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31.
Animal-to-Animal Variation in Fecal Microbial Diversity among Beef Cattle   总被引:1,自引:0,他引:1  
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.

TABLE 1.

Richness and diversity indices for 6 beef feedlot cattle
Library and animal (n)No. of OTUs observedSpecies richness (CI)a by:
Diversity (CI) by:
ChaoACEShannon''s indexSimpson''s index
97% DNA sequence similarity
    Animal 1 (2,485)198372 (294-515)329 (280-408)3.89 (3.83-3.95)0.0422
    Animal 2 (2,084)416600 (538-694)604 (552-675)5.40 (5.35-5.45)0.0066
    Animal 3 (1,710)6961,393 (1,224-1,615)1,418 (1,327-1,523)6.13 (6.08-6.18)0.0027
    Animal 4 (1,512)294526 (439-665)483 (425-566)4.71 (4.63-4.78)0.0237
    Animal 5 (2,059)314612 (495-805)488 (434-566)4.93 (4.88-4.99)0.0126
    Animal 6 (1,321)174320 (252-447)289 (244-361)4.18 (4.11-4.25)0.0286
85% DNA sequence similarity
    Animal 1 (2,485)4861 (51-99)62 (52-90)2.64 (2.59-2.68)0.1056
    Animal 2 (2,084)77107 (87-165)102 (87-139)3.38 (3.34-3.43)0.0505
    Animal 3 (1,710)130153 (139-186)151 (140-174)4.07 (4.02-4.12)0.0254
    Animal 4 (1,512)6675 (68-98)77 (70-96)2.71 (2.64-2.78)0.0931
    Animal 5 (2,059)6980 (72-109)84 (75-110)3.31 (3.26-3.36)0.0545
    Animal 6 (1,321)5465 (57-102)61 (56-76)2.90 (2.83-2.97)0.0939
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   
32.
33.
The impact of proximity to a beef cattle feedlot on Escherichia coli O157:H7 contamination of leafy greens was examined. In each of 2 years, leafy greens were planted in nine plots located 60, 120, and 180 m from a cattle feedlot (3 plots at each distance). Leafy greens (270) and feedlot manure samples (100) were collected six different times from June to September in each year. Both E. coli O157:H7 and total E. coli bacteria were recovered from leafy greens at all plot distances. E. coli O157:H7 was recovered from 3.5% of leafy green samples per plot at 60 m, which was higher (P < 0.05) than the 1.8% of positive samples per plot at 180 m, indicating a decrease in contamination as distance from the feedlot was increased. Although E. coli O157:H7 was not recovered from air samples at any distance, total E. coli was recovered from air samples at the feedlot edge and all plot distances, indicating that airborne transport of the pathogen can occur. Results suggest that risk for airborne transport of E. coli O157:H7 from cattle production is increased when cattle pen surfaces are very dry and when this situation is combined with cattle management or cattle behaviors that generate airborne dust. Current leafy green field distance guidelines of 120 m (400 feet) may not be adequate to limit the transmission of E. coli O157:H7 to produce crops planted near concentrated animal feeding operations. Additional research is needed to determine safe set-back distances between cattle feedlots and crop production that will reduce fresh produce contamination.  相似文献   
34.
目的筛选与Rap GAP相互作用的蛋白质,为进一步研究人源Rap1GAP介导的信号转导通路、揭示其与肿瘤的关系提供实验依据。方法选用与Rap1GAP同源的来自美丽线虫的Rap GAP作为饵蛋白,以来源于美丽线虫的c DNA文库作为靶蛋白,应用p PC97、p PC86组成的酵母双杂交系统筛选c DNA文库中与Rap GAP相互作用的蛋白质。结果通过营养缺陷平板(-LTH)筛选出63个拟似阳性菌落。经过Lac Z鉴定,19个菌落为阳性,其中7个为强阳性。提取来自19个酵母菌落中的重组DNA,经PCR扩增,12个菌落出现阳性结果。将该19个重组DNA分别电转化入DH5α细菌,涂板培养后,每板挑取4~10个克隆,通过Sal I和Not I双酶切鉴定进行阳性克隆筛选。将阳性克隆的重组DNA进行序列测定。测序结果与Gen Bank比较,其中4个克隆的DNA片段为Y39b6a基因片段、2个为Rap GAP、1个为苯丙氨酸-4-羟化酶、1个为细胞色素C氧化酶,还有1个DNA片段编码美丽线虫特有的小分子蛋白的基因片段,其余11个DNA片段不编码已知蛋白质。结论初步筛选出与Rap GAP相互作用的蛋白质,特别是其中有2个克隆为Rap GAP,提示Rap GAP可能以二聚体的方式存在。  相似文献   
35.

Background

It is now recognized that enzymatic or chemical side-reactions can convert normal metabolites to useless or toxic ones and that a suite of enzymes exists to mitigate such metabolite damage. Examples are the reactive imine/enamine intermediates produced by threonine dehydratase, which damage the pyridoxal 5''-phosphate cofactor of various enzymes causing inactivation. This damage is pre-empted by RidA proteins, which hydrolyze the imines before they do harm. RidA proteins belong to the YjgF/YER057c/UK114 family (here renamed the Rid family). Most other members of this diverse and ubiquitous family lack defined functions.

Results

Phylogenetic analysis divided the Rid family into a widely distributed, apparently archetypal RidA subfamily and seven other subfamilies (Rid1 to Rid7) that are largely confined to bacteria and often co-occur in the same organism with RidA and each other. The Rid1 to Rid3 subfamilies, but not the Rid4 to Rid7 subfamilies, have a conserved arginine residue that, in RidA proteins, is essential for imine-hydrolyzing activity. Analysis of the chromosomal context of bacterial RidA genes revealed clustering with genes for threonine dehydratase and other pyridoxal 5''-phosphate-dependent enzymes, which fits with the known RidA imine hydrolase activity. Clustering was also evident between Rid family genes and genes specifying FAD-dependent amine oxidases or enzymes of carbamoyl phosphate metabolism. Biochemical assays showed that Salmonella enterica RidA and Rid2, but not Rid7, can hydrolyze imines generated by amino acid oxidase. Genetic tests indicated that carbamoyl phosphate overproduction is toxic to S. enterica cells lacking RidA, and metabolomic profiling of Rid knockout strains showed ten-fold accumulation of the carbamoyl phosphate-related metabolite dihydroorotate.

Conclusions

Like the archetypal RidA subfamily, the Rid2, and probably the Rid1 and Rid3 subfamilies, have imine-hydrolyzing activity and can pre-empt damage from imines formed by amine oxidases as well as by pyridoxal 5''-phosphate enzymes. The RidA subfamily has an additional damage pre-emption role in carbamoyl phosphate metabolism that has yet to be biochemically defined. Finally, the Rid4 to Rid7 subfamilies appear not to hydrolyze imines and thus remain mysterious.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1584-3) contains supplementary material, which is available to authorized users.  相似文献   
36.
The rapid repolarization during phase 1 of the action potential of sheep cardiac purkinje fibers has been attributed to a time- and voltage-dependent chloride current. In part, this conclusion was based on experiments that showed a substantial slowing of phase 1 when larger, presumably impermeant, anions were substituted for chloride in tyrode’s solution. We have re- examined the electrical effects of low-chloride solutions. We recorded action potentials of sheep cardiac purkinje fibers in normal tyrode’s solution and in low-chloride solutions made by substituting sodium propionate, acetylglycinate, methylsulfate, or methanesulfonate for the NaCl of Tyrode’s solution. Total calcium was adjusted to keep calcium ion activity of test solutions equal to that of control solutions. Propionate gave qualitatively variable results in preliminary experiments; it was not tested further. Low-chloride solutions made with the other anions gave much more consistent results: phase 1 and the notch that often occurs between phases 1 and 2 were usually unaffected, and the action potential duration usually increased. The only apparent change in the resting potential was a transient 3-6 mV depolarization when low-chloride solution was first admitted to the chamber, and a symmetrical transient hyperpolarization when chloride was returned to normal. If a time- and voltage-dependent chloride current exists in sheep cardiac purkinje fibers, our results suggest that it plays little role in generating phase 1 of the action potential.  相似文献   
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The genus Borrelia includes the causative agents of Lyme disease and relapsing fever. An unusual feature of these bacteria is a genome that includes linear DNA molecules with covalently closed hairpin ends referred to as telomeres. We have investigated the mechanism by which the hairpin telomeres are processed during replication. A synthetic 140 bp sequence having the predicted structure of a replicated telomere was shown to function as a viable substrate for telomere resolution in vivo, and was sufficient to convert a circular replicon to a linear form. Our results suggest that the final step in the replication of linear Borrelia replicons is a site-specific DNA breakage and reunion event to regenerate covalently closed hairpin ends. The telomere substrate described here will be valuable both for in vivo manipulation of linear DNA in Borrelia and for in vitro studies to identify and characterize the telomere resolvase.  相似文献   
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