... more...
C# Network ProgrammingWiley 2006; US$ 71.95
On its own, C# simplifies network programming. Combine it with the precise instruction found in C# Network Programming, and you'll find that building network applications is easier and quicker than ever. This book helps newcomers get started with a look at the basics of network programming as they relate to C#, including the language's network classes,... more...
Professional C# 2005 with .NET 3.0Wiley 2007; US$ 59.99
Preparing readers to program in C#, this authoritative guide provides the necessary background information on how the .NET architecture works Begins with a tutorial on C# 2005 and the .NET 3.0 Framework, then moves through the vast .NET class library, showing how C# can be used to solve various tasks Includes coverage of the new .NET 3.0 Framework,... more...
Beginning Visual C# 2005 Express EditionApress 2006; US$ 20.99
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text:
Rated 5 out of 5 stars
love it. the only problem is when i type a keyword or some chinese characters (no space between each), firefox would try to resolve this word first (and ofcourse will fail), then use default search engine to search it. the first procedure won't happen in omnibar, please fix it, or it will take several seconds longer each time.This review is for a previous version of the add-on (18.104.22.168-signed).


text:
The color is not as depicted on the website. It is more blue-grey. Otherwise with a nice sheen and smoothness.
Using this as a living room rug. It really helps complete the room against my dark wood floors. Also, I have a dog that sheds a lot and was looking for a flatter rug where fur wouldn't get stuck in the fibers. This works perfectly and I've received many compliments on it!
I love this rug, but keep in mind that this rug is dark grey and the pattern color is definitely beige - not ivory or white. I think this is why I love it on my porch. My cushions on my porch furniture are beige in color and so it's a nice complement with the rug. If you want a rug that is lighter grey with an ivory or white pattern, this is NOT the rug for you, sadly. Some of the product pictures do make it look lighter in color than it actually is, so I thought I'd warn you. I felt that the shipping was fast and the rug was well-wrapped upon arrival so there was no damage. Also, it was a great price for a durable, outdoor rug. Thanks!
Love this rug! So beautiful. However it is not 8'x11'2" it is actually 9'x12'6" Just more bang for your buck!! Highly recommend!
- How did the color on site compare with the actual product? perfect
- Please tell us about the quality of the product. great
- How accurate was the on site description of the product? larger in person
Love this rug. The colors are perfect for my patio -great buy!
Much darker grey than the picture but still a very nice rug.
this rug is nice, somewhat thin, looks exactly like picture.
Bought 2 of this rug for outdoor porches at our beach house. Great rug for the price. Color as described, just note it is a creamy/beige not white with the gray.Perfect for the rain and sand. just rinse off as needed.
This rug looks nice, however I bought it for my dining room and it is more of an outdoor rug considering it's not that thick, not comfortable and it's very thin. Still looks nice but It would be best outside or over carpet, mine is over wood flooring.
like everyone has said, the actual rug color is way darker grey than pictured but since I had read the reviews, I was expecting that. Rug arrived in 3 days after ordering and Im extremely happy with it. Just what we wanted, durable (lets see if it stands up to cats scratching it though). Looks great on our hardwood floors, very "Zen" which is great as we are calling our newly repainted room the Zen/Mediation room. Great for the price!
I wasn't sure if I would like the texture for a living room rug- turns out I love it!
Nice rug, color a bit darker than expected will work indoors or out
The quality, etc of the rug was excellent but I went by the monitor's color instead of the description. My monitor usually does excellent and I believe the picture of the rug could have been better to prevent the cost of the return (which was les than I expected. customer service was fabulous!
Dark blue with a rubbery texture. Very industrial auto shop floor looking. That darkish dirty grey. Going back
I bought this rug to put into my dining room under the dining room table. It is a nice dark grey and is easy to clean. I like it!
This rug is fantastic! its beautiful and stay true to the color showing! I LOVED IT !
Rather plasticky, but does the trick I guess. I definitely won't be using it where initially intended
This is the second Safavieh indoor outdoor rug I have purchased. Love them. One is in my sunroom. If the dog tracks in dirt it is so easy to clean up. This one is on my front porch. Looks great.
I love this rug but I don't love that it was not anywhere near 8x11'2 as advertised hence the lack of 2 additional stars.
Better than expected, the color, texture,and size was exactly what what ever were looking for. We believe that Overstock just gained some new customers.


text:
Selected Community Events
Jackson Symphony Orchestra's Summer Pops - Beer Brats & Beethoven III
Riverwalk Amphitheater Downtown Jackson
The JSO Summer Pops concert entitled "Beer, Brats & Beethoven III" marks the third year for this festive outdoor concert which will be held once again at the Riverwalk Amphitheater in downtown Jackson. The event is scheduled for Saturday, July 11 at 7:30 p.m. and will feature members of the Jackson Symphony Orchestra, directed by JSO Associate Conductor David Schultz. The concert will also feature special guest singer and Jackson native Chip Mezo offering up several Broadway standards and modern favorites.
Jackson Symphony Orchestra, 517-782-3221, firstname.lastname@example.com
Free Concert in the Parks Series
Moores Park, Quentin Park, Durant Park, Riverfront Park, Ferris Park, Schmidt Center, St. Joe Park, Turner Dodge House
2015 Summer Concerts In The Park Schedule:
6/10 - The Lansing Unionized Vaudeville Spectacle - Moores Park
6/17 - The Joe Wright Experience (Country) - Quentin Park
6/24 - Straight Ahead (Jazz) - Durant Park
**7/4 - FRIDAY EVENING - 8:00PM - Lansing Concert Band - Riverfront Park
7/15 - Taylor Taylor (Pop) - Ferris Park
7/22 - Tejano Sound - Schmidt Center
7/29 - Big Willy (Blues) - St. Joe Park
8/5 - Sea Cruiser (Oldies) - Turner Dodge House
Concert attendees should bring lawn chairs or blankets. In case of rain or other inclement weather, concerts will take place at the same time and location on the following day.
For directions to the Park or for more information, please call 517-483-4277
Royal Heirs Southern Gospel Group to Perform
Crossroads UMC, corner of Haslet and Zimmer Roads, Williamston
An evening of soul-stirring music is offered to the public with Southern style gospel of the Royal Heirs.
517-655-1466 or www.crossroadsofwilliamston.org


text:
A collection of news and information related to Seth Rogen published by this site and its partners.
Top Seth Rogen Articles
Displaying items 34-44
Friday's TV Highlights: 'Great Performances' on PBSStory | Nov 20, 2014 | 8:00 PMCustomized TV Listings are available here: www.latimes.com/tvtimes Click here to download TV listings for the week of Nov. 16 - 22, 2014 in PDF format This week's TV Movies -------------------- SERIES Whose Line Is It Anyway? The improv-...
Natalie Portman may link up with Steve Jobs biopic
Four ways Bob Hope conquered the entertainment world
A sneak peek at new movies during the holidays
Christian Bale Drops Out of Steve Jobs BiopicStory | Nov 3, 2014 | 2:30 PMAfter early discussions to play the Apple founder, Christian Bale has decided to part ways with the Steve Jobs biopic at Sony. While negotiations were never fully under way, sources tell Variety that Bale had talks with director Danny Boyle about...
Sony Pictures returning to normal after crippling computer attack
Sony movies leak online as computer systems remain dark
Lisa Kudrow and 'The Comeback' clock in again at dream factory
North Korea surfaces in Sony investigators' probe into hackStory | Dec 4, 2014Cyber investigators looking for the culprits of a devastating hack into Sony Pictures Entertainment have found some links to North Korea — hacking tools similar to those used by that country in previous attacks on South Korea. A person familiar...
Seth Rogen and Evan Goldberg like that Kim Jong Un doesn't get the joke
'Preacher' adaptation gets pilot order at AMC


text:
A processor includes first and second execution cores that operate in a redundant (FRC) mode, an FRC check unit to compare results from the first and second execution cores, and an error check unit to detect recoverable errors in the first and second cores. The error detector disables the FRC checker, responsive to detection of a recoverable error. A multi-mode embodiment of the processor implements a multi-core mode in addition to the FRC mode. An arbitration unit regulates access to resources shared by the first and second execution cores in multi-core mode. The FRC checker is located proximate to the arbitration unit in the multi-mode embodiment.
1. A processor comprising:
first and second execution cores to operate in an FRC mode, wherein the first and second execution cores may also operate in a multi-core mode;
a resource to process a transaction from at least one of the first and second execution cores;
an interface control unit to regulate access to the resource by the first and second execution cores, the interface control unit including,
an FRC check unit to compare transaction signals from the first and second execution cores and to signal an error if the comparison indicates a mismatch, and
an arbitration unit to regulate access to the resource by the execution cores if they operate in multi-core mode; and
an error detector to detect an error in the first and second execution cores respectively and to disable the FRC check unit responsive to detecting an error.
2. The processor of
3. The processor of
4. The processor of
5. The processor of
6. The processor of
7. The processor of
8. The processor of
9. A system comprising:
a first memory location to store a recovery routine;
a second memory location to store a reset routine;
first and second execution cores capable of operating in an FRC mode;
an error unit to initiate the recovery routine responsive to detecting an error in one of the first and second execution cores, wherein the error unit disables the FRC checker, responsive to detecting the error in one of the first and second execution cores; and
an FRC checker to initiate the reset routine responsive to detecting a mismatch between signals from the first and second execution cores, wherein the reset routine includes instructions executable by the first and second execution cores to initialize the first and second execution cores in either a multi-core mode or the FRC model;
a cache to be shared by the first and second execution cores if the first and second execution cores are initialized in multi-core mode; and
an arbitration unit to manage access to the cache by the first and second execution cores in multi-core mode.
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1. Technical Field
The present invention relates to microprocessors and, in particular, to mechanisms for handling errors in FRC-enabled processors.
2. Background Art
Servers and other high-end computing and communication systems are designed to provide high levels of reliability and availability. Soft errors pose a major challenge to both of these properties. Soft errors result from collisions between high-energy particles, e.g. alpha particles, and charge storing nodes. They are prevalent in storage arrays, such as caches, TLBs, and the like, which include large numbers of charge storing nodes. They also occur in random state elements and logic. Rates of occurrence of soft errors (soft error rates or SERs) will likely increase as device geometry decreases and device densities increase.
Highly reliable systems include safeguards to detect and manage soft errors, before they lead to silent, e.g. undetected, data corruption (SDC). However, to the extent error detection/handling mechanisms that support high-reliability operations take a system away from its normal operations, the system's availability is reduced. For example, one such mechanism resets the system to its last known valid state if an error is detected. The system is unavailable to carry out its assigned task while it is engaged in the reset operation.
One well-known mechanism for detecting soft errors is functional redundancy checking (FRC). A single processor enabled for FRC may include replicated instruction execution cores on which the same instruction code is run. Depending on the particular embodiment, each replicated execution core may include one or more caches, register files and supporting resources in addition to the basic execution units (integer, floating point, load store, etc.). FRC-hardware compares results generated by each core, and if a discrepancy is detected, the FRC system passes control to an error-handling routine. The point(s) at which results from different execution cores are compared represents the FRC-boundary for the system. Errors that are not detected at the FRC boundary can lead to SDC.
Since FRC errors indicate only that the execution cores disagree on a result, FRC errors are detectable but not recoverable. As noted above, the FRC error handling routine typically resets the system to the last known point of reliable data. This reset mechanism is relatively time consuming. It takes the system away from its normal operations, reducing system availability.
FRC is only one mechanism for handling soft errors, and for random logic and random state elements, it is the primary mechanism. Array structures present a different picture. Array structures typically include parity and/or ECC hardware, which detect soft errors by examining properties of the data. In many cases, the system can correct errors created by data corruption using relatively fast hardware or software mechanisms. However, for FRC-enabled processors, such errors are likely to be manifested as FRC errors, since they take the execution cores out of lock-step. Handling these otherwise recoverable errors through a reset mechanism reduces system availability.
The present invention addresses mechanisms for combining recoverable and non-recoverable error handling mechanisms efficiently in FRC-enabled processors.
The present invention may be understood with reference to the following drawings, in which like elements are indicated by like numbers. These drawings are provided to illustrate selected embodiments of the present invention and are not intended to limit the scope of the invention.
The following discussion sets forth numerous specific details to provide a thorough understanding of the invention. However, those of ordinary skill in the art, having the benefit of this disclosure, will appreciate that the invention may be practiced without these specific details. In addition, various well-known methods, procedures, components, and circuits have not been described in detail in order to focus attention on the features of the present invention. For example, aspects of the present invention are illustrated using a dual-core processor, but persons skilled in the art will recognize that more than two cores may be used with appropriate modifications of the reset and recovery mechanisms.
Each execution core 120 includes a data pipeline 124 and an error pipeline 128 that feed into FRC checker 130 and error detector 140, respectively. Data pipeline 124 represents the logic that operates on various types of data as it moves through processor 110 toward FRC checker 130. Data processed by data pipeline 124 may include result operands, status flags, addresses, instructions and the like that are generated and staged through processor 110 during code execution. Error pipeline 128 represents the logic that operates on various types of data to detect errors in the data and provide appropriate signals to error detector 140. For example, the signals may be one or more bits (flags) representing the parity or ECC status of data retrieved from various storage arrays (not shown) of processor 110. Soft errors in these arrays may appear as parity or ECC error flags when the corrupted data is accessed.
If an error reaches error detector 140 from either core 120, recovery module 150 is activated to implement a recovery routine. Recovery can be implemented with relatively low latency by hardware, software, firmware or some combination of these. For example, there is an extremely small probability that data is corrupted in both execution cores 120 at the same (or nearly the same) time. This leaves an uncorrupted copy of the data available to restore data integrity to processor 110. However, an FRC error will be triggered if the corrupted data from one execution core and an uncorrupted version of the data from the other execution are allowed to reach FRC checker 130 before recovery module 150 is activated. Since FRC errors are not recoverable, reset module 160 resets the system, if FRC checker 130 signals an FRC error before the underlying parity/ECC error is detected.
Not all FRC-errors are traceable to underlying parity/ECC or other correctible soft errors. For those that are, it is faster for error detector 140 to address the underlying soft error than for FRC-checker to address the FRC error that results when the corrupted data reaches FRC boundary 104. As noted above, the reset process has a significantly longer latency than the recovery process, and it is to be avoided if the error can be corrected by recovery module 150. In addition, reset usually brings the entire system down, whereas recovery only results in a temporary performance loss. For this reason, FRC checker 130 is temporarily disabled if error detector 140 detects an error in either error pipeline 128, since execution cores 120 are no longer in lock step.
Execution cores 120 operate in lock step during normal FRC mode, but data pipeline 124 and error pipeline 128 may operate relatively independently. For example, ECC hardware is relatively complex and, consequently, relatively slow, especially for 2-bit errors. A flag signaling such an error may reach error detector 140 before, after, at the same time as the data with which it is associated reaches FRC checker 130. This flexibility is generally beneficial. For example, it allows data to be used speculatively before its error status is determined. Since soft errors are relatively rare, and error pipeline 128 is generally as fast as data pipeline 124, this flexibility is net positive. As long as the error flag arrives at error detector 140 in time to disable FRC checker 130 before it acts on a mismatch attributable to the corrupted data, the relatively low latency recovery routine is engaged.
As discussed below, processor 110 may implement strategies to mitigate the race between recoverable and non-recoverable error mechanisms. For example, a streamlined signaling mechanism may be used in FRC mode to speed disabling of FRC checker 130 in the event of a non-FRC error. In addition, FRC errors may be delayed for an interval prior to reset, in case a late arriving recoverable error signal obviates the need for reset.
For one embodiment of the invention, processor 110 is capable of operating in a high reliability (e.g. FRC) mode or a high performance (e.g. multi-core) mode. The operating mode may be selected, for example, when a computing system that includes processor 110 is booted or reset. In FRC mode, execution cores 120(a) and 120(b) may appear to the operating system as a single logical processor. Execution cores 120(a) and 120(b) process the same code sequence, and the results generated are compared by FRC checker 130. If the results agree, a machine state corresponding to the code sequence is updated.
In FRC mode, one of execution cores 120 may be designated as the master. The master refers to the execution core that is responsible for updating the resources shared by execution cores 120. The other execution core 120 may be designated as the slave. The slave is responsible for generating results from the same code sequence to be checked against those of the master. Since an error may occur in either the master or slave, embodiments of the present invention allow the master/slave designation to be changed dynamically. As discussed below, this allows the slave to take over the master designation to implement recovery if a recoverable error is detected in the execution core that is currently designated as master.
In multi-core mode, execution cores 120(a) and 120(b) may appear to the operating system as two different logical processors on a single processor die. In this mode, execution cores 120(a) and 120(b) process different code sequences, and each updates a machine state associated with the code sequence it processes. Portions of the machine state of a logical processor may be stored in a cache and/or register associated with the corresponding execution core. At some point(s) on the processor die, results from execution cores 120(a) and 120(b) are routed to shared resource(s) 170 for, e.g., storage (cache) or transmission off of the processor die (bus). For this embodiment, additional logic is provided to mediate access to shared resources 170 by execution cores 120(a) and 120(b). In general, multi-core mode allows the execution cores of the processor to be controlled separately.
Expansion of the FRC boundary in this manner naturally increases the time necessary to propagate signals to FRC checker 130. This increased "flight time" provides more time for a parity or ECC error to reach detector 140, which increases the opportunity for error recovery. As noted above, the recovery routine triggered by error detector 140 provides greater system availability than the reset routine triggered by FRC checker 130. Expanding the FRC boundary thus increases both the amount of logic that is duplicated for execution cores 120 and the flight time, during which detectable errors may be identified. The former increases FRC protection, albeit through a reset mechanism. The latter increases the likelihood that errors identifiable through parity, ECC or similar core-specific protections are handled through recovery rather than reset.
Processor 310 includes first and second execution cores 320(a) and 320(b), respectively (generically, execution cores 320). Each execution core includes execution resources 324 and a bus cluster 328. Execution resources 324 may include, for example, one or more integer, floating point, load/store, and branch execution units, as well as register files and cache(s) to supply them with data (e.g. instructions, operands, addresses). Bus cluster 328 represents logic for managing transactions to a cache 340 that is shared by execution cores 320(a) and 320(b), as well as to a front side bus 360, for those transactions that may miss in shared cache 340. Resources corresponding to the error pipeline of
Interface units (IFU) 330(a), 330(b) (generically, IFU 330) represent a boundary between execution cores 320 and shared resources, cache 340 and FSB 360. The disclosed embodiment of IFU 330 includes an FRC unit 332 and an arbitration unit 334. As noted above, FRC unit 332 and arbitration unit 334 receive signals from execution cores 320, and locating them proximate to each other results in significant savings of wiring on the processor die. Also shown in
For FRC mode, FRC unit 332 compares signals from execution cores 320 for transactions to shared resources like cache 340 and FSB 360. FRC unit 332 thus forms part of the FRC boundary of processor 310. For multi-core mode, arbitration unit 334 monitors signals from execution cores 320 and grants access to its associated shared resource according to an arbitration algorithm. The arbitration algorithm implemented by arbitration unit 334 may be, for example, a round robin scheme, a priority-based scheme or similar arbitration algorithms. For both FRC and multi-core mode, error unit 336 may monitor signals from execution cores 320 for recoverable errors.
Portions of recovery module 150 and reset module 160 (
The disclosed embodiment of system 300 also includes interrupt controllers 370(a) and 370(b) (generically, interrupt controller(s) 370) to process interrupts for execution cores 320(a) and 320(b), respectively. Each interrupt controller 370 is shown having first and second components 374 and 378, respectively, to accommodate the different clock domains in which interrupt controller 370 may operate. For example, FSB 360 typically operates at a different frequency than processor 310. Consequently, components of processor 310 that interact directly with FSB 360 typically operate in its clock domain, which is indicated as area 364 on processor 310.
The disclosed embodiment of interrupt controller 370 also includes an FRC-boundary-like component in the form of XOR 372. XOR 372 signals an FRC error if it detects a mismatch between outgoing signals, e.g. interrupt responses, of components 374(a) and 374(b) from execution cores 320(a) and 320(b). Errors attributable to interrupt controllers 370 may still arise, however, from soft errors in components 378(a), 378(b) in FSB clock domain 364. These error may be detected by the discrepancies they introduce between the subsequent operations of execution cores 320(a) and 320(b).
For the disclosed embodiment of system 300, a common snoop block 362 processes snoop transactions to and from execution cores 320(a) and 320(b). XOR 366 provides FRC-checking on snoop responses from execution cores 320(a), 320(b) and signals an error if a mismatch is detected. XORs 372 and 366 may be disabled if processor 310 is operating in multi-core mode.
If the error signal does not disable FRC unit 332 the corrupted data triggers an FRC error, and an otherwise recoverable error is treated as a non-recoverable, e.g. FRC, error. That is, the system goes through a reset operation rather than a shorter recovery operation. Depending on the particular implementation of the system, there may be a number of cases in which the race to FRC unit 332 between the error signal and the mismatched data signals from the execution cores (created by the recoverable error) is close. For this reason, apparatus 344 may include a mechanism to accelerate error signal propagation, at least in FRC mode.
For one embodiment, apparatus 334 supports a high level interrupt such as an MCA that operates in both FRC and high performance modes. In high performance mode, the error signal is subject to pipeline stalls, e.g., in the front end of the execution core or in the L2 cache. This ensures that no unnecessary MCAs are taken, since the event that triggered the stall may make the error signal moot. In FRC mode, the error signal bypasses these stalls. Bypassing stalls in FRC may result in the processing of some unnecessary error signals, but it also reduces the probability that an FRC error is triggered before the (non-FRC) error signal disables FRC unit 332. As discussed in conjunction with
A pair of write-line buffers (WLB) 430(a), 430(b) stage data from execution cores 320(a), 320(b), respectively, to cache 340 or FSB 360, and a pair of read-line buffers 440(a), 440(b) stage data from FSB 360 to cache 340 or execution cores 320. Coalescing buffers (CB) 450(a), 450(b) collect data to be written to memory 380 and forward it to FSB 360, periodically. For example, multiple data writes to the same line of memory may be collected in CBs 450 before triggering a write transaction on FSB 360.
For the disclosed embodiment, logic associated with these buffers provides the FRC-checking and data routing functions when processor 310 is operated in FRC mode. For example, logic block 454 represents MUX and XOR functions for data in CBs 450(a), 450(b). The XOR function provides FRC checking if processor 310 is operating in FRC mode. The MUX function provides data routing if processor is operating in multi-core mode. Logic blocks 434 and 444 provide similar functions for data in WLBs 430(a), 430(b) and RLBs 440(a), 440(b), respectively. MUXs 460, 470 and 480 route data from different sources to cache 340, FSB 360 and execution cores 320.
As noted above, the recovery mechanism for errors detected within the FRC boundary may be handled by various combinations of hardware, software and firmware modules. One embodiment of the recovery mechanism employs code that is closely associated with the processor. For example, the Itanium� Processor Family of Intel� Corporation, employs a layer of firmware called the processor abstraction layer (PAL), which provides an abstraction of the processor to the rest of the computing system. Implementing recovery in the PAL hides the recovery process from system level code, such as the system abstraction layer (SAL), e.g. BIOS, and the operating system. PAL-based implementations of the recovery mechanism should be able to complete quickly enough to avoid triggering a time-out period enforced by the operating system. Recovery mechanisms may also be implemented using system level code, e.g. SAL/BIOS, or operating system code. The latter implementations may not be subject to the same time constraints as the PAL-based implementation. Unless otherwise noted, the recovery mechanisms discussed below may be implemented using code associated with any of the foregoing sources.
For one embodiment of the invention, one of execution cores 120 may be designated as the master core and the other as the slave core when processor 10 is operating in FRC mode. For this embodiment, signals generated by the master and slave cores are compared at the FRC boundary to determine if reset is necessary. If no FRC reset is warranted, signals generated by the master core are transferred to shared resource(s) 170, and signals generated by the slave core are dropped. For this embodiment, a bit in a status register of each execution core 120 may be used to indicate its status as master or slave. The bit may be set, for example, when the system is booted or reset. As discussed below in greater detail, the master/slave status of an execution may also be changed dynamically to allow recovery for an error in either core. For errors detected within the FRC boundary, e.g. recoverable errors, the actions of the master and slave core may differ, depending on which core generated the error.
Routine 600 is initiated if the slave execution core detects 610 an error (parity, ECC, etc.). The slave core triggers 620 an interrupt to signal the error condition to other components of the computing system. For embodiments of routine 600 implemented by PAL or comparable processor-level code, broadcast of the interrupt signal may be limited to components within the processor chip, such as the master execution core. In addition to signaling the error, the slave execution core disables 630 the FRC unit and suspends its activities. Disabling the FRC unit prevents the error from triggering an FRC reset when it reaches the FRC boundary, and suspending activities in the slave core prevents it from disrupting the recovery process.
In response 624 to the interrupt, the master execution core determines 640 whether its state data contains any errors. For example, each execution core may include a status bit that is set if an error is detected. The master execution core may check this bit to determine if it has also generated an error. Except for the very rare case in which soft errors occur in both execution cores almost simultaneously, the master core is likely to be clean. If it is not clean 640, there is no uncorrupted processor state with which to implement a recovery. In this case, the master core signals 642 a reset condition to the slave core and the computing system executes 644 a full, e.g. FRC-level, reset.
If the state data for the master core is not corrupted, the master core saves 660 its machine state and flushes 664 queues and buffers in its pipeline. For example, the master core may save the contents of its data and control registers and low-level cache(s) to a protected area of memory. The master core also signals 668 a limited reset to the slave core and sets 676 it resources to a specified state, e.g. initializes its pipeline. The slave core detects 670 the limited reset and initializes 674 its pipeline, synchronizing the states of the cores.
With the cores thus synchronized, FRC mode is reactivated 680. This may be accomplished, for example, by having each core execute a handler routine, which sets appropriate state bits in its status/control registers. The saved state is restored 684 to both execution cores, and control is returned 690 to the interrupted code sequence.
Method 600 represents an embodiment of the recovery mechanism for the case in which the error is detected in the execution core that is currently designated as the slave core. For one embodiment, the slave core is the execution core that does not "control" the shared resource(s). For example, in FRC mode, signals from the slave execution core are dropped following comparison with those from the master execution core at the FRC boundary. If no FRC error is detected, signals from the master core are used to control the shared resources outside the FRC boundary.
If the error originates in the master core rather than the slave core, recovery may be handled by changing the master/slave designations of the execution cores. For example, master/slave designation may be indicated by the state of a bit in a status register associated with each execution core. The execution core for which this status bit is in the master state controls the shared resources, which are used to implement the state-saving operations of recovery routine 600, e.g. operation 660.
For one embodiment of the recovery routine, the execution core in which the error originates may check its master/slave status bit. If the status bit indicates it is the slave, method 600 may be implemented as described. If the status bit indicates it is the master, it may signal the slave to change its status to master, change its own status to slave, and suspend activities.
If the data does not match, the status flag is set to indicate the mismatch and timer unit 738 is triggered to begin a countdown interval. If error detector 140 receives an error flag before the timeout interval expires, it disables FRC checker 730 and triggers recovery unit 150 to implement the recovery routine.
There has thus been disclosed a mechanism for handling recoverable and non-recoverable errors in multi-core processor. The multiple cores may be operated in FRC mode, in which case, one or more checker units compare signals from the cores to detect non-recoverable errors. In addition, each core includes an error unit to detect recoverable errors. If a recoverable error is detected, the checker units are disabled and a recovery routine is implemented. A multi-core mode embodiment of the multi-core processor may include an arbitration unit, proximate to the checker, to control access to the shared resource(s). Proximity of the FRC boundary to the shared resources increases the logic protected by the FRC boundary and reduces wiring necessary for the multi-core mode implementation.
Embodiments of the present invention detect virtually all errors that are undetected in non-FRC-enabled systems, and they support recovery of virtually all detectable errors, including those that are typically handled through reset in other FRC-enabled processors.
The disclosed embodiments have been provided to illustrate various features of the present invention. Persons skilled in the art of processor design, having the benefit of this disclosure, will recognize variations and modifications of the disclosed embodiments, which none the less fall within the spirit and scope of the appended claims.
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text:
The Bulls continue to battle their way back against Philadelphia
- Updated: May 10, 2012
NBA Playoffs Betting Previews- No.1 Chicago Bulls vs. No.8 Philadelphia 76ers
Pointspread: Philadelphia -1.5
Total Line: 174
The Chicago Bulls head to the Wells Fargo Center this Thursday night with the intention of extending their first-round playoff series against the upstart Philadelphia 76ers to deciding Game 7 in this Eastern Conference matchup. This Game 6 clash is set to tip-off at 7 p.m. (ET) and it will be broadcast nationally on TNT.
First, Derrick Rose went down with a season ending knee injury in Game 1. Next, Chicago proceeded to drop three-straight games to the eighth-seeded 76ers to dig a 3-1 hole in this series, while losing another starter, Joakim Noah with an ankle injury. Despite all the adversity, a Bulls' team that won 50 of 66 games in the regular season is now just one more victory away from regaining complete control of this series.
Defense along with a much better effort from Luol Deng and Carlos Boozer led to Chicago's 77-69 victory in Tuesday's Game 5 as a five-point home favorite. It will now have to recreate that effort on the road, where it is 1-4 both straight-up and against the spread in its last five trips to Philadelphia.
The 76ers have been over-achievers all season long, but are dangerously close to an epic collapse in a series it had all but won. The cracks in Cinderella's carriage are starting to widen with a 40.9 shooting percentage from the field and a woeful 21.5 percent shooting performance from three-point range. Things really got ugly on Tuesday night after the Sixers put-up a franchise-low 26 points in the first half. They finished the night shooting just 32.1 percent from the floor and 18.2 percent from beyond the arc.
In a lineup that lacks any true star power, players such as Andre Iguodala and Lou Williams are going to have to come up big for Philadelphia to have any chance to close this series out on Thursday night. Another key will be a much better shooting performance from Jrue Holiday. He led the team in Game 5 with 16 points but went just 5-for-17 from the floor.
Betting Trends
The Bulls are 6-1 ATS in their last seven games on one day's rest but just 2-6 ATS in their last eight games on the road. The total has stayed 'under' in their last five road games.
The 76ers are 3-7 ATS in their last 10 games following a SU loss and 2-5 ATS in their last seven home games. The total has stayed 'under' in five of their last six games at home.
The home team has covered ATS in five of the last six meetings and the favorite is 6-1 ATS in the last seven. The total has stayed 'under' in the last three games of this series but has gone 'over' in seven of the last 11 meetings in Philadelphia.
Even with the loss of Rose and Noah day-to-day for this game, the Bulls know that one more win takes this series back to Chicago. The clock is about to strike midnight for Philly as the reality it is an eighth- seed playing a one-seed begins to set in. Chicago 82 Philadelphia 77
Dave Schwab
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