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1.
After separation of gangliosides by thin-layer chromatography, femtomolar quantities of GM1 were detected by incubating the plate with native choleratoxin, followed by anticholeratoxin and species-specific labeled antiserum. Only stable reagents were involved when antiserum labeled with horseradish peroxidase was used. Native choleratoxin rather than iodinelabeled toxin ensured good reproducibility of the method. 相似文献
2.
Codon usage in the vertebrate hemoglobins and its implications 总被引:2,自引:0,他引:2
A study of codon usage in vertebrate hemoglobins revealed an evolutionary
trend toward elevated numbers of CpG codon boundary pairs in mammalian
hemoglobin alpha genes. Selection for CpG codon boundaries countering the
generally observed CpG suppression is strongly suggested by these data.
These observations parallel recently published experimental results that
indicate that constitutive expression of the human alpha-globin gene
appears to be determined by regulatory information encoded within the
structural gene. The possibility is raised that, in the absence of
selection, CpG decay can be used to date the evolutionary origin of a
mammalian alpha pseudogene from its active alpha gene.
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3.
Evolution of crystallins: expression of lens-specific proteins in the blind mammals mole (Talpa europaea) and mole rat (Spalax ehrenbergi) 总被引:3,自引:0,他引:3
Quax-Jeuken Y; Bruisten S; Bloemendal H; de Jong WW; Nevo E 《Molecular biology and evolution》1985,2(4):279-288
The mole (Talpa europaea; Insectivora) and the mole rat (Spalax ehrenbergi;
Rodentia) both have degenerated eyes as a convergent adaptation to
subterranean life. The rudimentary eye lenses of these blind mammals no
longer function in a visual process. The crystallin genes, which display a
lens-specific expression pattern, were studied in these blind mammals and
in related species with normal eyes by hybridizing their genomic DNAs with
probes obtained from cDNA clones for alpha A-, alpha B-, and beta
Bp-crystallins from calf and gamma 3- crystallin from the rat. For all
crystallin genes examined, the hybridization signals of mole and mole rat
genomic DNA were comparable, respectively, with those of shrew and of rat
and mouse, normal-vision representatives of the orders Insectivora and
Rodentia. The expression of the crystallins at the protein level was tested
by using antiserum specific for alpha-crystallin in immunofluorescence
reactions on lens sections of mole and mole rat eyes and by using antisera
against the beta- and gamma-crystallins on sections of the mole eye. All
antisera gave positive fluorescence reactions exclusively with lens tissue
of these blind mammals, indicating that the crystallins are still normally
expressed despite the fact that these lenses have had no function in a
visual process in these mammals for at least many million years. These
findings apparently imply that some unknown selective advantage has
conserved the crystallin genes and their expression after the loss of
normal function of the lenses.
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4.
In Drosophila pseudoobscura, the amylase (Amy) multigene family is
contained within a series of inversions, or gene arrangements, on the third
chromosome. The Standard (ST), Santa Cruz (SC), and Tree Line (TL)
inversions are central to the phylogeny of arrangements, and have clusters
of other arrangements derived from them. The gene arrangements belonging to
each of these three clusters have a characteristic number of Amy genes,
ranging from three in ST to two in SC to one in TL. This distribution
pattern can reflect a history of either duplications or deletions, although
the data available in the past did not permit a decision between these
alternatives. We provide unambiguous evidence that three Amy genes were
present before the divergence of the ST, SC, and TL arrangements. Thus, the
current status of the Amy multigene family is the result of deletions in
the TL and SC arrangements, which created three new pseudogenes: TL
Amy2-psi, TL Amy3-psi, and SC Amy3- psi. Analysis of pseudogene sequences
revealed that, in the SC and ST arrangements, pseudogene evolution has been
retarded, most likely due to the homogenization effect of gene conversion.
Finally, by determining the original copy number, we have reconstructed the
evolutionary history of the Amy multigene family and linked it with the
evolution of the central gene arrangements.
相似文献
5.
The alpha-amylase (Amy) multigene family in Drosophila pseudoobscura is
located on the third chromosome, which is polymorphic for more than 40
inverted gene arrangements. The number of copies in this family ranges from
one to three, depending on the arrangement in question. A previous study of
the three Amy genes from the Standard (ST) arrangement suggested either
that duplicated copies (Amy2 and Amy3) are functionally constrained or that
they are undergoing gene conversion with Amy1. In order to elucidate
further the pattern of molecular evolution in this family, we cloned and
sequenced four additional Amy genes, two from the Santa Cruz (SC) and two
from the Chiricahua (CH) gene arrangement. Of the two alternatives, only
the hypothesis of gene conversion is supported by the sequence analysis.
The homogenization effect of gene conversion has been strongest in SC,
whose copies differ by only two nucleotides, less noticeable in ST, and
negligible in the CH. Furthermore, the action of gene conversion is
apparently localized, occurring only in the coding region. Interestingly,
these results concur with the findings of other workers for the duplicated
Amy genes in the Drosophila melanogaster group. Thus, the occurrence of
gene conversion in the Amy multigene family seems to be a common feature in
the Drosophila species studied so far.
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6.
Bono JL Keen JE Miller LC Fox JM Chitko-McKown CG Heaton MP Laegreid WW 《Applied and environmental microbiology》2004,70(3):1855-1857
A commercially available real-time, rapid PCR test was evaluated for its ability to detect Escherichia coli O157. Both the sensitivity and specificity of the assay were 99% for isolates in pure culture. The assay detected 1 CFU of E. coli O157:H7 g(-1) in artificially inoculated bovine feces following enrichment. 相似文献
7.
Michael?P.?HeatonEmail author Kreg?A.?Leymaster Brad?A.?Freking Deedra?A.?Hawk Timothy?P. L.?Smith John?W.?Keele Warren?M.?Snelling James?M.?Fox Carol?G.?Chitko-McKown William?W.?Laegreid 《Mammalian genome》2003,14(11):765-777
Prions are proteins that play a central role in transmissible spongiform encephalopathies in a variety of mammals. Among the most notable prion disorders in ungulates are scrapie in sheep, bovine spongiform encephalopathy in cattle, and chronic wasting disease in deer. Single nucleotide polymorphisms in the sheep prion gene (PRNP) have been correlated with susceptibility to natural scrapie in some populations. Similar correlations have not been reported in cattle or deer; however, characterization of PRNP nucleotide diversity in those species is incomplete. This report describes nucleotide sequence variation and frequency estimates for the PRNP locus within diverse groups of U.S. sheep, U.S. beef cattle, and free-ranging deer (Odocoileus
virginianus and O. hemionus from Wyoming). DNA segments corresponding to the complete prion coding sequence and a 596-bp portion of the PRNP promoter region were amplified and sequenced from DNA panels with 90 sheep, 96 cattle, and 94 deer. Each panel was designed to contain the most diverse germplasm available from their respective populations to facilitate polymorphism detection. Sequence comparisons identified a total of 86 polymorphisms. Previously unreported polymorphisms were identified in sheep (9), cattle (13), and deer (32). The number of individuals sampled within each population was sufficient to detect more than 95% of all alleles present at a frequency greater than 0.02. The estimation of PRNP allele and genotype frequencies within these diverse groups of sheep, cattle, and deer provides a framework for designing accurate genotype assays for use in genetic epidemiology, allele management, and disease control. 相似文献
8.
Lisa M. Durso Gregory P. Harhay Timothy P. L. Smith James L. Bono Todd Z. DeSantis Dayna M. Harhay Gary L. Andersen James E. Keen William W. Laegreid Michael L. Clawson 《Applied and environmental microbiology》2010,76(14):4858-4862
The intestinal microbiota of beef cattle are important for animal health, food safety, and methane emissions. This full-length sequencing survey of 11,171 16S rRNA genes reveals animal-to-animal variation in communities that cannot be attributed to breed, gender, diet, age, or weather. Beef communities differ from those of dairy. Core bovine taxa are identified.The gastrointestinal tracts (GIT) of beef cattle are colonized by microorganisms that profoundly impact animal physiology, nutrition, health, and productivity (5). The GIT microbiota potentially impact food safety via pathogen shedding (13) by interacting with organisms such as Salmonella and competing for resources in the GIT. Cattle intestinal microbiota also play an important role in methane emissions, with U.S. beef cattle alone contributing an estimated 3.87 million metric tons of methane into the environment each year, both from rumen and large-intestine fermentations (7). Although the bovine fecal microbiota have been well characterized using culture-based methods, these techniques are necessarily limited to characterizing bacteria that can be grown in the laboratory. Culture-independent methods can reveal community members that are recalcitrant to culture. Only a handful of deep-sequencing studies have been done using culture-independent 16S rRNA-based methods (1, 11, 12, 14), all with dairy cattle, which have a fundamentally different diet and metabolism from beef cattle. Despite the potential contributions of the beef cattle GIT microbiota to animal health, food safety, and global warming, these communities remain poorly characterized. With the advent of pyrosequencing technology, researchers now have the tools to characterize these important communities. Pyrosequencing will allow rapid characterization of large-sample data sets (1). However, the taxonomic information generated by rapid sequencing is approximate by necessity (9), and full-length 16S-rRNA sequencing remains the “gold standard” method. Accordingly, we have characterized fecal bacteria from six feedlot cattle by full-length capillary sequence analysis of 11,171 16S rRNA gene clones (Fig. (Fig.11).Open in a separate windowFIG. 1.Bacterial diversity of six feedlot beef cattle. Gray bars represent the percentages of all 16S sequences that were assigned to each taxonomy. Colored dots represent the percentages of 16S sequences from each library that were assigned to each taxonomic group. Asterisks indicate unclassified members of the named taxon. Panel A shows the data for the first 99% of all the sequences. Panel B shows the data for the remaining 1% of sequences. Note differences in scales for panels A and B.Rectal grab fecal samples (n = 6) were collected according to institutional animal care guidelines. All animals were female cross-bred MARCIII beef heifers, 6 to 8 months of age, 214 to 241 kg, housed in the same feedlot pen for 2 months prior to fecal collection, and fed the same typical feedlot beef production growing rations consisting of 61.6% corn silage (41.3% dry matter), 15.2% alfalfa hay, 20.9% corn, and 2.3% liquid supplement.Total fecal DNA was isolated from homogenized samples using MoBio UltraClean fecal kit (Carlsbad, CA). PCR was performed using 27F and 1392R primers (11). Amplification consisted of 25 cycles, with an annealing temperature of 55°C. Amplicons from three reactions per sample were pooled (8), cloned using the Invitrogen TOPO TA cloning kit (Carlsbad, CA), and sequenced bidirectionally with M13 primers using an ABI 3700 sequencer (17). Low-quality and chimeric sequences (6) were excluded from further analysis. Distance matrices were compiled from ClustalW alignments (18) in PHYLIP (4). Pairwise estimates of shared richness were calculated using EstimateS, version 8.2 (R. K. Colwell; http://purl.oclc.org/estimates). DOTUR (16) was used to identify operational taxonomic units (OTUs) and to generate rarefaction curves (Fig. (Fig.2),2), richness and evenness estimates, and Shannon''s and Simpson''s diversity indices (Table (Table1).1). A 97% similarity cutoff and an 85% similarity cutoff for estimating OTUs were used to approximate species and class-level designations (15). Taxonomies were assigned to one member of each OTU using the RDP “classifier” tool (19), and the RDP taxonomic information was used for Fig. Fig.11 and and3.3. Common bovine taxa were identified based on inclusion in all three U.S. culture-independent studies (this study and references 1 and 11).Open in a separate windowFIG. 2.Rarefaction curves for six feedlot beef cattle. OTUs were assigned at the 85% DNA sequence similarity level. For comparison purposes, all six curves were truncated after 1,321 sequences.Open in a separate windowFIG. 3.Phylum-level distribution of bacterial sequences from six beef feedlot cattle. Asterisks indicate unclassified members of the named taxon.
Open in a separate windowaCI, confidence interval.The GIT community of beef feedlot cattle characterized in this study was found to share many taxa with the bovine GIT community described for dairy cattle (1, 11, 14), although the relative abundances of the major bacterial groups differed considerably. The fecal microbiota of beef cattle were dominated by members of the Firmicutes, with 62.8% of the OTUs belonging to this taxonomic group (Fig. (Fig.3).3). Bacteroidetes (29.5% of the OTUs) and Proteobacteria (4.4% of the OTUs) were also represented in feces (Fig. (Fig.3).3). A total of seven phyla were found in our six animals.Total estimated species richness values (Chao) for each of the six animals were 372, 600, 1,393, 526, 612, and 320 (Table (Table1).1). These cattle richness numbers are higher than those observed for three human subjects (164, 332, and 297) (2). The mean of Chao pairwise estimates of shared richness between any two of the six cattle fecal libraries was 230.Our findings, in addition to those from pyrosequencing studies (1), identify a core set of bovine GIT bacterial taxa, including the Bacteroidetes Prevotella and Bacteroides; the Firmicutes Faecalibacterium, Ruminococcus, Roseburia, and Clostridium; and the proteobacterium Succinovibrio (Fig. (Fig.1).1). These genera are consistently identified in bovine feces and likely compose part of the bovine resident microbiota. Although the potential exists for culture-independent methods to reveal minority microbial community members, 16S rRNA gene sequencing in dairy (1, 11) and beef cattle supports the list of core taxa identified using culture-based methods.Comparisons between our data set and recent studies done with dairy cattle (1, 11, 12) suggest that although beef and dairy cattle share many of the same major bacterial groups, the relative abundances of these groups in beef and dairy cattle may differ, and there may be differences between the two groups in the compositions of minority community members. The most common genus in beef cattle from our study was Prevotella, representing 24% of the total number of sequences evaluated. In comparison, Dowd et al. (1) found that Prevotella spp. represented only 5.5% of the total 16S genes sequenced from 20 dairy cattle, and Prevotella was not listed in the top 10 most frequently occurring OTUs in either of the studies from McGarvey et al. (11, 12). Likewise, Clostridium represented only 1.5% of the total beef sequences but 19% of the dairy pyrosequences (1). There were a number of bacterial sequences present in the beef cattle sequences but not reported in the dairy sequences, including Arthrobacter, Asteroleplasma, Bifidobacterium, Collinsella, Delftia, Eggerthella, Lactobacillus, Mitsuokella, Olsenella, and Propionibacterium (1, 11), although a number of these genera have been cultured from dairy animals in the past. It must be noted that all of these sequencing studies examined only a small number of animals, and each method has limitations which affect interpretation of the results. The full-length sequencing performed as part of this beef cattle study and two dairy studies (11, 12) relies on a PCR step which can potentially affect the relative numbers of each taxon observed due to PCR bias, while the pyrosequeincg method used in the 20-animal dairy study suffers from artifacts that potentially affect taxonomic assignment and richness estimates due to short read lengths and potential biases in evenness (how many of each group) due to primer and template mismatches (3). Nonetheless, these studies indicate that there may be fundamental differences between the gastrointestinal communities of beef and dairy cattle, they provide a comprehensive examination of the communities present in the specific animals tested, and they serve to provide important baseline information for further studies examining various factors which can impact cattle gastrointestinal communities.The taxonomic information generated by deep sequencing of beef cattle feces revealed considerable animal-to-animal variation in the operational taxonomic unit (OTU) composition of the individual libraries (Fig. (Fig.1).1). The OTU designation facilitates an analysis of the community data without forcing the assignment of sequences into an incomplete and imperfect bacterial taxonomic system. It relies on DNA sequence similarity to assign sequences to a particular OTU defined by the level of DNA sequence similarity. In total, 1,906 OTUs (97% OTU designation) were identified in the six libraries. Of these, only 24 OTUs (1.2%) (comprising 1,253 [11.2%] of sequences) were present in all six libraries, while 1,348 OTUs (69%) were found only in individual libraries. Of these, 1,064 OTUs (77%) were unique, represented by a solitary clone (range of 3% to 29% of the total clones from each individual animal). These data hint at considerable animal-to-animal variation in bacterial community structure at the species level that cannot be readily attributed to breed, gender, age, macroecologic factors such as weather conditions, or diet, given that the animals in this study were controlled for these variables, and support the conclusions of Manter et al. (10) that pooling samples can obscure rare phylotypes.Our results from beef cattle suggest that there may be differences in the bacterial community members present in the GIT of each individual animal that cannot be attributed to diet, breed, gender, age, or macroecologic factors such as weather and suggest the need for the high-resolution community sequencing of much larger numbers of animals before “core” minority community members can be identified. Considering the limited nature of the community surveys to date and all of the genetic, management, geographic, and temporal factors that can contribute to the composition of GIT microbiota, much work remains before we are able to understand and predict the community composition of any individual animal. 相似文献
TABLE 1.
Richness and diversity indices for 6 beef feedlot cattleLibrary and animal (n) | No. of OTUs observed | Species richness (CI)a by: | Diversity (CI) by: | ||
---|---|---|---|---|---|
Chao | ACE | Shannon''s index | Simpson''s index | ||
97% DNA sequence similarity | |||||
Animal 1 (2,485) | 198 | 372 (294-515) | 329 (280-408) | 3.89 (3.83-3.95) | 0.0422 |
Animal 2 (2,084) | 416 | 600 (538-694) | 604 (552-675) | 5.40 (5.35-5.45) | 0.0066 |
Animal 3 (1,710) | 696 | 1,393 (1,224-1,615) | 1,418 (1,327-1,523) | 6.13 (6.08-6.18) | 0.0027 |
Animal 4 (1,512) | 294 | 526 (439-665) | 483 (425-566) | 4.71 (4.63-4.78) | 0.0237 |
Animal 5 (2,059) | 314 | 612 (495-805) | 488 (434-566) | 4.93 (4.88-4.99) | 0.0126 |
Animal 6 (1,321) | 174 | 320 (252-447) | 289 (244-361) | 4.18 (4.11-4.25) | 0.0286 |
85% DNA sequence similarity | |||||
Animal 1 (2,485) | 48 | 61 (51-99) | 62 (52-90) | 2.64 (2.59-2.68) | 0.1056 |
Animal 2 (2,084) | 77 | 107 (87-165) | 102 (87-139) | 3.38 (3.34-3.43) | 0.0505 |
Animal 3 (1,710) | 130 | 153 (139-186) | 151 (140-174) | 4.07 (4.02-4.12) | 0.0254 |
Animal 4 (1,512) | 66 | 75 (68-98) | 77 (70-96) | 2.71 (2.64-2.78) | 0.0931 |
Animal 5 (2,059) | 69 | 80 (72-109) | 84 (75-110) | 3.31 (3.26-3.36) | 0.0545 |
Animal 6 (1,321) | 54 | 65 (57-102) | 61 (56-76) | 2.90 (2.83-2.97) | 0.0939 |
9.
10.
Ingo Aldag Ulrike Bockau Jan Rossdorf Sven Laarmann Willem Raaben Lutz Herrmann Thomas Weide Marcus WW Hartmann 《BMC biotechnology》2011,11(1):11