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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   

5.
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 (%)c
A1/A2 divergence <1%A1-23645630020.4410.44
A1-0456544000040.61
A2-568413220.4820.4800.24
A2-411480210.210010.31
A1/A2 divergence >1%A1-2176679000091.35
A1-12856990010.1881.49
A1-199618130010.16122.02
A2-4223449000092.62
A2-516470140000142.98
A2-404508200030.59173.64
A2-4355062220.3920.39183.95
A2-4734572310.2210.22214.81
A2-4573031710.3300165.54
A2-5755034750.9930.59398.55
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   

6.
Promotion of Mn(II) Oxidation and Remediation of Coal Mine Drainage in Passive Treatment Systems by Diverse Fungal and Bacterial Communities     
Cara M. Santelli  Donald H. Pfister  Dana Lazarus  Lu Sun  William D. Burgos  Colleen M. Hansel 《Applied and environmental microbiology》2010,76(14):4871-4875
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7.
Dominant Bacteria and Biomass in the Kuytun 51 Glacier     
Shu-Rong Xiang  Tian-Cui Shang  Yong Chen  Ze-Fan Jing  Tandong Yao 《Applied and environmental microbiology》2009,75(22):7287-7290
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8.
Dehalogenation Activities and Distribution of Reductive Dehalogenase Homologous Genes in Marine Subsurface Sediments     
Taiki Futagami  Yuki Morono  Takeshi Terada  Anna H. Kaksonen  Fumio Inagaki 《Applied and environmental microbiology》2009,75(21):6905-6909
Halogenated organic compounds serve as terminal electron acceptors for anaerobic respiration in a diverse range of microorganisms. Here, we report on the widespread distribution and diversity of reductive dehalogenase homologous (rdhA) genes in marine subsurface sediments. A total of 32 putative rdhA phylotypes were detected in sediments from the southeast Pacific off Peru, the eastern equatorial Pacific, the Juan de Fuca Ridge flank off Oregon, and the northwest Pacific off Japan, collected at a maximum depth of 358 m below the seafloor. In addition, significant dehalogenation activity involving 2,4,6-tribromophenol and trichloroethene was observed in sediment slurry from the Nankai Trough Forearc Basin. These results suggest that dehalorespiration is an important energy-yielding pathway in the subseafloor microbial ecosystem.Scientific ocean drilling explorations have revealed that marine subsurface sediments harbor remarkable numbers of microbial cells that account for approximately 1/10 to 1/3 of all living biota on Earth (20, 25, 33). Thermodynamic calculations of pore-water chemistry suggest that subseafloor microbial activities are generally supported by nutrient and energy supplies from the seawater and/or underlying basaltic aquifers (6, 7). Although sulfate, nitrate, Fe(III), Mn(IV), and bicarbonate are known to be potential electron acceptors for anaerobic microbial respiration in marine subsurface sediments (5), the incidence of both the dissimilatory dehalorespiration pathway and microbial activity in halogenated organic substrates remains largely unknown.Previous molecular ecological studies using 16S rRNA gene sequences demonstrated that Chloroflexi is one of the most frequently detected phyla in subseafloor sediments of the Pacific Ocean margins (12-14). Some of the sequences within the Chloroflexi are closely related to sequences in the genus Dehalococcoides, which contains obligatory dehalorespiring bacteria that employ halogenated organic compounds as terminal electron acceptors (21, 29). The frequent detection of Dehalococcoides-related 16S rRNA genes from these environments implies the occurrence of dissimilatory dehalorespiration in marine subsurface sediments.In this study, we detected and phylogenetically analyzed the reductive dehalogenase homologous (rdhA) genes, key functional genes for dehalorespiration pathways, from frozen sediment core samples obtained by Ocean Drilling Program (ODP) Leg 201 (Peru margin and eastern equatorial Pacific) (7, 14); Integrated Ocean Drilling Program (IODP) Expedition 301 (Juan de Fuca Ridge flank) (8, 24); Chikyu Shakedown Expedition CK06-06 (Northwest Pacific off Japan) (20, 23); and IODP Expedition 315 (Nankai Trough Forearc Basin off Japan) (Table (Table1).1). DNA was extracted using an ISOIL bead-beating kit (Nippon Gene, Japan) and purified using a MagExtractor DNA fragment purification kit (Toyobo, Japan) according to the manufacturer''s instructions. To increase concentration, DNA was amplified by multiple displacement amplification using the phi29 polymerase supplied with a GenomiPhi kit (GE Healthcare, United Kingdom) (20). Putative rdhA genes were amplified by PCR using Ex Taq polymerase (TaKaRa, Japan) with degenerate primers RRF2 and B1R (17), dehaloF3, dehaloF4, dehaloF5, dehaloR2, dehaloR3, and dehaloR4 (32), and ceRD2S, ceRD2L, and RD7 (26) and the PCR conditions described in those studies. Amplicons of the approximate target size were gel purified and cloned into the pCR2.1 vector (Invitrogen, Japan). Sequence similarity was analyzed using FastGroupII web-based software (34), and sequences with a 95% identity were tentatively assigned to the same phylotype. Amino acid sequences were aligned by ClustalW (31), including known and putative reductive dehalogenase sequences in the genome of Dehalococcoides ethenogenes strain 195 (28), as well as several functionally characterized reductive dehalogenases from other species.

TABLE 1.

Sample locations and results of PCR amplification of rdhA
Sampling site (expedition name)LocationWater depth (m)Core sectionSediment depth (mbsf)rdh amplification resulta
1226 (ODP Leg 201)Eastern equatorial Pacific3,2971-33.2++
6-346.7++
1227 (ODP Leg 201)Southeast Pacific off Peru4271-10.3+
3-216.6+
5D-542.0
9-375.1+
1230 (ODP Leg 201)Southeast Pacific off Peru5,0861-10.3++
10-373.8
27-3209.3
1301 (IODP Expedition 301)Northeast Pacific Juan de Fuca Ridge flank off Oregon2,6561-22.5+
6-651.2
11-190.8
1D-2132.5
C9001 (JAMSTEC Chikyu Shakedown Expedition CK06-06)Northwest Pacific off Japan1,1801-11.0++
2-513.5++
9-478.5+
21-4191.5+
24-4216.8++
25-6228.9
38-7346.3
40-3358.6+
C0002 (IODP Expedition 315)Nankai Trough Forearc Basin off Japan1,9371-31.9+
1-64.7
2-49.2+
2-813.4
3-520.2+
4-530.0
8-366.6+
16-4155.4
Open in a separate windowa−, PCR product of expected size not amplified; +, PCR product of expected size weakly amplified; ++, PCR product of expected size amplified and confirmed by sequencing analysis.Putative rdhA genes were successfully detected by primer set RRF2-B1R in samples from the eastern equatorial Pacific (ODP site 1226, 3.2 and 46.7 m below the seafloor [mbsf]), the Peru margin (ODP site 1227, 0.3, 16.6, and 75.1 mbsf, and ODP site 1230, 0.3 mbsf), the Juan de Fuca Ridge flank (IODP site 1301, 2.5 mbsf), offshore from the Shimokita Peninsula of Japan (CK06-06 site C9001, 1.0, 13.5, 78.5, 191.5, 216.8, and 358.6 mbsf), and the Nankai Trough Forearc Basin off the Kii Peninsula of Japan (IODP site C0002, 1.9, 9.2, 20.2, and 66.6 mbsf) (Table (Table1).1). No amplification was observed in samples from several deep horizons at sites 1227, 1230, 1301, C9001, and C0002 (Table (Table1).1). A total of 92 clones of subseafloor putative rdhA genes were sequenced and classified into 32 phylotypes (Fig. (Fig.1).1). Phylogenetic analysis revealed that all of the detected putative rdhA sequences were related to those of Dehalococcoides.Open in a separate windowFIG. 1.Phylogenetic tree based on the deduced amino acid sequences of rdhA genes, including sequences from marine subsurface sediments. Putative rdhA sequences from marine subsurface sediments (rdhA clones 1 to 32) are marked in red, while those of the Dehalococcoides genome are marked in blue. Clonal frequencies and sequence accession numbers are indicated in parentheses. Bootstrap values from 50% to 84% and 85% to 100% are indicated by open and solid circles at the branches, respectively. Asterisks indicate the following functionally characterized rdhA genes: pceA and prdA, tetrachloroethene reductive dehalogenase; tceA, trichloroethene reductive dehalogenase; vcrA and bvcA, vinyl chloride reductive dehalogenase; dcaA, 1,2-dichloroethane reductive dehalogenase; cprA, chlorophenol reductive dehalogenase; and cbrA, chlorobenzene reductive dehalogenase. The tree was constructed by a neighbor-joining (NJ) method based on an alignment of almost-complete rdhA amino acid sequences with pairwise gap deletion on MEGA version 4.0 software (30). The resulting tree was displayed using Interactive Tree Of Life (19). The scale bar represents 0.1 substitutions per amino acid position.In the alignment of the subseafloor rdhA sequences, we observed two Fe-S cluster-binding motifs as a conserved structure of previously reported reductive dehalogenases (29). The sequences were amplified with primer RRF2 containing the N-terminal twin arginine translocation (Tat) signal sequence and primer B1R containing the rdhB genes encoding a putative dehalogenase membrane anchor protein (17). Thus, the dehalogenases of subseafloor bacteria have a structural framework similar to that of known dehalogenases from terrestrial Dehalococcoides species. However, BLASTP analysis showed that similarities among subseafloor rdhA sequences and previously reported dehalogenase sequences were generally low, ranging from 33.06% to 64.27%. Some sequences were affiliated, with relatively high bootstrap values, with subseafloor rdhA clusters I and II, which are clearly distinct from the rdhA sequences of Dehalococcoides and other known species (Fig. (Fig.1).1). In addition, we were unable to detect subseafloor rdhA genes using other primer sets targeting cprA- and pceA-like genes (26, 32). These results indicate that most subseafloor rdhA genes are distinct from those reported from terrestrial environments, a trend that corroborates the results of a metagenomic survey of subseafloor microbial communities at the Peruvian site (3). However, it is worth noting that the RRF2 and B1R primers used in this study are based on the rdhA sequences present in Dehalococcoides (17) and that sequence retrieval is probably biased by primer mismatch. It is thus likely that there are still unexplored functional genes related to the dehalorespiration pathways in marine subsurface sediments.An interesting finding of the functional gene survey is that the subseafloor rdhA homologues are preferentially detected in shallow sediments. At site C9001 off Japan, the sedimentation ratio is considerably higher than at other sites (54 to 95 cm per 1,000 years) (unpublished data), and rdhA genes were successfully detected in horizons as deep as 358 mbsf (Table (Table1).1). The rdhA genes were also detected in sediments from the open ocean at site 1226, which contained very low concentrations (<0.2%) of organic matter (7). This may be because halogenated compounds are derived not only from terrestrial environments but also from the seawater overlying the sediments. In addition, a diverse range of marine organisms, such as phytoplankton, mollusks, algae, polychaetes, jellyfish, and sponges, are known to produce halogenated organic compounds (11). For example, the amount of brominated organic compounds in the ocean has been estimated at 1 to 2 million tons per year (10). Since these halogenated compounds are generally recalcitrant or not metabolizable by aerobic microorganisms in the seawater column (15), they are effectively buried in marine subsurface sediments. In fact, debromination of brominated phenols in marine, estuarine, or intertidal strait sediments has been reported (4, 9, 16, 22), and a brominated phenol-dehalogenating microbial community has been observed in the marine sponge Aplysina aerophoba, which produces bromophenolic metabolites (1).We also observed reductive dehalogenation activity in subseafloor sediment slurry from site C0002 in the Nankai Trough (Fig. (Fig.2;2; also see the supplemental material). The slurry sample was prepared by mixing sediment samples from 1.9, 4.7, 9.2, 13.4, 20.2, 30.0, 66.6, and 155.4 mbsf. During the initial incubation with 2,4,6-tribromophenol (2,4,6-TBP) for 179 days, 2,4,6-TBP was completely converted to phenol. We then supplemented the same incubation slurry with 2,4,6-TBP and once again observed dehalogenation activity (Fig. (Fig.2A).2A). During the incubation, 2,4-dibromophenol and 4-bromophenol were produced as intermediates (Fig. (Fig.2C),2C), suggesting that ortho debromination occurred in preference to para debromination, as observed previously in marine sponge habitats (1). The maximum phenol production rate during the second incubation was calculated to be 0.094 μM per 1 cm3 of sediment per day (Fig. (Fig.2A2A).Open in a separate windowFIG. 2.Dehalogenation activities of subseafloor microbes. (A) Debromination of 2,4,6-TBP in a subseafloor sediment slurry from site C0002 in the Nankai Trough Forearc Basin. Arrow indicates the timing of 2,4,6-TBP supplementation. (B) Dechlorination of TCE in the same slurry sample. Sterilized control sediment slurries did not exhibit phenol and/or cis-DCE production (data not shown). (C) Potential debromination pathway of 2,4,6-TBP (solid arrows) and (D) potential dechlorination pathway of TCE (solid arrows) observed. The pathways indicated by dashed arrows were not observed in this experiment.Using the same sediment slurry sample, we also observed dehalogenation activity of trichloroethene (TCE), a substantial pollutant in the natural environment. During an incubation lasting more than 200 days, TCE was almost entirely converted to cis-dichloroethene (cis-DCE) (Fig. (Fig.2B).2B). The subsequent dechlorination step of cis-DCE, which is presumably from cis-DCE to monochloroethene, was not observed during the incubation. The rate of cis-DCE production was calculated as 0.045 μM per 1 cm3 of sediment per day.In conclusion, the observed molecular and activity data suggest that metabolically active dehalorespiring microbes are well represented in marine subsurface sediments and that these microbes may be widely distributed in Pacific Ocean margin sediments. Given the relatively high in vitro activity rates, we expect that subseafloor dehalorespiring microbes play important ecological roles in the biogeochemical cycles of chlorine, iodine, and bromine, as well as in halogenated carbon substrates. The distribution of in situ activity rates, chemical and geophysical constraints, metabolic characteristics of the individual dehalorespiring phylotypes, and genetic and enzymatic mechanisms of the microbes remain to be clarified. Nevertheless, the findings of this study provide new evidence of microbial functioning in the subseafloor ecosystem.  相似文献   

9.
Cultivation and Genomic,Nutritional, and Lipid Biomarker Characterization of Roseiflexus Strains Closely Related to Predominant In Situ Populations Inhabiting Yellowstone Hot Spring Microbial Mats     
Marcel T. J. van der Meer  Christian G. Klatt  Jason Wood  Donald A. Bryant  Mary M. Bateson  Laurens Lammerts  Stefan Schouten  Jaap S. Sinninghe Damsté  Michael T. Madigan  David M. Ward 《Journal of bacteriology》2010,192(12):3033-3042
  相似文献   

10.
Spontaneous Quinolone Resistance in the Zoonotic Serovar of Vibrio vulnificus     
Francisco J. Roig  A. Llorens  B. Fouz  C. Amaro 《Applied and environmental microbiology》2009,75(8):2577-2580
This work demonstrates that Vibrio vulnificus biotype 2, serovar E, an eel pathogen able to infect humans, can become resistant to quinolone by specific mutations in gyrA (substitution of isoleucine for serine at position 83) and to some fluoroquinolones by additional mutations in parC (substitution of lysine for serine at position 85). Thus, to avoid the selection of resistant strains that are potentially pathogenic for humans, antibiotics other than quinolones must be used to treat vibriosis on farms.Vibrio vulnificus is an aquatic bacterium from warm and tropical ecosystems that causes vibriosis in humans and fish (http://www.cdc.gov/nczved/dfbmd/disease_listing/vibriov_gi.html) (33). The species is heterogeneous and has been subdivided into three biotypes and more than eight serovars (6, 15, 33; our unpublished results). While biotypes 1 and 3 are innocuous for fish, biotype 2 can infect nonimmune fish, mainly eels, by colonizing the gills, invading the bloodstream, and causing death by septicemia (23). The disease is rapidly transmitted through water and can result in significant economic losses to fish farmers. Surviving eels are immune to the disease and can act as carriers, transmitting vibriosis between farms. Interestingly, biotype 2 isolates belonging to serovar E have been isolated from human infections, suggesting that serovar E is zoonotic (2). This serovar is also the most virulent for fish and has been responsible for the closure of several farms due to massive losses of fish. A vaccine, named Vulnivaccine, has been developed from serovar E isolates and has been successfully tested in the field (14). Although the vaccine provides fish with long-term protection from vibriosis, at present its use is restricted to Spain. For this reason, in many fish farms around the world, vibriosis is treated with antibiotics, which are usually added to the food or water.Quinolones are considered the most effective antibiotics against human and fish vibriosis (19, 21, 31). These antibiotics can persist for a long time in the environment (20), which could favor the emergence of resistant strains under selective pressure. In fact, spontaneous resistances to quinolones by chromosomal mutations have been described for some gram-negative bacteria (10, 11, 17, 24, 25, 26). Therefore, improper antibiotic treatment of eel vibriosis or inadequate residue elimination at farms could favor the emergence of human-pathogenic serovar E strains resistant to quinolones by spontaneous mutations. Thus, the main objective of the present work was to find out if the zoonotic serovar of biotype 2 can become quinolone resistant under selective pressure and determine the molecular basis of this resistance.Very few reports on resistance to antibiotics in V. vulnificus have been published; most of them have been performed with biotype 1 isolates. For this reason, the first task of this study was to determine the antibiotic resistance patterns in a wide collection of V. vulnificus strains belonging to the three biotypes that had been isolated worldwide from different sources (see Table S1 in the supplemental material). Isolates were screened for antimicrobial susceptibility to the antibiotics listed in Table S1 in the supplemental material by the agar diffusion disk procedure of Bauer et al. (5), according to the standard guideline (9). The resistance pattern found for each isolate is shown in Table S1 in the supplemental material. Less than 14% of isolates were sensitive to all the antibiotics tested, and more than 65% were resistant to more than one antibiotic, irrespective of their biotypes or serovars. The most frequent resistances were to ampicillin-sulbactam (SAM; 65.6% of the strains) and nitrofurantoin (F; 60.8% of the strains), and the least frequent were to tetracycline (12%) and oxytetracycline (8%). In addition, 15% of the strains were resistant to nalidixic acid (NAL) and oxolinic acid (OA), and 75% of these strains came from fish farms (see Table S1 in the supplemental material). Thus, high percentages of strains of the three biotypes were shown to be resistant to one or more antibiotics, with percentages similar to those found in nonbiotyped environmental V. vulnificus isolates from Asia and North America (4, 27, 34). In those studies, resistance to antibiotics could not be related to human contamination. However, the percentage of quinolone-resistant strains found in our study is higher than that reported in other ones, probably due to the inclusion of fish farm isolates, where the majority of quinolone-resistant strains were concentrated. This fact suggests that quinolone resistance could be related to human contamination due to the improper use of these drugs in therapy against fish diseases, as has been previously suggested (18, 20). Although no specific resistance pattern was associated with particular biotypes or serovars, we found certain differences in resistance distribution, as shown in Table Table1.1. In this respect, biotype 3 displayed the narrowest spectrum of resistances and biotype 1 the widest. The latter biotype encompassed the highest number of strains with multiresistance (see Table S1 in the supplemental material). Within biotype 2, there were differences among serovars, with quinolone resistance being restricted to the zoonotic serovar (Table (Table11).

TABLE 1.

Percentage of resistant strains distributed by biotypes and serovars
V. vulnificusNo. of isolatesResistance distribution (%) for indicated antibiotica
SAMCTXENALFOTOASXT-TMPTE
Biotype 14975.524.514.330.683.78.230.628.68.2
Biotype 2 (whole)7258.313.912.54.247.29.74.24.213.9
Biotype 2
    Serovar E3630.312.139.127.315.29.1321.2
    Serovar A231009.118.2077.3009.14.6
    Nontypeable82914.325057.114.30014.3
    Serovar I5100202002020000
Biotype 3510002008000020
Open in a separate windowaCTX, cefotaxime; E, erythromycin; OT, oxytetracycline; SXT-TMP, sulfamethoxazole-trimethoprim; TE, tetracycline.The origin of resistance to quinolones in the zoonotic serovar was further investigated. To this end, spontaneous mutants of sensitive strains were selected from colonies growing within the inhibition halo around OA or NAL disks. Two strains (strain CG100 of biotype 1 and strain CECT 4604 of biotype 2, serovar E) developed isolated colonies within the inhibition zone. These colonies were purified, and maintenance of resistance was confirmed by serial incubations on medium without antibiotics. Using the disk diffusion method, CG100 was shown to be resistant to SAM and F and CECT 4604 to F (see Table S1 in the supplemental material). The MICs for OA, NAL, flumequine (UB), and ciprofloxacin (CIP) were determined by using the microplate assay according to the recommendations of the Clinical and Laboratory Standards Institute and the European Committee for Antimicrobial Susceptibility Testing of the European Society of Clinical Microbiology and Infectious Diseases (8, 12) and interpreted according to the European Committee for Antimicrobial Susceptibility Testing of the European Society of Clinical Microbiology and Infectious Diseases (13). The MICs for OA and NAL and for the fluoroquinolones UB and CIP exhibited by the mutants and their counterparts are shown in Table Table2.2. The inhibition zone diameters correlated well with MICs (data not shown). Mutants FR1, FR2, FR3, and FR4 were resistant to NAL and sensitive to the remaining quinolones, although they showed higher resistances than their parental strains (Table (Table2).2). Thus, these four mutants showed increases of 32- to 128-fold for NAL MICs, 4- to 8-fold for UB MICs, and 16-fold for CIP MICs (Table (Table2).2). The fifth mutant, FR5, was resistant to the two tested quinolones and to UB, a narrow-spectrum fluoroquinolone. This mutant, although sensitive to CIP, multiplied its MIC for this drug by 128 with respect to the parental strain (Table (Table22).

TABLE 2.

MICs for quinolones and fluoroquinolones and mutations in gyrA, gyrB, and parC detected in naturally and artificially induced resistant strains
Strain(s)MIC (μg ml−1) for indicated antibioticb
Gene mutationa
gyrA
gyrB
parC
Position
Codon changeaa changePosition
Codon changeaa changePosition
Codon changeaa change
NALOAUBCIPntaantaantaa
CG1000.5 (S)0.125 (S)0.0625 (S)0.0078 (S)
FR116 (R)1 (S)0.25 (S)0.125 (S)24883AGT→ATTS→INCNCNCNCNCNCNCNC
FR216 (R)1 (S)0.25 (S)0.125 (S)24883AGT→ATTS→INCNCNCNCNCNCNCNC
CECT 46040.25 (S)0.0625 (S)0.0625 (S)0.0078 (S)
FR332 (R)2 (S)0.5 (S)0.125 (S)24883AGT→ATTS→INCNCNCNCNCNCNCNC
FR432 (R)2 (S)0.5 (S)0.125 (S)24883AGT→ATTS→INCNCNCNCNCNCNCNC
FR5256 (R)16 (R)16 (R)1 (S)24883AGT→ATTS→I1156386GCA→ACAA→T25485TCA→TTAS→L
1236412CAG→CACQ→H
CECT 4602128 (R)8 (R)64 (R)1 (S)24883AGT→ATTS→INCNCNCNC25485TCA→TTAS→L
CECT 4603, CECT 4606, CECT 4608, PD-5, PD-12, JE32 (R)2 (S)<1 (S)<1 (S)24883AGT→ATTS→INCNCNCNCNCNCNCNC
CECT 486264 (R)2 (S)2 (S)<1 (S)24983AGT→AGAS→RNCNCNCNCNCNCNCNC
A2, A4, A5, A6, A7, PD-1, PD-364-128 (R)2 (S)4 (S)<1 (S)24883AGT→ATTS→INCNCNCNC338113GCA→GTAA→V
V1128 (R)4 (S)4 (S)<1 (S)24883AGT→ATTS→I1274425GAG→GGGE→GNCNCNCNC
1314438AAC→AAAN→K
Open in a separate windowaMutations in a nucleotide (nt) that gave rise to a codon change and to a change in amino acids (aa) are indicated. NC, no change detected.bThe resistance (R) or sensitivity (S) against the antibiotic determined according to the Clinical and Laboratory Standards Institute and the European Committee for Antimicrobial Susceptibility Testing of the European Society of Clinical Microbiology and Infectious Diseases (9, 13) is indicated in parentheses.For other gram-negative pathogens, quinolone resistance relies on spontaneous mutations in the gyrA, gyrB, parC, and parE genes that occur in a specific region of the protein known as the quinolone resistance-determining region (QRDR) (1, 11, 17, 24, 25, 26, 28). To test the hypothesis that mutations in these genes could also produce quinolone resistance in V. vulnificus, the QRDRs of these genes were sequenced in the naturally resistant strains and in the two sensitive strains that had developed resistances by selective pressure in vitro. The genomic DNA was extracted (3), and the QRDRs of gyrA, gyrB, parE, and parC were amplified using the primers shown in Table Table3,3, which were designed from the published genomes of biotype 1 strains YJ016 and CMCP6 (7, 22). PCR products of the predicted size were sequenced in an ABI 3730 sequencer (Applied Biosystems). Analysis of the QRDR sequences for gyrA, gyrB, parC, and parE of the mutants and the naturally resistant strains revealed that all naturally resistant strains, except one, shared a specific mutation at nucleotide position 248 with the laboratory-induced mutants (Table (Table2).2). This mutation gave rise to a change from serine to isoleucine at amino acid position 83. The exception was a mutation in the adjacent nucleotide that gave rise to a substitution of arginine for serine at the same amino acid position (Table (Table2).2). All the isolates that were resistant to the quinolone NAL had a unique mutation in the gyrA gene, irrespective of whether resistance was acquired naturally or in the laboratory (Table (Table2).2). This result strongly suggests that a point mutation in gyrA that gives rise to a change in nucleotide position 83 can confer resistance to NAL in V. vulnificus biotypes 1 and 2 and that this mutation could be produced by selective pressure under natural conditions. gyrA mutations consisting of a change from serine 83 to isoleucine have also been described in isolates of Aeromonas from water (17) and in diseased fish isolates of Vibrio anguillarum (26). Similarly, replacement of serine by arginine at amino acid position 83 in diseased fish isolates of Yersinia ruckeri (16) suggests that this mechanism of quinolone resistance is widespread among gram-negative pathogens. In all cases, these single mutations were also related to increased resistance to other quinolones (OA) and fluoroquinolones (UB and CIP) (Table (Table2),2), although the mutants remained sensitive according to the standards of the Clinical and Laboratory Standards Institute and the European Committee for Antimicrobial Susceptibility Testing of the European Society of Clinical Microbiology and Infectious Diseases (9, 13). A total of 50% of the naturally resistant strains, all of them of biotype 1, showed additional mutations that affected parC (a change in amino acid position 113) or gyrB (changes in amino acids at positions 425 and 438) (Table (Table2).2). These strains exhibited higher MICs for OA and fluoroquinolones (Table (Table2),2), although they were still sensitive to these drugs (9, 13). Finally, one isolate of biotype 2, serovar E, which was naturally resistant to quinolones and UB, showed a mutation in parC that gave rise to a substitution of leucine for serine at amino acid position 85 (Table (Table2).2). This mutation was shared only with the laboratory-induced mutant, also a biotype 2, serovar E mutant, which was resistant to the fluoroquinolone UB. The same mutation in parC had been previously described in diseased fish isolates of V. anguillarum that were highly resistant to quinolones (28), but this had not been related to fluoroquinolone resistance in Vibrio spp. nor in other gram-negative bacteria. These results strongly suggest that resistance to fluoroquinolones in V. vulnificus is related to specific mutations in gyrA and parC and that mutations in different positions for parC or in gyrB could contribute to increased resistance to quinolones and fluoroquinolones. Our results also agree with previous studies confirming that the acquisition of higher quinolone resistance is more probable when arising from a gyrA parC double mutation than from a gyrA gyrB double mutation (29).

TABLE 3.

Oligonucleotides used in this study
PrimerSequenceAnnealing temp (°C)Size (bp)
GyrAFGGCAACGACTGGAATAAACC55.8416
GyrARCAGCCATCAATCACTTCCGTC
ParCFCGCAAGTTCACCGAAGATGC56.6411
ParCRGGCATCCGCAACTTCACG
GyrBFCGACTTCTGGTGACGATGCG57.4642
GyrBRGACCGATACCACAACCTAGTG
ParEFGCCAGGTAAGTTGACCGATTG56.8512
ParERCACCCAGACCTTTGAATCGTTG
Open in a separate windowFinally, the evolutionary history for each protein was inferred from previously published DNA sequences of the whole genes from different Vibrio species after multiple sequence alignment with MEGA4 software (32) by applying the neighbor-joining method (30) with the Poisson correction (35). The distance tree for each whole protein showed a topology similar to the phylogenetic tree based on 16S rRNA analysis, with the two isolates of V. vulnificus forming a single group, closely related to Vibrio parahaemolyticus, Vibrio cholerae, V. anguillarum, and Vibrio harveyi (see Fig. S1A in the supplemental material). A second analysis was performed with the QRDR sequences of the different mutants and isolates of V. vulnificus (GenBank accession numbers FJ379836 to FJ379927) to infer the intraspecies relationships (see Fig. S1B in the supplemental material). This analysis showed that QRDRs of gyrA, gyrB, parC, and parE were highly homogeneous within V. vulnificus.In summary, the zoonotic serovar of V. vulnificus can mutate spontaneously to gain quinolone resistance, under selective pressure in vitro, due to specific mutations in gyrA that involve a substitution of isoleucine for serine at amino acid position 83. This mutation appears in biotype 2, serovar E diseased-fish isolates and biotype 1 strains, mostly recovered from fish farms. An additional mutation in parC, resulting in a substitution of lysine for serine at amino acid position 85, seems to endow partial fluoroquinolone resistance on biotype 2, serovar E strains. This kind of double mutation is present in diseased-fish isolates of the zoonotic serovar but not in resistant biotype 1 isolates, which show different mutations in gyrB or in parC that increase their resistance levels but do not make the strains resistant to fluoroquinolones. Thus, antibiotics other than quinolones should be used at fish farms to prevent the emergence and spread of quinolone resistances, especially to CIP, a drug widely recommended for human vibriosis treatment.  相似文献   

11.
RNA-Based Investigation of Ammonia-Oxidizing Archaea in Hot Springs of Yunnan Province,China     
Hongchen Jiang  Qiuyuan Huang  Hailiang Dong  Peng Wang  Fengping Wang  Wenjun Li  Chuanlun Zhang 《Applied and environmental microbiology》2010,76(13):4538-4541
  相似文献   

12.
Identification of a Polyketide Synthase Coding Sequence Specific for Anatoxin-a-Producing Oscillatoria Cyanobacteria     
Sabrina Cadel-Six  Isabelle Iteman  Caroline Peyraud-Thomas  Stéphane Mann  Olivier Ploux  Annick Méjean 《Applied and environmental microbiology》2009,75(14):4909-4912
  相似文献   

13.
Intrathecal Humoral Responses Are Inversely Associated with the Frequency of Simian Immunodeficiency Virus Macrophage-Tropic Variants in the Central Nervous System     
Elena Ryzhova  Pyone Aye  Tom Harvey  Wei Cao  Andrew Lackner  Francisco González-Scarano 《Journal of virology》2009,83(16):8282-8288
  相似文献   

14.
Retrograde Intraflagellar Transport Mutants Identify Complex A Proteins With Multiple Genetic Interactions in Chlamydomonas reinhardtii          下载免费PDF全文
Carlo Iomini  Linya Li  Jessica M. Esparza  Susan K. Dutcher 《Genetics》2009,183(3):885-896
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   

15.
Characterization of a Thermostable Short-Chain Alcohol Dehydrogenase from the Hyperthermophilic Archaeon Thermococcus sibiricus     
Tatiana N. Stekhanova  Andrey V. Mardanov  Ekaterina Y. Bezsudnova  Vadim M. Gumerov  Nikolai V. Ravin  Konstantin G. Skryabin  Vladimir O. Popov 《Applied and environmental microbiology》2010,76(12):4096-4098
Short-chain alcohol dehydrogenase, encoded by the gene Tsib_0319 from the hyperthermophilic archaeon Thermococcus sibiricus, was expressed in Escherichia coli, purified and characterized as an NADPH-dependent enantioselective oxidoreductase with broad substrate specificity. The enzyme exhibits extremely high thermophilicity, thermostability, and tolerance to organic solvents and salts.Alcohol dehydrogenases (ADHs; EC 1.1.1.1.) catalyze the interconversion of alcohols to their corresponding aldehydes or ketones by using different redox-mediating cofactors. NAD(P)-dependent ADHs, due to their broad substrate specificity and enantioselectivity, have attracted particular attention as catalysts in industrial processes (5). However, mesophilic ADHs are unstable at high temperatures, sensitive to organic solvents, and often lose activity during immobilization. In this relation, there is a considerable interest in ADHs from extremophilic microorganisms; among them, Archaea are of great interest. The representatives of all groups of NAD(P)-dependent ADHs have been detected in genomes of Archaea (11, 12); however, only a few enzymes have been characterized, and the great majority of them belong to medium-chain (3, 4, 14, 16, 19) or long-chain iron-activated ADHs (1, 8, 9). Up to now, a single short-chain archaeal ADH from Pyrococcus furiosus (10, 18) and only one archaeal aldo-keto reductase also from P. furiosus (11) have been characterized.Thermococcus sibiricus is a hyperthermophilic anaerobic archaeon isolated from a high-temperature oil reservoir capable of growth on complex organic substrates (15). The complete genome sequence of T. sibiricus has been recently determined and annotated (13). Several ADHs are encoded by the T. sibiricus genome, including three short-chain ADHs (Tsib_0319, Tsib_0703, and Tsib_1998) (13). In this report, we describe the cloning and expression of the Tsib_0319 gene from T. sibiricus and the purification and the biochemical characterization of its product, the thermostable short-chain ADH (TsAdh319).The Tsib_0319 gene encodes a protein with a size of 234 amino acids and the calculated molecular mass of 26.2 kDa. TsAdh319 has an 85% degree of sequence identity with short-chain ADH from P. furiosus (AdhA; PF_0074) (18). Besides AdhA, close homologs of TsAdh319 were found among different bacterial ADHs, but not archaeal ADHs. The gene flanked by the XhoI and BamHI sites was PCR amplified using two primers (sense primer, 5′-GTTCTCGAGATGAAGGTTGCTGTGATAACAGGG-3′, and antisense primer, 5′-GCTGGATCCTCAGTATTCTGGTCTCTGGTAGACGG-3′) and cloned into the pET-15b vector. TsAdh319 was overexpressed, with an N-terminal His6 tag in Escherichia coli Rosetta-gami (DE3) and purified to homogeneity by metallochelating chromatography (Hi-Trap chelating HP column; GE Healthcare) followed by gel filtration on Superdex 200 10/300 GL column (GE Healthcare) equilibrated in 50 mM Tris-HCl (pH 7.5) with 200 mM NaCl. The homogeneity and the correspondence to the calculated molecular mass of 28.7 kDa were verified by SDS-PAGE (7). The molecular mass of native TsAdh319 was 56 to 60 kDa, which confirmed the dimeric structure in solution.The standard ADH activity measurement was made spectrophotometrically at the optimal pH by following either the reduction of NADP (in 50 mM Gly-NaOH buffer; pH 10.5) or the oxidation of NADPH (in 0.1 M sodium phosphate buffer; pH 7.5) at 340 nm at 60°C. The enzyme exhibited a strong preference for NADP(H) and broad substrate specificity (Table (Table1).1). The highest oxidation rates were found with pentoses d-arabinose (2.0 U mg−1) and d-xylose (2.46 U mg−1), and the highest reduction rates were found with dimethylglyoxal (5.9 U mg−1) and pyruvaldehyde (2.2 U mg−1). The enzyme did not reduce sugars which were good substrates for the oxidation reaction. The kinetic parameters of TsAdh319 determined for the preferred substrates are shown in Table Table2.2. The enantioselectivity of the enzyme was estimated by measuring the conversion rates of 2-butanol enantiomers. TsAdh319 showed an evident preference, >2-fold, for (S)-2-butanol over (RS)-2-butanol. The enzyme stereoselectivity is confirmed by the preferred oxidation of d-arabinose over l-arabinose (Table (Table1).1). The fact that TsAdh319 is metal independent was supported by the absence of a significant effect of TsAdh319 preincubation with 10 mM Me2+ for 30 min before measuring the activity in the presence of 1 mM Me2+ or EDTA (Table (Table3).3). TsAdh319 also exhibited a halophilic property, so the enzyme activity increased in the presence of NaCl and KCl and the activation was maintained even at concentration of 4 M and 3 M, respectively (Table (Table33).

TABLE 1.

Substrate specificity of TsAdh319
SubstrateaRelative activity (%)
Oxidation reactionb
    Methanol0
    2-Methoxyethanol0
    Ethanol36
    1-Butanol80
    2-Propanol100
    (RS)-(±)-2-Butanol86
    (S)-(+)-2-Butanol196
    2-Pentanol67
    1-Phenylmethanol180
    1.3-Butanediol91
    Ethyleneglycol0
    Glycerol16
    d-Arabinose*200
    l-Arabinose*17
    d-Xylose*246
    d-Ribose*35
    d-Glucose*146
    d-Mannose*48
    d-Galactose*0
    Cellobiose*71
Reduction reactionc
    Pyruvaldehyde100
    Dimethylglyoxal270
    Glyoxylic acid36
    Acetone0
    Cyclopentanone0
    Cyclohexanone4
    3-Methyl-2-pentanone*13
    d-Arabinose*0
    d-Xylose*0
    d-Glucose*0
    Cellobiose*0
Open in a separate windowaSubstrates were present in 250 mM or 50 mM (*) concentrations.bRelative rates, measured under standard conditions, were calculated by defining the activity for 2-propanol as 100%, which corresponds to 1.0 U mg−1. Data are averages from triplicate experiments.cRelative rates, measured under standard conditions, were calculated by defining the activity for pyruvaldehyde as 100%, which corresponds to 2.2 U mg−1. Data are averages from triplicate experiments.

TABLE 2.

Apparent Km and Vmax values for TsAdh319
Coenzyme or substrateApparent Km (mM)Vmax (U mg−1)kcat (s−1)
NADPa0.022 ± 0.0020.94 ± 0.020.45 ± 0.01
NADPHb0.020 ± 0.0033.16 ± 0.111.51 ± 0.05
2-Propanol168 ± 291.10 ± 0.090.53 ± 0.04
d-Xylose54.4 ± 7.41.47 ± 0.090.70 ± 0.04
Pyruvaldehyde17.75 ± 3.384.26 ± 0.402.04 ± 0.19
Open in a separate windowaActivity was measured under standard conditions with 2-propanol. Data are averages from triplicate experiments.bActivity was measured under standard conditions with pyruvaldehyde. Data are averages from triplicate experiments.

TABLE 3.

Effect of various ions and EDTA on TsAdh319a
CompoundConcn (mM)Relative activity (%)
None0100
NaCl400206
600227
4,000230
KCl600147
2,000200
3,000194
MgCl21078
CoCl210105
NiSO410100
ZnSO41079
FeSO41074
EDTA1100
580
Open in a separate windowaThe activity was measured under standard conditions with 2-propanol; relative rates were calculated by defining the activity without salts as 100%, which corresponds to 0.9 U mg−1. Data are averages from duplicate experiments.The most essential distinctions of TsAdh319 are the thermophilicity and high thermostability of the enzyme. The optimum temperature for the 2-propanol oxidation catalyzed by TsAdh319 was not achieved. The initial reaction rate of oxidation increased up to 100°C (Fig. (Fig.1).1). The Arrhenius plot is a straight line, typical of a single rate-limited thermally activated process, but there is no obvious transition point due to the temperature-dependent conformational changes of the protein molecule. The activation energy for the oxidation of 2-propanol was estimated at 84.0 ± 5.8 kJ·mol−1. The thermostability of TsAdh319 was calculated from residual TsAdh319 activity after preincubation of 0.4 mg/ml enzyme solution in 50 mM Tris-HCl buffer (pH 7.5) containing 200 mM NaCl at 70, 80, 90, or 100°C. The preincubation at 70°C or 80°C for 1.5 h did not cause a decrease in the TsAdh319 activity, but provoked slight activation. The residual TsAdh319 activities began to decrease after 2 h of preincubation at 70°C or 80°C and were 10% and 15% down from the control, respectively. The determined half-life values of TsAdh319 were 2 h at 90°C and 1 h at 100°C.Open in a separate windowFIG. 1.Temperature dependence of the initial rate of the 2-propanol reduction by TsAdh319. The reaction was initiated by enzyme addition to a prewarmed 2-propanol-NADP mixture. The inset shows the Arrhenius plot of the same data.Protein thermostability often correlates with such important biotechnological properties as increased solvent tolerance (2). We tested the influence of organic solvents at a high concentration (50% [vol/vol]) on TsAdh319 by using either preincubation of the enzyme at a concentration of 0.2 mg/ml with solvents for 4 h at 55°C or solvent addition into the reaction mixture to distinguish the effect of solvent on the protein stability and on the enzyme activity. TsAdh319 showed significant solvent tolerance in both cases (Table (Table4),4), and the effects of solvents could be modulated by salts, acting apparently as molecular lyoprotectants (17). Furthermore, TsAdh319 maintained 57% of its activity in 25% (vol/vol) 2-propanol, which could be used as the cosubstrate in cofactor regeneration (6).

TABLE 4.

Influence of various solvents on TsAdh319 activitya
SolventRelative activity (%)bRelative activity (%)c
Buffer without NaClBuffer with 600 mM NaCl
None100100100
DMSOd98040
DMFAe1011341
Methanol98259
Acetonitrile9500
Ethyl acetate470*33*
Chloroform10579*81*
n-Hexane10560*118*
n-Decane3691*107*
Open in a separate windowaThe activity measured at the standard condition with 2-propanol as a substrate. Data are averages from triplicate experiments.bPreincubation for 4 h at 55°C in the presence of 50% (vol/vol) of solvent prior the activity assay.cWithout preincubation, solvent addition to the reaction mixture up to 50% (vol/vol) or using the buffer saturated by a solvent (*).dDMSO, dimethyl sulfoxide.eDMFA, dimethylformamide.From all the aforesaid we may suppose TsAdh319 or its improved variant to be interesting both for the investigation of structural features of protein tolerance and for biotechnological applications.  相似文献   

16.
Genetic Testing of the Hypothesis That Hybrid Male Lethality Results From a Failure in Dosage Compensation     
Daniel A. Barbash 《Genetics》2010,184(1):313-316
  相似文献   

17.
Quantitative Real-Time PCR Assays for Sensitive Detection of Canada Goose-Specific Fecal Pollution in Water Sources     
B. Fremaux  T. Boa  C. K. Yost 《Applied and environmental microbiology》2010,76(14):4886-4889
Canada geese (Branta canadensis) are prevalent in North America and may contribute to fecal pollution of water systems where they congregate. This work provides two novel real-time PCR assays (CGOF1-Bac and CGOF2-Bac) allowing for the specific and sensitive detection of Bacteroides 16S rRNA gene markers present within Canada goose feces.The Canada goose (Branta canadensis) is a prevalent waterfowl species in North America. The population density of Canada geese has doubled during the past 15 years, and the population was estimated to be close to 3 million in 2007 (4). Canada geese often congregate within urban settings, likely due to available water sources, predator-free grasslands, and readily available food supplied by humans (6). They are suspected to contribute to pollution of aquatic environments due to the large amounts of fecal matter that can be transported into the water. This can create a public health threat if the fecal droppings contain pathogenic microorganisms (6, 7, 9, 10, 12, 13, 19). Therefore, tracking transient fecal pollution of water due to fecal inputs from waterfowl, such as Canada geese, is of importance for protecting public health.PCR detection of host-specific 16S rRNA gene sequences from Bacteroidales of fecal origin has been described as a promising microbial source-tracking (MST) approach due to its rapidity and high specificity (2, 3). Recently, Lu et al. (15) characterized the fecal microbial community from Canada geese by constructing a 16S rRNA gene sequence database using primers designed to amplify all bacterial 16S rRNA gene sequences. The authors reported that the majority of the 16S rRNA gene sequences obtained were related to Clostridia or Bacilli and to a lesser degree Bacteroidetes, which represent possible targets for host-specific source-tracking assays.The main objective of this study was to identify novel Bacteroidales 16S rRNA gene sequences that are specific to Canada goose feces and design primers and TaqMan fluorescent probes for sensitive and specific quantification of Canada goose fecal contamination in water sources.Primers 32F and 708R from Bernhard and Field (2) were used to construct a Bacteroidales-specific 16S rRNA gene clone library from Canada goose fecal samples (n = 15) collected from grass lawns surrounding Wascana Lake (Regina, SK, Canada) in May 2009 (for a detailed protocol, see File S1 in the supplemental material). Two hundred eighty-eight clones were randomly selected and subjected to DNA sequencing (at the Plant Biotechnology Institute DNA Technologies Unit, Saskatoon, SK, Canada). Representative sequences of each operational taxonomic unit (OTU) were recovered using an approach similar to that described by Mieszkin et al. (16). Sequences that were less than 93% similar to 16S rRNA gene sequences from nontarget host species in GenBank were used in multiple alignments to identify regions of DNA sequence that were putatively goose specific. Subsequently, two TaqMan fluorescent probe sets (targeting markers designated CGOF1-Bac and CGOF2-Bac) were designed using the RealTimeDesign software provided by Biosearch Technologies (http://www.biosearchtech.com/). The newly designed primer and probe set for the CGOF1-Bac assay included CG1F (5′-GTAGGCCGTGTTTTAAGTCAGC-3′) and CG1R (5′-AGTTCCGCCTGCCTTGTCTA-3′) and a TaqMan probe (5′-6-carboxyfluorescein [FAM]-CCGTGCCGTTATACTGAGACACTTGAG-Black Hole Quencher 1 [BHQ-1]-3′), and the CGOF2-Bac assay had primers CG2F (5′-ACTCAGGGATAGCCTTTCGA-3′) and CG2R (5′-ACCGATGAATCTTTCTTTGTCTCC-3′) and a TaqMan probe (5′-FAM-AATACCTGATGCCTTTGTTTCCCTGCA-BHQ-1-3′). Oligonucleotide specificities for the Canada goose-associated Bacteroides 16S rRNA primers were verified through in silico analysis using BLASTN (1) and the probe match program of the Ribosomal Database Project (release 10) (5). Host specificity was further confirmed using DNA extracts from 6 raw human sewage samples from various geographical locations in Saskatchewan and 386 fecal samples originating from 17 different animal species in Saskatchewan, including samples from Canada geese (n = 101) (Table (Table1).1). An existing nested PCR assay for detecting Canada goose feces (15) (targeting genetic marker CG-Prev f5) (see Table S1 in the supplemental material) was also tested for specificity using the individual fecal and raw sewage samples (Table (Table1).1). All fecal DNA extracts were obtained from 0.25 g of fecal material by using the PowerSoil DNA extraction kit (Mo Bio Inc., Carlsbad, CA) (File S1 in the supplemental material provides details on the sample collection).

TABLE 1.

Specificities of the CGOF1-Bac, CGOF2-Bac, and CG-Prev f5 PCR assays for different species present in Saskatchewan, Canada
Host group or sample typeNo. of samplesNo. positive for Bacteroidales marker:
CGOF1-BacCGOF2-BacCG-Prev f5All-Bac
Individual human feces2500125
Raw human sewage60006
Cows4100041
Pigs4800148
Chickens3400834
Geese10158515995a
Gulls1600614
Pigeons2510222
Ducks1000010
Swans10001
Moose1000010
Deer
    White tailed1000010
    Mule1000010
    Fallow1000010
Caribou1000010
Bison1000010
Goats1000010
Horses1500015
Total392595177381
Open in a separate windowaThe 6 goose samples that tested negative for the All-Bac marker also tested negative for the three goose markers.The majority of the Canada goose feces analyzed in this study (94%; 95 of 101) carried the Bacteroidales order-specific genetic marker designated All-Bac, with a relatively high median concentration of 8.2 log10 copies g1 wet feces (Table (Table11 and Fig. Fig.1).1). The high prevalence and abundance of Bacteroidales in Canada goose feces suggested that detecting members of this order could be useful in identifying fecal contamination associated with Canada goose populations.Open in a separate windowFIG. 1.Concentrations of the Bacteroidales (All-Bac, CGOF1-Bac, and CGOF2-Bac) genetic markers in feces from various individual Canada geese.The composition of the Bacteroidales community in Canada goose feces (n = 15) was found to be relatively diverse since 52 OTUs (with a cutoff of 98% similarity) were identified among 211 nonchimeric 16S rRNA gene sequences. Phylogenetic analysis of the 52 OTUs (labeled CGOF1 to CGOF52) revealed that 43 (representing 84% of the 16S rRNA gene sequences) were Bacteroides like and that 9 (representing 16% of the 16S rRNA gene sequences) were likely to be members of the Prevotella-specific cluster (see Fig. S2 in the supplemental material). Similarly, Jeter et al. (11) reported that 75.7% of the Bacteroidales 16S rRNA clone library sequences generated from goose fecal samples were Bacteroides like. The majority of the Bacteroides- and Prevotella-like OTUs were dispersed among a wide range of previously characterized sequences from various hosts and did not occur in distinct clusters suitable for the design of Canada goose-associated real-time quantitative PCR (qPCR) assays (see Fig. S2 in the supplemental material). However, two single Bacteroides-like OTU sequences (CGOF1 and CGOF2) contained putative goose-specific DNA regions that were identified by in silico analysis (using BLASTN, the probe match program of the Ribosomal Database Project, and multiple alignment). The primers and probe for the CGOF1-Bac and CGOF2-Bac assays were designed with no mismatches to the clones CGOF1 and CGOF2, respectively.The CGOF2-Bac assay demonstrated no cross-amplification with fecal DNA from other host groups, while cross-amplification for the CGOF1-Bac assay was limited to one pigeon fecal sample (1 of 25, i.e., 4% of the samples) (Table (Table1).1). Since the abundance in the pigeon sample was low (3.3 log10 marker copies g1 feces) and detection occurred late in the qPCR (with a threshold cycle [CT] value of 37.1), it is unlikely that this false amplification would negatively impact the use of the assay as a tool for detection of Canada goose-specific fecal pollution in environmental samples. In comparison, the nested PCR CG-Prev f5 assay described by Lu and colleagues (15) demonstrated non-host-specific DNA amplification with fecal DNA samples from several animals, including samples from humans, pigeons, gulls, and agriculturally relevant pigs and chickens (Table (Table11).Both CGOF1-Bac and CGOF2-Bac assays showed limits of quantification (less than 10 copies of target DNA per reaction) similar to those of other host-specific Bacteroidales real-time qPCR assays (14, 16, 18). The sensitivities of the CGOF1-Bac and CGOF2-Bac assays were 57% (with 58 of 101 samples testing positive) and 50% (with 51 of 101 samples testing positive) for Canada goose feces, respectively (Table (Table1).1). A similar sensitivity of 58% (with 59 of 101 samples testing positive) was obtained using the CG-Prev f5 PCR assay. The combined use of the three assays increased the detection level to 72% (73 of 101) (Fig. (Fig.2).2). Importantly, all markers were detected within groups of Canada goose feces collected each month from May to September, indicating relative temporal stability of the markers. The CG-Prev f5 PCR assay is an end point assay, and therefore the abundance of the gene marker in Canada goose fecal samples could not be determined. However, development of the CGOF1-Bac and CGOF2-Bac qPCR approach allowed for the quantification of the host-specific CGOF1-Bac and CGOF2-Bac markers. In the feces of some individual Canada geese, the concentrations of CGOF1-Bac and CGOF2-Bac were high, reaching levels up to 8.8 and 7.9 log10 copies g1, respectively (Fig. (Fig.11).Open in a separate windowFIG. 2.Venn diagram for Canada goose fecal samples testing positive with the CGOF1-Bac, CGOF2-Bac, and/or CG-Prev f5 PCR assay. The number outside the circles indicates the number of Canada goose fecal samples for which none of the markers were detected.The potential of the Canada goose-specific Bacteroides qPCR assays to detect Canada goose fecal pollution in an environmental context was tested using water samples collected weekly during September to November 2009 from 8 shoreline sampling sites at Wascana Lake (see File S1 and Fig. S1 in the supplemental material). Wascana Lake is an urban lake, located in the center of Regina, that is routinely frequented by Canada geese. In brief, a single water sample of approximately 1 liter was taken from the surface water at each sampling site. Each water sample was analyzed for Escherichia coli enumeration using the Colilert-18/Quanti-Tray detection system (IDEXX Laboratories, Westbrook, ME) (8) and subjected to DNA extraction (with a PowerSoil DNA extraction kit [Mo Bio Inc., Carlsbad, CA]) for the detection of Bacteroidales 16S rRNA genetic markers using the Bacteroidales order-specific (All-Bac) qPCR assay (14), the two Canada goose-specific (CGOF1-Bac and CGOF2-Bac) qPCR assays developed in this study, and the human-specific (BacH) qPCR assay (17). All real-time and conventional PCR procedures as well as subsequent data analysis are described in the supplemental material and methods. The E. coli and All-Bac quantification data demonstrated that Wascana Lake was regularly subjected to some form of fecal pollution (Table (Table2).2). The All-Bac genetic marker was consistently detected in high concentrations (6 to 7 log10 copies 100 ml1) in all the water samples, while E. coli concentrations fluctuated according to the sampling dates and sites, ranging from 0 to a most probable number (MPN) of more than 2,000 100 ml1. High concentrations of E. coli were consistently observed when near-shore water experienced strong wave action under windy conditions or when dense communities of birds were present at a given site and time point.

TABLE 2.

Levels of E. coli and incidences of the Canada goose-specific (CGOF1-Bac and CGOF2-Bac), human-specific (BacH), and generic (All-Bac) Bacteroidales 16S rRNA markers at the different Wascana Lake sites sampled weeklya
SiteE. coli
All-Bac
CGOF1-Bac
CGOF2-Bac
BacH
No. of positive water samples/total no. of samples analyzed (%)Min level-max level (MPN 100 ml−1)Mean level (MPN 100 ml−1)No. of positive water samples/total no. of samples analyzed (%)Min level-max level (log copies 100 ml−1)Mean level (log copies 100 ml−1)No. of positive water samples/total no. of samples analyzed (%)Min level-max level (log copies 100 ml−1)Mean level (log copies 100 ml−1)No. of positive water samples/total no. of samples analyzed (%)Min level-max level (log copies 100 ml−1)Mean level (log copies 100 ml−1)No. of positive water samples/total no. of samples analyzedMin level-max level (log copies 100 ml−1)Mean level (log copies 100 ml−1)
W18/8 (100)6-19671.18/8 (100)6.2-8.16.96/8 (75)0-4.72.44/8 (50)0-41.72/80-3.71.7
W29/10 (90)0-1,12019410/10 (100)5.8-6.86.49/10 (90)0-3.72.68/10 (80)0-3.32.20/1000
W310/10 (100)6-1,55053410/10 (100)6-7.8710/10 (100)2.9-4.83.810/10 (100)2-4.53.40/1000
W410/10 (100)16-1,73252910/10 (100)6.4-7.6710/10 (100)3.2-4.63.910/10 (100)2.8-4.33.40/1000
W510/10 (100)2-2,42068710/10 (100)5.5-6.96.37/10 (70)0-3.21.75/10 (50)0-3.11.20/1000
W610/10 (100)3-1,99038910/10 (100)5.5-76.39/10 (90)0-4.32.86/10 (60)0-5.121/100-3.41.3
W77/7 (100)5-2,4204457/7 (100)5.7-7.876/7 (86)0-3.82.65/7 (71)0-4.42.42/70-5.12.8
W810/10 (100)17-98016010/10 (100)6.3-8.67.18/10 (80)0-4.62.87/10 (70)0-4.42.30/1000
Open in a separate windowaMin, minimum; max, maximum.The frequent detection of the genetic markers CGOF1-Bac (in 65 of 75 water samples [87%]), CGOF2-Bac (in 55 of 75 samples [73%]), and CG-Prev f5 (in 60 of 75 samples [79%]) and the infrequent detection of the human-specific Bacteroidales 16S rRNA gene marker BacH (17) (in 5 of 75 water samples [7%[) confirmed that Canada geese significantly contributed to the fecal pollution in Wascana Lake during the sampling period. Highest mean concentrations of both CGOF1-Bac and CGOF2-Bac markers were obtained at the sampling sites W3 (3.8 and 3.9 log10 copies 100 ml1) and W4 (3.4 log10 copies 100 ml1 for both), which are heavily frequented by Canada geese (Table (Table2),2), further confirming their significant contribution to fecal pollution at these particular sites. It is worth noting that concentrations of the CGOF1-Bac and CGOF2-Bac markers in water samples displayed a significant positive relationship with each other (correlation coefficient = 0.87; P < 0.0001), supporting the accuracy of both assays for identifying Canada goose-associated fecal pollution in freshwater.In conclusion, the CGOF1-Bac and CGOF2-Bac qPCR assays developed in this study are efficient tools for estimating freshwater fecal inputs from Canada goose populations. Preliminary results obtained during the course of the present study also confirmed that Canada geese can serve as reservoirs of Salmonella and Campylobacter species (see Fig. S3 in the supplemental material). Therefore, future work will investigate the cooccurence of these enteric pathogens with the Canada goose fecal markers in the environment.  相似文献   

18.
Identification of Enhancer Binding Proteins Important for Myxococcus xanthus Development     
Krista M. Giglio  Jessica Eisenstatt  Anthony G. Garza 《Journal of bacteriology》2010,192(1):360-364
  相似文献   

19.
Quantitative Fluorescence In Situ Hybridization of Microbial Communities in the Rumens of Cattle Fed Different Diets     
Yunhong Kong  Maolong He  Tim McAlister  Robert Seviour  Robert Forster 《Applied and environmental microbiology》2010,76(20):6933-6938
At present there is little quantitative information on the identity and composition of bacterial populations in the rumen microbial community. Quantitative fluorescence in situ hybridization using newly designed oligonucleotide probes was applied to identify the microbial populations in liquid and solid fractions of rumen digesta from cows fed barley silage or grass hay diets with or without flaxseed. Bacteroidetes, Firmicutes, and Proteobacteria were abundant in both fractions, constituting 31.8 to 87.3% of the total cell numbers. They belong mainly to the order Bacteroidales (0.1 to 19.2%), hybridizing with probe BAC1080; the families Lachnospiraceae (9.3 to 25.5%) and Ruminococcaceae (5.5 to 23.8%), hybridizing with LAC435 and RUM831, respectively; and the classes Deltaproteobacteria (5.8 to 28.3%) and Gammaproteobacteria (1.2 to 8.2%). All were more abundant in the rumen communities of cows fed diets containing silage (75.2 to 87.3%) than in those of cows fed diets containing hay (31.8 to 49.5%). The addition of flaxseed reduced their abundance in the rumens of cows fed silage-based diets (to 45.2 to 58.7%) but did not change markedly their abundance in the rumens of cows fed hay-based diets (31.8 to 49.5%). Fibrolytic species, including Fibrobacter succinogenes and Ruminococcus spp., and archaeal methanogens accounted for only a small proportion (0.4 to 2.1% and 0.2 to 0.6%, respectively) of total cell numbers. Depending on diet, between 37.0 and 91.6% of microbial cells specifically hybridized with the probes used in this study, allowing them to be identified in situ. The identities of other microbial populations (8.4 to 63.0%) remain unknown.The rumen is an anaerobic ecosystem used by herbivores to convert fibrous plant material into fermentation products that are in turn used as energy by the host. Fibrolytic degradation is accomplished by a complex microbial community which includes specialized fungi, protozoa, and bacteria (14). More than 200 bacterial species (5) have been isolated from rumen, and many of these have been phylogenetically and physiologically characterized. Several of these, including Fibrobacter succinogenes, Ruminococcus albus, and Ruminococcus flavefaciens, have the ability to hydrolyze cellulose in axenic culture (24). Despite the presence of these fibrolytic populations, a large portion of the fiber in low-quality forage diets passes through the rumen undigested. In the rumen, fibrolytic bacteria do not digest plant cell walls in isolation but rather interact with a consortium of bacteria (18). Although culture-dependent studies have improved our understanding of rumen microbiology, the importance of the isolates to the structure and function of the rumen microbial community, with the possible exception of the fibrolytic strains, is still unknown. Expanding our knowledge of the structure and function of the rumen microbial community may provide insights into approaches to improve the efficiency of fiber digestion and biofuel production (14).To provide a high-resolution view of the population structure of the rumen bacterial community, we used quantitative fluorescence in situ hybridization (qFISH) to investigate the composition and distribution of bacterial populations associated with the liquid and solid rumen contents from 12 ruminally cannulated Holstein dairy cows (3 cows were used for each diet) fed (for at least 21 days) grass hay or barley silage diets with or without flaxseed (Table (Table1).1). Six new 16S rRNA-targeted FISH probes (Table (Table2)2) for not only the fibrolytic groups but also other unclassified bacterial groups in the rumen were designed, using ARB software (17), against the rumen 16S rRNA gene sequences (data not shown) retrieved from the Ribosomal Database Project (RDP) database (6). The new probes target Bacteroidales-related clones (probe BAC1080) (phylum Bacteroidetes), Lachnospiraceae- and Ruminococcaceae-related clones (probes LAC435 and RUM831, respectively) (phylum Firmicutes), Butyrivibrio fibrisolvens-related clones (probe BFI826), and R. albus- and R. flavefaciens-related clones (probes RAL1436 and RFL155, respectively).

TABLE 1.

Composition of diets used in this study
IngredientDiet composition (% dry weight)
Hay-based dietHay and flaxseed dietSilage-based dietSilage and flaxseed diet
Alfalfa grass hay (chopped)47.547.500
Barley silage0047.547.5
Steamed rolled barley grain47.532.547.532.5
Ground flaxseeds015015
Other5555
Open in a separate window

TABLE 2.

Oligonucleotide probes and their target populations used in this study for FISH analyses
Probe nameaTarget rRNADesigned target(s)% FAbReference
EUB338 (00159)16SDomain Bacteria0-5016
EUB338II (00160)16SPhylum Planctomycetes0-5016
EUB338III (00161)16SPhylum Verrucomicrobia0-5016
NONEUB (00243)16SControl probe complementary to EUB3380-5016
ALF968 (00021)16SClass Alphaproteobacteria, phylum Proteobacteria2016
BET42a (00034)23SClass Betaproteobacteria, phylum Proteobacteria3516
GAM42a (00174)23SClass Gammaproteobacteria, phylum Proteobacteria3516
SRB385 (00300)16SClass Deltaproteobacteria, phylum Proteobacteria3516
SRB385Db (00301)16SClass Deltaproteobacteria, phylum Proteobacteria3516
HGC69a (00182)23SPhylum Actinobacteria2516
GNSB941 (00718)16SPhylum Chloroflexi3516
CFX1223 (00719)16SPhylum Chloroflexi3516
SPIRO1400 (01004)16SSubgroup of family Spirochaetaceae2016
TM7-905 (00600)16SCandidate phylum TM72016
LGC354A (00195)16SPhylum Firmicutes3516
LGC354B (00196)16SPhylum Firmicutes3516
LGC354C (00197)16SPhylum Firmicutes3516
RUM83116SRumen clones in family Ruminococcaceae, phylum Firmicutes35This study
RAL143616SRuminococcus albus-related clones, phylum Firmicutes20This study
RFL15516SRuminococcus flavefaciens-related clones, phylum Firmicutes45This study
LAC43516SClones in family Lachnospiraceae, phylum Firmicutes35This study
BFI82616SButyrivibrio fibrisolvens-related clones, phylum Firmicutes35This study
BAC108016SClones in order Bacteroidales, phylum Bacteroidetes20This study
Fibr225 (00005)16SFibrobacter succinogenes-related clones, phylum Fibrobacteres20c16
ARCH915 (00027)16SDomain Archaea2016
Open in a separate windowaThe numbers in parentheses after the probe names represent the probe accession numbers in probeBase (16).bFA, formamide concentration used in the FISH buffer.cThe optimum formamide concentration for the probe was determined in this study.The optimal formamide concentrations (OFC) of the new probes used in FISH were assessed in different ways. Probes RUM831 and BAC1080 were assessed by using pure cultures of Ruminococcus and Prevotella strains with zero and one mismatch (Fig. (Fig.1)1) to the probes. The OFC of probes LAC435 and BFI826 were assessed using Clone-FISH (21) with zero and one mismatch 16S rRNA clone (Fig. (Fig.1)1) by following the procedure described previously (9, 10). The highest formamide concentration (tested in 5% stepwise increases) at which a clear fluorescent signal was observed with the reference bacterium or competent cells with zero mismatches after FISH probing, but not with bacteria or competent cells with one mismatch, was selected. The OFC of probes FIB225 (designed by Stahl et al. [23]), RFL155, and RAL1436 were assessed using only pure cultures of F. succinogenes, R. flavefaciens, and R. albus, respectively, all having perfect matches to each probe (Fig. (Fig.1).1). The highest formamide concentration (tested in 5% stepwise increases) at which a clear fluorescent signal was observed with the reference bacterium after FISH probing was selected. These probes were employed with other available probes (Table (Table2)2) chosen from probeBase (16) based on the alignment and classification of the 16S rRNA gene sequences retrieved from rumen communities.Open in a separate windowFIG. 1.Alignments of the probe sequences and their target sites and sequences of corresponding sites in reference bacteria or clones. The probe names in parentheses after the abbreviated names are according to Oligonucleotide Probe Database nomenclature (2). Only the nucleotides that are different from target sequences are shown. E, empty space; R., Ruminococcus; P., Prevotella; F., Fibrobacter.The digest samples from the top, bottom, and middle of the rumen were collected through a cannula, thoroughly mixed, and fractioned as liquid fraction (LiqF) and solid fraction (SolF). On-site, about 100 ml was transferred to a heavy-wall 250-ml beaker and squeezed using a Bodum coffee maker plunger (Bodum Inc., Triengen, Switzerland). The extruded liquid samples (containing the planktonic cells) were fixed in ethanol and paraformaldehyde (PFA) for FISH probing (3). The remaining liquid was discarded, and the squeezed particulate samples (used to collect particulate-attached cells) were washed with 100 ml phosphate buffer (5.23 g/liter K2HPO4, 2.27 g/liter KH2PO4, 3.00 g/liter NaHCO3, and 20 ml/liter 2.5% cysteine HCl) by stirring gently with a spatula, followed by squeezing again and decanting. Washed particulate samples (5 g) were then fixed for FISH as described above.After fixation, the particulate samples plus the fixation solution were transferred into a stomacher bag and “stomached” (Stomacher 400 Circulator, Seaward England) at 230 rpm for 6 min. Treated samples were then transferred into a clean 250-ml beaker and squeezed again. Microscopic examination of the squeezed residues after DAPI (4′,6-diamidino-2-phenylindole) staining (100 μl [0.003 mg/ml] for 10 min) showed only a few bacterial cells attached on the plant fibers, indicating that most bacterial cells had been “stomached” into the liquid (data not shown). To recover cells, filtrates were centrifuged (5,000 × g), and the cell pellet was washed three times with phosphate buffer before being used for FISH probing. On the day of sampling, each cow was sampled twice, at 1100 h and 1600 h. The liquid FISH samples obtained from the 3 cows fed with the same diet (at two different sampling times) were mixed, as were the particulate FISH samples, and used in qFISH analysis. FISH was carried out according to Amann (3). FISH was carried out on glass coverslips (24 by 60 mm) coated with gelatin (9). DAPI staining of biomass samples was carried out after FISH probing. FISH and DAPI images were captured with a Zeiss epifluorescence microscope (Zeiss PM III) equipped with a Canon 5D Mark II camera. Raw images captured randomly were transferred into gray TIF images and sharpened in Adobe Photoshop CS3. Cells stained with DAPI and hybridized to the probes were enumerated using the function provided in ImageJ (1). The percent compositions of these probe-defined groups (against all DAPI-stained cells in the same microscopic field) in the different fractions of rumen contents from cows fed different diets are presented in Table Table33.

TABLE 3.

Distribution and composition of FISH probe-defined groups in rumen microbial communities in cows fed with different diets
Probe-defined microbial groupComposition (mean value [%] ± SD)a
Hay-based diet
Hay and flaxseed diet
Silage-based diet
Silage and flaxseed diet
LiqFSolFLiqFSolFLiqFSolFLiqFSolF
BAC10809.6 ± 1.330.1 ± 0.0219.2 ± 3.714.2 ± 0.7214.2 ± 3.1118.8 ± 3.8814.4 ± 2.8916.7 ± 4.33
ALF9680.2 ± 0.020.2 ± 0.020.2 ± 0.030.2 ± 0.040.7 ± 0.141.5 ± 0.410.1 ± 0.010.1 ± 0.01
BET42a000.6 ± 0.011.2 ± 0.270.1 ± 0.01<0.10.4 ± 0.060.2 ± 0.04
GAM42a3.2 ± 0.534.4 ± 0.574.2 ± 0.764.5 ± 0.672.0 ± 0.321.2 ± 0.238.2 ± 1.235.3 ± 0.95
SRBmix5.8 ± 0.8811.6 ± 2.439.0 ± 1.5210.1 ± 2.5628.3 ± 4.4323.3 ± 4.547.7 ± 0.7813.2 ± 2.22
CHLmix1.7 ± 0.2700.5 ± 0.010 ± 00.2 ± 0.020.4 ± 0.070.1 ± 0.010.1 ± 0.02
SPIRO14000.5 ± 0.091.9 ± 0.321.7 ± 0.332.0 ± 0.211.4 ± 0.311.9 ± 0.330.4 ± 0.030.4 ± 0.07
TM7-9050.6 ± 0.080.8 ± 0.070.5 ± 0.010.1 ± 0.031.5 ± 0.230.2 ± 0.020.6 ± 0.020.3 ± 0.08
HGC69a1.3 ± 0.282.1 ± 0.310.3 ± 0.060.3 ± 0.050.4 ± 0.030.1 ± 0.020.5 ± 0.090.2 ± 0.02
RUM8315.5 ± 0.135.7 ± 0.895.8 ± 0.738.9 ± 1.3218.0 ± 4.1323.8 ± 3.115.6 ± 1.147.4 ± 1.32
RAL14360.4 ± 0.060.3 ± 0.030.2 ± 0.060.2 ± 0.030.3 ± 0.050.6 ± 0.090.7 ± 0.130.6 ± 0.12
RFL1550.7 ± 0.110.2 ± 0.030.3 ± 0.070.7 ± 0.190.1 ± 0.010.8 ± 0.110.5 ± 0.061.2 ± 0.34
LAC43525.5 ± 3.9810.0 ± 1.519.6 ± 1.3111.7 ± 1.6712.6 ± 2.5620.2 ± 3.239.3 ± 1.5116.1 ± 3.31
BFI8260.3 ± 0.060.4 ± 0.050.4 ± 0.060.7 ± 0.120.5 ± 0.050.3 ± 0.082.4 ± 0.370.2 ± 0.02
Fibr225000.2 ± 0.040.1 ± 0.020.8 ± 0.140.7 ± 0.140.4 ± 0.110.1 ± 0.04
ARCH9150.3 ± 0.080.2 ± 0.070.6 ± 0.010.3 ± 0.070.6 ± 0.090.1 ± 0.020.4 ± 0.050.4 ± 0.06
Total hybridizedb54.13752.443.780.991.64860.7
Otherc45.96347.656.319.18.45239.3
Open in a separate windowaThe two numbers represent the mean value (%) and the standard deviation of individual probe-defined microbial groups in a specified rumen digest fraction, which were calculated based on 3 mean values, each consisting of 20 enumerations.bThe numbers represent the sum of percentages of all individual probe-defined microbial groups in a specified rumen digest fraction. The percentages obtained with FISH probes RAL1436, RFL155, and BFI826 were not counted in the sum because the bacterial cells hybridizing with the former two probes also hybridized with RUM831, and the bacterial cells hybridizing with the last probe also hybridized with probe LAC435.cThe numbers represent the percentages of microorganisms which were not identified by FISH in a specified rumen digest fraction.We provided quantitative data by using qFISH to show that Bacteroidetes, Firmicutes, and Proteobacteria were abundant in both the LiqF and the SolF, constituting 31.8 to 87.3% of the total cell numbers. These FISH data add weight to the view that Firmicutes and Bacteroidetes might be dominant in rumens, as suggested previously from their high ratios retrieved from 16S rRNA clone libraries (e.g., see references 12, 26, and 27). However, information emerging from 16S rRNA gene clone library data cannot be used to reach conclusions on the quantitative composition of the rumen bacterial community. Bacteria may have 1 to 14 copies of rRNA genes, and several biases are known to be associated with their PCR amplification (8).These 3 dominant bacterial groups have been identified at a high-resolution level. They belong mainly to the order Bacteroidales (0.1 to 19.2%), hybridizing with probe BAC1080 (Fig. (Fig.22 A); the families Lachnospiraceae (9.3 to 25.5%) and Ruminococcaceae (5.5 to 23.8%), hybridizing with LAC435 (Fig. (Fig.2E)2E) and RUM831 (Fig. (Fig.2D),2D), respectively; and the classes Deltaproteobacteria (5.8 to 28.3%) and Gammaproteobacteria (1.2 to 8.2%), hybridizing with SRBmix (equal moles of SRB385 and SRB385Db) (Fig. (Fig.2C)2C) and GAM42a (Fig. (Fig.2B),2B), respectively. All were more abundant in the microbial communities in the rumens of cows fed diets containing silage (75.2 to 87.3%) than in those in the rumens of cows fed diets containing hay (31.8 to 49.5%). These results show how diets containing different forages (hay or silage) may influence the distribution of the microbial populations, which is in line with data by Tajima et al. (25). We also found in this study that the addition of flaxseed (to inhibit methane emission) reduced their abundance in the rumens of cows fed silage-based diets (to 45.2 to 58.7%) but did not change markedly their abundance in the rumens of cows fed hay-based diets (31.8 to 49.5%), suggesting that adding flaxseed to these diets also affected rumen microbial community composition, although the extent of its influence reflected the forage used, being more profound with a silage-based diet than when hay was used.Open in a separate windowFIG. 2.Images of digest samples from the rumens of cows fed hay- or silage-based diets with and without flaxseed after color combination. Images from probes are labeled in red, and those from DAPI staining are in green. The yellow (combination of red and green), including those partly colored cells in panels A to F, hybridized with probes BAC1080, GAM42a, SRBmix, RUM831, LAC435, and ARCH915, respectively. A few cells (arrows) hybridizing with SRBmix (C) were not stained by DAPI. Bars, 10 μm.We also present evidence here to suggest that Proteobacteria are common members of the microbial community, with sulfur-reducing bacteria (SRB) belonging to Deltaproteobacteria in particular being readily detected (up to 28% of the total cells) in both the LiqF and the SolF of rumen contents from cows fed the four different diets examined here. SRB have seldom been retrieved in clone libraries obtained from rumen samples. Lin et al. (15) have estimated SRB abundance in the rumen using DNA hybridization and concluded that they were of minor importance (0.7 to 0.8% of the total rRNA). Our estimates are much higher than those for every diet regime examined, possibly reflecting the coverage of the probes used in the two different studies. The probe mixture SRBmix used here targets most members of the Deltaproteobacteria, while those of Lin et al. (15) covered mainly members of the Desulfobacteraceae, Desulfovibrionaceae, and Desulfobulbaceae. We also recognized that the probe mixture SRBmix perfectly matched with the 16S rRNA genes of some bacteria other than SRB in Deltaproteobacteria. The possibility of overestimation of SRB cannot be ruled out. Interestingly, our data suggest that Gammaproteobacteria were abundant in some of the rumen communities we examined by FISH, comprising 1.2 to 8.2% of total cells.The other unexpected finding was that the fibrolytic bacteria and archaeal methanogens accounted for only a minor fraction of the communities. Of the three characterized fibrolytic bacterial species, F. succinogenes was not detected in the rumen digesta from cattle fed the hay-based diet but was present in the remainder of the diets. In contrast, R. albus and R. flavefaciens were present in both the LiqF and the SolF of the rumen digesta from cows fed all four diets. Although the importance of these bacteria within the rumen microbial community cannot be denied, these three populations accounted for only 0.7 to 2.1% of the total microbial cells. This numerical range compares well with that determined previously for F. succinogenes (0.1 to 6.9% of total rRNA) (4, 23) and Ruminococcus spp. (1.5 to 2.9% of total rRNA) (11), considering that different animals and diets were used in those studies and that different specificities of the probes and different detection methods were used. However, this is much lower than the 9% (of total rRNA) detected by Michalet-Doreau et al. (19) in their work. The abundance of fibrolytic B. fibrisolvens-related species was also low, being present at <1% in all fractions, except in the LiqF in cows fed the mixture of silage and flaxseed, where they contributed 2.4% of total cells.Methanogens hybridized to ARCH915 (Fig. (Fig.2F)2F) were present (0.1 to 0.6%) in all rumen samples examined by FISH, which is close to or within the range (0.3 to 3.3%) estimated in other studies (15, 22). Interestingly, no marked difference in abundance of the methanogens could be seen between the samples from the rumens of cows fed diets with flaxseed and those from the rumens of cows fed diets without flaxseed, although it has been reported (7) that the addition of fatty acids could decrease methane production in the rumen. This may be due to the presence of methanogens with different activities in different rumen samples or the inability of probe ARCH915 to hybridize to all methanogens in the rumen samples examined here.Bacteria belonging to Chloroflexi, TM7, Spirochetes, and Actinobacteria hybridizing with CHLmix, TM7-905, SPRO1400, and HGC69a, respectively, accounted for only a minor fraction of the total cell numbers observed. In most cases, their abundances in each fraction did not change markedly with diet, always being present in small numbers (0 to 1%), suggesting that they have a minor role there. This conclusion, however, has to be confirmed since many (8.4 to 63.0%, depending on diet) of the bacteria could not be identified in the rumens of cows fed with all diets except the silage-based diet (Table (Table33).FISH with the probes designed in this study failed to identify all of the bacterial cells. This is because the probes do not target all rumen 16S rRNA gene sequences and/or the true extent of rumen biodiversity has not been revealed from cloning analyses. This indicates that our current understanding of the quantitative composition of the rumen microbial community is far from complete. Moreover, no physiological data were generated in this study to suggest what the role(s) of most of the dominant populations (except the SRB hybridized with probe SRBmix) identified by FISH might be, meaning that it is still not possible to link their abundance to their in situ function. Furthermore, each FISH-probed population probably includes bacteria with different phenotypes. Clearly, much needs to be done before the structure and function of the rumen microbial community are fully understood.FISH is a useful tool in the investigation of microbial composition in complex ecosystems (3). However, FISH probes targeting rumen bacterial populations are limited. By comparison with other culture-independent methods, e.g., quantitative PCR, FISH has several advantages (8). In particular, in combination with histochemical staining methods (20) and microautoradiography (MAR-FISH) (13), the in situ ecophysiology of a targeted population can be determined under specified electron acceptor conditions. These techniques may provide important clues as to the functional role of microbial populations within complex communities, like that of the rumen. The possession of the FISH probes described in this paper could allow such studies to be undertaken in herbivore rumens.  相似文献   

20.
Hierarchical Oligonucleotide Primer Extension as a Time- and Cost-Effective Approach for Quantitative Determination of Bifidobacterium spp. in Infant Feces     
Pei-Ying Hong  Gaik Chin Yap  Bee Wah Lee  Kaw Yan Chua  Wen-Tso Liu 《Applied and environmental microbiology》2009,75(8):2573-2576
The Bifidobacterium spp. present in 10 infant fecal samples (4 from infants with eczema and 6 from healthy infants) were quantified with both hierarchical oligonucleotide primer extension (HOPE) and fluorescence in situ hybridization-flow cytometry. The relative abundances of Bifidobacterium longum and B. catenulatum with respect to the total bifidobacteria had a poor correlation (ρ, <0.600; P value, >0.208), presumably due to differences in primer specificity and the level of hybridization stringency of both methods. In contrast, the relative abundances of organisms of the genus Bifidobacterium against the total amplified 16S rRNA genes and those of B. adolescentis, B. bifidum, and B. breve against the genus Bifidobacterium exhibited a good statistical correlation (ρ, >0.783; P value, <0.066). This good comparability supports HOPE as a method to achieve high-throughput quantitative determination of bacterial targets in a time- and cost-effective manner.The “microflora hygiene” hypothesis states that a lack of exposure to pathogens or certain commensal bacteria in early life may predispose some individuals to allergic disorders (14). However, inconsistent findings on the abundance of health-associated microbes have prevented precise conclusions as to their role in modulating host health. For example, by performing fluorescence in situ hybridization (FISH) on infant feces, Bifidobacterium spp. were found in high abundance in healthy infants (11). In contrast, certain species, like Bifidobacterium pseudocatenulatum, may be more commonly detected in infants with eczema (3). Therefore, to facilitate our understanding of microbial composition and its correlation to human health, it is essential to use a rapid and high-throughput molecular method to determine the abundances of bacterial targets in a large sample size (16). Although FISH-flow cytometry (FISH-FC) is routinely used to quantify the abundances of bacterial targets in feces (9, 11, 17), it does not suffice as a high-throughput method due to the limited range of spectrally distinct fluorophores that are available in the UV spectrum (10, 13). There is a need to develop a high-throughput technique which can complement the existing molecular methods to rapidly evaluate the relative abundance of bacterial targets.A molecular method termed hierarchical oligonucleotide primer extension (HOPE) was developed to rapidly determine the relative abundances of bacterial 16S rRNA genes among total PCR-amplified 16S rRNA genes (19). HOPE uses primers of different lengths that were designed to target bacteria at different phylogenetic levels. The primers anneal to complementary regions of the targeted bacteria and extend with a fluorophore-labeled nucleotide when the bacterial target is present. The extended primers can be differentiated on a genetic analyzer based on primer length and fluorophore color. The relative abundance of the bacterial target against a higher-level primer can then be quantified by calculating the ratio of the peak area of the extended primer with that of a higher-level primer. A subsequent study demonstrated that HOPE can be used for rapid and specific determination of Bacteroides spp. present in feces and wastewaters at different taxonomical levels (5). It also has the versatility to be expanded to include other bacterial groups. This can potentially facilitate the identification and quantification of bacterial populations that modulate the health of an individual at different temporal intervals.This study aimed to demonstrate HOPE as a time- and cost-effective method to quantify the abundances of Bifidobacterium spp. in 10 infant fecal samples (4 from infants with eczema and 6 from healthy infants) that were collected at 1, 3, and 12 months of age. The abundances of the Bifidobacterium spp. as determined, respectively, by HOPE and FISH-FC were also compared to validate the use of HOPE as a quantitative method.To obtain the total PCR-amplified 16S rRNA genes, genomic DNA of the fecal microbiota was extracted based on a previously described protocol (12) prior to 20 cycles of PCR amplification (modified 11F forward primer 5′-GTT YGA TYC TGG CTC AG-3′ and 1492R reverse primer 5′-GGY TAC CTT GTT ACG ACT T-3′) (6, 7). The amplicons were purified, and the concentrations were diluted to 10 ng/μl. For HOPE, a total of 12 primers specifically targeting six Bifidobacterium spp. at different taxonomic levels were designed based on a previously described protocol (5). The specificity of the designed primers was verified in silico against entries in RDP II (2), and the sensitivity of the primers was determined as described previously (19). FISH-FC was performed on the same set of fecal samples based on the protocol described by Lay et al. (9). Table Table11 lists the HOPE primers and FISH probes used in this study. A nonparametric Spearson ranked correlation analysis (Minitab) was performed on the abundances of Bifidobacterium spp. as quantified by FISH-FC and HOPE, respectively.

TABLE 1.

HOPE primers and FISH probes included in this study
Primer or probeTarget(s) (no. of RDP II hits)aSequence (5′-3′)Poly(A) tail length (nt)Type of ddNTPb addedHOPE reaction tube no.Reference
HOPE primers
    Bia183_speB. adolescentis (62)AAG GAC ATG CAT CCA ACT0G2This study
    Biang183_speB. angulatum (3)TTC CCA GAC CAC CAT GCG ATG GAC T0G2This study
    Bibif183_speB. bifidum (11)GAA TCT TTC CCA CAA TCA CAT GCG AT6C2This study
    Bbreve1264_speB. breve (11)CAG GGA TCC GCT CCA GCT CGC A4C2This study
    Bicat181_speB. catenulatum, B. pseudocatenulatum (41)CCA TGC GAG GAG TCG GAG CA0T2This study
    Bil181_speB. longum (12)CAT GCG ATC AAC TGG AA5C1This study
    Bifgp1120_cluB. breve, some B. longum isolates (19)ACA ATC CGC TGG CAA CAC G15G1, 2This study
    Bifgp1250_cluB. dentium, B. bifidum (14)GTC GCC ATG TCG CAT CCC GC10T1, 2This study
    Bifgp442_cluB. adolescentis, B. ruminatium (75)CCG AAG GGC TTG CTC CCA G15T1, 2This study
    Bifgp272_cluB. angulatum, B. catenulatum, B. pseudocatenulatum (49)GCC GGC TAC CCG TCG TAG GCT C8G1, 2This study
    Bif660_genMost Bifidobacterium spp. (308)CCA CCG TTA CAC CGG GAA TTC CAG0T18c
    Eub338Ia_domMost Bacteria spp. (221136)GCT GCC TCC CGT AGG AG23T119
FISH probes
    Bado434B. adolescentis (79)GCT CCC AGT CAA AAG CG17
    Bang198B. angulatum (3)AAT CTT TCC CAG ACC ACC17
    Bbif186B. bifidum (13)CCA CAA TCA CAT GCG ATC ATG17
    Bbre198B. breve (28)AAA GGC TTT CCC AAC ACA CC17
    Bcat187B. catenulatum, B. pseudocatenulatum (40)ACA CCC CAT GCG AGG AGT17
    Blon1004B. longum (48), some Spirochaeta spp. (16)AGC CGT ATC TCT ACG ACC GT17
    Bif164Most Bifidobacterium spp. (293)CAT CCG GCA TTA CCA CCC8
    Eub338Most Bacteria spp. (220802)GCT GCC TCC CGT AGG AGT1
    Non338Non-Bacteria spp. (0)ACT CCT ACG GGA GGC AGC18
Open in a separate windowaDenotes that only good-quality 16S rRNA sequences of >1,200 bp were subjected to BLAST analysis to retrieve the number of perfectly matched hits in RDP II.bddNTP, dideoxynucleoside triphosphate.cModified from reference 8.The extended HOPE primers were detected in the genetic analyzer when target DNA templates made up more than 0.10% of the total genomic DNA. The lower detection sensitivity of the Bifidobacterium-targeting primers than those obtained in previous studies (5, 19) may be due to the high GC content of DNA templates. As Bifidobacterium spp. are predominant in infant feces (4, 16), the effect of the low primer sensitivities on subsequent findings could be negligible.Our findings agree with previous studies and suggested that the genus Bifidobacterium was predominant in the infants'' fecal microbiota (Fig. (Fig.1).1). Furthermore, it was observed that the abundances varied across individuals and with time (Fig. (Fig.1).1). In most individuals, the relative abundances of the genus Bifidobacterium against the total amplified 16S rRNA genes were also highest in the fecal samples that were collected at 1 and 3 months after birth (Fig. (Fig.1).1). On average, B. adolescentis was only detected by both HOPE and FISH-FC in the fecal microbiota that was collected 12 months after birth (Fig. (Fig.2).2). In contrast, the B. catenulatum group and B. bifidum were consistently detected at all sampling times and at relatively high abundances of up to 28.5% and 16.6% of the total bifidobacteria, respectively (Fig. (Fig.2).2). Furthermore, B. breve was detected in the fecal microbiota of infants with eczema at 1 and 3 months after birth and at relative abundances that ranged from 2.8 to 7.9% of the total bifidobacteria (Fig. (Fig.2).2). In contrast, a reverse trend was observed throughout the period in healthy infants (Fig. (Fig.2).2). However, the role of B. breve in atopic eczema cannot be conclusively determined from this study as other variables such as the mode of delivery and the dietary regimen were not investigated (15).Open in a separate windowFIG. 1.Relative abundances of bifidobacteria in fecal samples obtained from 10 infants at 1, 3, and 12 months after birth. Abundances were quantified by HOPE (A) and FISH-FC (B).Open in a separate windowFIG. 2.Relative abundances of Bifidobacterium spp. and total bifidobacteria. Abundances in samples from the infants in the respective health groups and time points were averaged and quantified by HOPE (○) and FISH-FC (▵).To determine the comparability of HOPE and FISH-FC, the relative abundances of Bifidobacterium spp. quantified by both methods were statistically analyzed by nonparametric Spearson correlation analysis. The relative abundances of B. longum and the B. catenulatum group against the genus Bifidobacterium did not show a significant correlation (P values = 0.208 and 0.623, respectively) (Table (Table2),2), and the discrepancy may be due to the different specificities of the HOPE primers and FISH-FC probes. Table Table11 showed that FISH-FC probe Blon1004 was designed to target B. longum at a fourfold higher coverage than the HOPE primer (Bil181) and would understandably result in a significant difference between the abundances detected. Although the HOPE primer and the FISH-FC probe that target the B. catenulatum group have similar specificities, the discrepancy in the abundances detected may be due to the difference between the hybridization stringencies of the two methods. In this study, fluorescently labeled probes for FISH-FC were hybridized to their complementary 16S rRNA genes at 35°C (9). The low hybridization temperature may have resulted in cross-hybridization with nontargets and therefore comparably higher abundances of the B. catenulatum group than those quantified by HOPE (Fig. (Fig.11).

TABLE 2.

Nonparametric correlation analysis of the relative abundances of Bifidobacterium spp. determined by HOPE and FISH-FC
BacteriaSpearson correlation (ρ)P valueCorrelation of abundances quantified by HOPE and FISH-FC
All Bifidobacterium spp.a0.8290.042Good at 90% confidence level
B. adolescentisb0.9200.009
B. breveb0.8570.029
B. bifidumb0.7830.066Fairly good at 85% confidence level
B. catenulatum groupb0.6000.208Not significant
B. longumb0.2570.623
Open in a separate windowaThe relative abundances of Bifidobacterium spp. against the total Bacteria spp. amplified were compared in this correlation analysis.bThe relative abundances of the individual Bifidobacterium sp. shown against the total amplified Bifidobacterium spp. were compared in this correlation analysis.Despite the poor correlation of the relative abundances of B. longum and the B. catenulatum group, a fairly good correlation, ranging from 0.783 to 0.920, was obtained for the relative abundances of the bifidobacteria with respect to the total bacteria and also for the relative abundances of individual species like B. adolescentis, B. bifidum, and B. breve against the genus Bifidobacterium (average P value = 0.04) (Table (Table22).FISH-FC and quantitative PCR are two molecular methods used to examine the Bifidobacterium spp. present in the fecal microbiota. Compared to FISH-FC, the entire HOPE procedure for the identification and quantification of Bifidobacterium spp. after primary DNA extraction and PCR amplification took less than 120 min (5, 19), which was significantly shorter than that required for FISH-FC. Furthermore, we demonstrate the use of inexpensive unlabeled oligonucleotide primers to achieve up to nine-plexing per reaction. Compared to quantitative PCR, which uses fluorescently labeled PCR assays like the TaqMan, HOPE would allow a relatively more cost-effective examination of up to 864 targets in a 96-well plate format.Furthermore, HOPE is highly adaptable and allows the total number of detectable bacterial targets to be easily increased simply by adding HOPE reactions or by adding a primer(s) to individual reactions. For example, although the HOPE primer targeting B. longum is highly specific, it did not achieve satisfactory coverage of the entire B. longum group. Primers that target B. dentium and B. infantis were also not included in this study. These species may constitute the large unidentified fraction of Bifidobacterium spp. that was not accounted for. Besides profiling for these known Bifidobacterium spp., the yet-to-be-cultured Bifidobacterium spp. can also be identified by the construction of 16S rRNA gene libraries and designed with new HOPE primers that target the unrepresented Bifidobacterium spp. The current list of primer assays can be easily expanded to include these new primers so as to provide more comprehensive coverage of the bifidobacterial population that is present in infant feces.In summary, this study has demonstrated the potential of HOPE as a time- and cost-effective detection method that can examine the relative abundances of bacterial targets at various taxonomic levels. It can be used to capture possible changes in the abundances of Bifidobacterium spp. and/or other bacterial targets present in infant feces. The abundances can then be correlated with clinical disorders such as allergic diseases, and the findings will eventually assist in the elucidation of the roles played by microorganisms in the mediation of immune responses.  相似文献   

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