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Characterization of four lectin-like receptor kinases expressed in roots of Medicago truncatula. Structure, location, regulation of expression, and potential role in the symbiosis with Sinorhizobium meliloti 总被引:1,自引:0,他引:1
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Navarro-Gochicoa MT Camut S Timmers AC Niebel A Herve C Boutet E Bono JJ Imberty A Cullimore JV 《Plant physiology》2003,133(4):1893-1910
To study the role of LecRK (lectin-like receptor kinase) genes in the legumerhizobia symbiosis, we have characterized the four Medicago truncatula Gaernt. LecRK genes that are most highly expressed in roots. Three of these genes, MtLecRK7;1, MtLecRK7;2, and MtLecRK7;3, encode proteins most closely related to the Class A LecRKs of Arabidopsis, whereas the protein encoded by the fourth gene, MtLecRK1;1, is most similar to a Class B Arabidopsis LecRK. All four genes show a strongly enhanced root expression, and detailed studies on MtLecRK1;1 and MtLecRK7;2 revealed that the levels of their mRNAs are increased by nitrogen starvation and transiently repressed after either rhizobial inoculation or addition of lipochitooligosaccharidic Nod factors. Studies of the MtLecRK1;1 and MtLecRK7;2 proteins, using green fluorescent protein fusions in transgenic M. truncatula roots, revealed that they are located in the plasma membrane and that their central transmembrane-spanning helix is required for correct sorting. Moreover, their lectin-like domains appear to be highly glycosylated. Of the four proteins, only MtLecRK1;1 shows a high conservation of key residues implicated in monosaccharide binding, and molecular modeling revealed that this protein may be capable of interacting with Nod factors. However, no increase in Nod factor binding was found in roots overexpressing a fusion in which the kinase domain of this protein had been replaced with green fluorescent protein. Roots expressing this fusion protein however showed an increase in nodule number, suggesting that expression of MtLecRK1;1 influences nodulation. The potential role of LecRKs in the legume-rhizobia symbiosis is discussed. 相似文献
23.
Goedhart J Bono JJ Bisseling T Gadella TW 《Molecular plant-microbe interactions : MPMI》2003,16(10):884-892
Nod factors are signaling molecules secreted by Rhizobium bacteria. These lipo-chitooligosaccharides (LCOs) are required for symbiosis with legumes and can elicit specific responses at subnanomolar concentrations on a compatible host. How plants perceive LCOs is unclear. In this study, using fluorescent Nod factor analogs, we investigated whether sulfated and nonsulfated Nod factors were bound and perceived differently by Medicago truncatula and Vicia sativa root hairs. The bioactivity of three novel sulfated fluorescent LCOs was tested in a root hair deformation assay on M. truncatula, showing bioactivity down to 0.1 to 1 nM. Fluorescence microscopy of plasmolyzed M. truncatula root hairs shows that sulfated fluorescent Nod factors accumulate in the cell wall of root hairs, whereas they are absent from the plasma membrane when applied at 10 nM. When the fluorescent Nod factor distribution in medium surrounding a root was studied, a sharp decrease in fluorescence close to the root hairs was observed, visualizing the remarkable capacity of root hairs to absorb Nod factors from the medium. Fluorescence correlation microscopy was used to study in detail the mobilities of sulfated and nonsulfated fluorescent Nod factors which are biologically active on M. truncatula and V. sativa, respectively. Remarkably, no difference between sulfated and nonsulfated Nod factors was observed: both hardly diffuse and strongly accumulate in root hair cell walls of both M. truncatula and V. sativa. The implications for the mode of Nod factor perception are discussed. 相似文献
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Yoshimi Tokuzawa Ken Yagi Yzumi Yamashita Yutaka Nakachi Itoshi Nikaido Hidemasa Bono Yuichi Ninomiya Yukiko Kanesaki-Yatsuka Masumi Akita Hiromi Motegi Shigeharu Wakana Tetsuo Noda Fred Sablitzky Shigeki Arai Riki Kurokawa Toru Fukuda Takenobu Katagiri Christian Sch?nbach Tatsuo Suda Yosuke Mizuno Yasushi Okazaki 《PLoS genetics》2010,6(7)
27.
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 |
28.
Besser TE Shaikh N Holt NJ Tarr PI Konkel ME Malik-Kale P Walsh CW Whittam TS Bono JL 《Applied and environmental microbiology》2007,73(3):671-679
Escherichia coli O157:H7, a zoonotic human pathogen for which domestic cattle are a reservoir host, produces a Shiga toxin(s) (Stx) encoded by bacteriophages. Chromosomal insertion sites of these bacteriophages define three principal genotypes (clusters 1 to 3) among clinical isolates of E. coli O157:H7. Stx-encoding bacteriophage insertion site genotypes of 282 clinical and 80 bovine isolates were evaluated. A total of 268 (95.0%) of the clinical isolates, but only 41 (51.3%) of the bovine isolates, belonged to cluster 1, 2, or 3 (P < 0.001). Thirteen additional genotypes were identified in isolates from both cattle and humans (four genotypes), from only cattle (seven genotypes), or from only humans (two genotypes). Two other markers previously associated with isolates from cattle or with clinical isolates showed similar associations with genotype groups within bovine isolates; the tir allele sp-1 and the Q933W allele were under- and overrepresented, respectively, among cluster 1 to 3 genotypes. Stx-encoding bacteriophage insertion site typing demonstrated that there is broad genetic diversity of E. coli O157:H7 in the bovine reservoir and that numerous genotypes are significantly underrepresented among clinical isolates, consistent with the possibility that there is reduced virulence or transmissibility to humans of some bovine E. coli O157:H7 genotypes. 相似文献
29.
Bignetti E Franchi D Gorreri A Fusari A Del Bono G Ubaldi A Aiello G 《Alternatives to laboratory animals : ATLA》2007,35(4):387-395
A major issue concerning the protocols of heavy metal cytotoxicity tests with PC12 cells was the hypothesis that serum in the culture medium might sequester the metal, thus altering the results obtained. However, serum withdrawal impairs the viability of PC12 cells themselves, thus impeding cytotoxicity testing in the absence of serum. In this study, we repeatedly selected undifferentiated, totally non-adherent PC12 cells in Petri dishes. Surprisingly, we discovered that these cells could survive and proliferate in serum-free medium. Moreover, features such as NGF-responsiveness, resazurin reduction potential, doubling rate, protein content, and basal caspase-3 enzyme activity, were equivalent to those exhibited by standard PC12 cultures. Further experiments aimed at fully characterising these serum-independent PC12 cells are in progress. These cells enabled cytotoxicity experiments to be conducted with manganese, both in serum-supplemented and in serum-deprived medium. The results demonstrated that serum removal decreased the LC50 of manganese from 250microM to 32microM, without affecting the internalisation of the metal. The data exclude an early competitive effect of serum on metal internalisation; rather, they suggest a late protective mechanism mediated by serum against the cytotoxic effect of the already-internalised metal. 相似文献
30.
Elaine D. Berry James E. Wells James L. Bono Bryan L. Woodbury Norasak Kalchayanand Keri N. Norman Trevor V. Suslow Gabriela López-Velasco Patricia D. Millner 《Applied and environmental microbiology》2015,81(3):1101-1110
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