首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献,搜索用时 78 毫秒
1.
The biological, serological, and genomic characterization of a paramyxovirus recently isolated from rockhopper penguins (Eudyptes chrysocome) suggested that this virus represented a new avian paramyxovirus (APMV) group, APMV10. This penguin virus resembled other APMVs by electron microscopy; however, its viral hemagglutination (HA) activity was not inhibited by antisera against any of the nine defined APMV serotypes. In addition, antiserum generated against this penguin virus did not inhibit the HA of representative viruses of the other APMV serotypes. Sequence data produced using random priming methods revealed a genomic structure typical of APMV. Phylogenetic evaluation of coding regions revealed that amino acid sequences of all six proteins were most closely related to APMV2 and APMV8. The calculation of evolutionary distances among proteins and distances at the nucleotide level confirmed that APMV2, APMV8, and the penguin virus all were sufficiently divergent from each other to be considered different serotypes. We propose that this isolate, named APMV10/penguin/Falkland Islands/324/2007, be the prototype virus for APMV10. Because of the known problems associated with serology, such as antiserum cross-reactivity and one-way immunogenicity, in addition to the reliance on the immune response to a single protein, the hemagglutinin-neuraminidase, as the sole base for viral classification, we suggest the need for new classification guidelines that incorporate genome sequence comparisons.Viruses from the Paramyxoviridae family have caused disease in humans and animals for centuries. Over the last 40 years, many paramyxoviruses isolated from animals and people have been newly described (16, 17, 22, 29, 31, 32, 36, 42, 44, 46, 49, 58, 59, 62-64). Viruses from this family are pleomorphic, enveloped, single-stranded, nonsegmented, negative-sense RNA viruses that demonstrate serological cross-reactivity with other paramyxoviruses related to them (30, 46). The subfamily Paramyxovirinae is divided into five genera: Respirovirus, Morbillivirus, Rubulavirus, Henipavirus, and Avulavirus (30). The Avulavirus genus contains nine distinct avian paramyxovirus (APMV) serotypes (Table (Table1),1), and information on the discovery of each has been reported elsewhere (4, 6, 7, 9, 12, 34, 41, 50, 51, 60, 68).

TABLE 1.

Characteristics of prototype viruses APMV1 to APMV9 and the penguin virus
StrainHostDiseaseDistributionFusion cleavagecGI accession no.
APMV1/Newcastle disease virus>250 speciesHigh mortalityWorldwideGRRQKRF45511218
InapparentWorldwideGGRQGRLa11545722
APMV2/Chicken/CA/Yucaipa/1956Turkey, chickens, psittacines, rails, passerinesDecrease in egg production and respiratory diseaseWorldwideDKPASRF169144527
APMV3/Turkey/WI/1968TurkeyMild respiratory disease and moderate egg decreaseWorldwidePRPSGRLa209484147
APMV3/Parakeet/Netherlands/449/1975Psittacines, passerines, flamingosNeurological, enteric, and respiratory diseaseWorldwideARPRGRLa171472314
APMV4/Duck/Hong Kong/D3/1975Duck, geese, chickensNone knownWorldwideVDIQPRF210076708
APMV5/Budgerigar/Japan/Kunitachi/1974Budgerigars, lorikeetsHigh mortality, enteric diseaseJapan, United Kingdom, AustraliaGKRKKRFa290563909
APMV6/Duck/Hong Kong/199/1977Ducks, geese, turkeysMild respiratory disease and increased mortality in turkeysWorldwidePAPEPRLb15081567
APMV7/Dove/TN/4/1975Pigeons, doves, turkeysMild respiratory disease in turkeysUnited States, England, JapanTLPSSRF224979458
APMV8/Goose/DE/1053/1976Ducks, geeseNone knownUnited States, JapanTYPQTRLa226343050
APMV9/Duck/NY/22/1978DucksNone knownWorldwideRIREGRIa217068693
APMV10/Penguin/Falkland Islands/324/2007Rockhopper penguinsNone KnownFalkland IslandsDKPSQRIa300432141
Open in a separate windowaRequires the addition of an exogenous protease.bProtease requirement depends on the isolate examined.cPutative.Six of these serotypes were classified in the latter half of the 1970s, when the most reliable assay available to classify paramyxoviruses was the hemagglutination inhibition (HI) assay (61). However, there are multiple problems associated with the use of serology, including the inability to classify some APMVs by comparing them to the sera of the nine defined APMVs alone (2, 8). In addition, one-way antigenicity and cross-reactivity between different serotypes have been documented for many years (4, 5, 14, 25, 29, 33, 34, 41, 51, 52, 60). The ability of APMVs, like other viruses, to show antigenic drift as it evolves over time (37, 43, 54) and the wide use and availability of precise molecular methods, such as PCR and genome sequencing, demonstrate the need for a more practical classification system.The genetic diversity of APMVs is still largely unexplored, as hundreds of avian species have never been surveyed for the presence of viruses that do not cause significant signs of disease or are not economically important. The emergence of H5N1 highly pathogenic avian influenza (HPAI) virus as the cause of the largest outbreak of a virulent virus in poultry in the past 100 years has spurred the development of surveillance programs to better understand the ecology of avian influenza (AI) viruses in aquatic birds around the globe, and in some instances it has provided opportunities for observing other viruses in wild bird populations (15, 53). In 2007, as part of a seabird health surveillance program in the Falkland Islands (Islas Malvinas), oral and cloacal swabs and serum were collected from rockhopper penguins (Eudyptes chrysocome) and environmental/fecal swab pools were collected from other seabirds.While AI virus has not yet been isolated from penguins in the sub-Antarctic and Antarctic areas, there have been two reports of serum antibodies positive to H7 and H10 from the Adélie species (11, 40). Rare isolations of APMV1, both virulent (45) and of low virulence (8), have been reported from Antarctic penguins. Sera positive for APMV1 and AMPV2 have also been reported (21, 24, 38, 40, 53). Since 1981, paramyxoviruses have been isolated from king penguins (Aptenodytes patagonicus), royal penguins (Eudyptes schlegeli), and Adélie penguins (Pygoscelis adeliae) from Antarctica and little blue penguins (Eudyptula minor) from Australia that cannot be identified as belonging to APMV1 to -9 and have not yet been classified (8, 11, 38-40). The morphology, biological and genomic characteristics, and antigenic relatedness of an APMV recently isolated from multiple penguin colonies on the Falkland Islands are reported here. Evidence that the virus belongs to a new serotype (APMV10) and a demonstration of the advantages of a whole genome system of analysis based on random sequencing followed by comparison of genetic distances are presented. Only after all APMVs are reported and classified will epidemiological information be known as to how the viruses are moving and spreading as the birds travel and interact with other avian species.  相似文献   

2.
Predator-prey relationships among prokaryotes have received little attention but are likely to be important determinants of the composition, structure, and dynamics of microbial communities. Many species of the soil-dwelling myxobacteria are predators of other microbes, but their predation range is poorly characterized. To better understand the predatory capabilities of myxobacteria in nature, we analyzed the predation performance of numerous Myxococcus isolates across 12 diverse species of bacteria. All predator isolates could utilize most potential prey species to effectively fuel colony expansion, although one species hindered predator swarming relative to a control treatment with no growth substrate. Predator strains varied significantly in their relative performance across prey types, but most variation in predatory performance was determined by prey type, with Gram-negative prey species supporting more Myxococcus growth than Gram-positive species. There was evidence for specialized predator performance in some predator-prey combinations. Such specialization may reduce resource competition among sympatric strains in natural habitats. The broad prey range of the Myxococcus genus coupled with its ubiquity in the soil suggests that myxobacteria are likely to have very important ecological and evolutionary effects on many species of soil prokaryotes.Predation plays a major role in shaping both the ecology and evolution of biological communities. The population and evolutionary dynamics of predators and their prey are often tightly coupled and can greatly influence the dynamics of other organisms as well (1). Predation has been invoked as a major cause of diversity in ecosystems (11, 12). For example, predators may mediate coexistence between superior and inferior competitors (2, 13), and differential trajectories of predator-prey coevolution can lead to divergence between separate populations (70).Predation has been investigated extensively in higher organisms but relatively little among prokaryotes. Predation between prokaryotes is one of the most ancient forms of predation (27), and it has been proposed that this process may have been the origin of eukaryotic cells (16). Prokaryotes are key players in primary biomass production (44) and global nutrient cycling (22), and predation of some prokaryotes by others is likely to significantly affect these processes. Most studies of predatory prokaryotes have focused on Bdellovibrionaceae species (e.g., see references 51, 55, and 67). These small deltaproteobacteria prey on other Gram-negative cells, using flagella to swim rapidly until they collide with a prey cell. After collision, the predator cells then enter the periplasmic space of the prey cell, consume the host cell from within, elongate, and divide into new cells that are released upon host cell lysis (41). Although often described as predatory, the Bdellovibrionaceae may also be considered to be parasitic, as they typically depend (apart from host-independent strains that have been observed [60]) on the infection and death of their host for their reproduction (47).In this study, we examined predation among the myxobacteria, which are also deltaproteobacteria but constitute a monophyletic clade divergent from the Bdellovibrionaceae (17). Myxobacteria are found in most terrestrial soils and in many aquatic environments as well (17, 53, 74). Many myxobacteria, including the model species Myxococcus xanthus, exhibit several complex social traits, including fruiting body formation and spore formation (14, 18, 34, 62, 71), cooperative swarming with two motility systems (64, 87), and group (or “wolf pack”) predation on both bacteria and fungi (4, 5, 8, 9, 15, 50). Using representatives of the genus Myxococcus, we tested for both intra- and interspecific variation in myxobacterial predatory performance across a broad range of prey types. Moreover, we examined whether prey vary substantially in the degree to which they support predatory growth by the myxobacteria and whether patterns of variation in predator performance are constant or variable across prey environments. The latter outcome may reflect adaptive specialization and help to maintain diversity in natural populations (57, 59).Although closely related to the Bdellovibrionaceae (both are deltaproteobacteria), myxobacteria employ a highly divergent mode of predation. Myxobacteria use gliding motility (64) to search the soil matrix for prey and produce a wide range of antibiotics and lytic compounds that kill and decompose prey cells and break down complex polymers, thereby releasing substrates for growth (66). Myxobacterial predation is cooperative both in its “searching” component (6, 31, 82; for details on cooperative swarming, see reference 64) and in its “handling” component (10, 29, 31, 32), in which secreted enzymes turn prey cells into consumable growth substrates (56, 83). There is evidence that M. xanthus employs chemotaxis-like genes in its attack on prey cells (5) and that predation is stimulated by close contact with prey cells (48).Recent studies have revealed great genetic and phenotypic diversity within natural populations of M. xanthus, on both global (79) and local (down to centimeter) scales (78). Phenotypic diversity includes variation in social compatibility (24, 81), the density and nutrient thresholds triggering development (33, 38), developmental timing (38), motility rates and patterns (80), and secondary metabolite production (40). Although natural populations are spatially structured and both genetic diversity and population differentiation decrease with spatial scale (79), substantial genetic diversity is present even among centimeter-scale isolates (78). No study has yet systematically investigated quantitative natural variation in myxobacterial predation phenotypes across a large number of predator genotypes.Given the previous discovery of large variation in all examined phenotypes, even among genetically extremely similar strains, we anticipated extensive predatory variation as well. Using a phylogenetically broad range of prey, we compared and contrasted the predatory performance of 16 natural M. xanthus isolates, sampled from global to local scales, as well as the commonly studied laboratory reference strain DK1622 and representatives of three additional Myxococcus species: M. flavescens (86), M. macrosporus (42), and M. virescens (63) (Table (Table1).1). In particular, we measured myxobacterial swarm expansion rates on prey lawns spread on buffered agar (31, 50) and on control plates with no nutrients or with prehydrolyzed growth substrate.

TABLE 1.

List of myxobacteria used, with geographical origin
Organism abbreviation used in textSpeciesStrainGeographic originReference(s)
A9Myxococcus xanthusA9Tübingen, Germany78
A23Myxococcus xanthusA23Tübingen, Germany78
A30Myxococcus xanthusA30Tübingen, Germany78
A41Myxococcus xanthusA41Tübingen, Germany78
A46Myxococcus xanthusA46Tübingen, Germany78
A47Myxococcus xanthusA47Tübingen, Germany78
A75Myxococcus xanthusA75Tübingen, Germany78
A85Myxococcus xanthusA85Tübingen, Germany78
TVMyxococcus xanthusTvärminneTvärminne, Finland79
PAKMyxococcus xanthusPaklenicaPaklenica, Croatia79
MADMyxococcus xanthusMadeira 1Madeira, Portugal79
WARMyxococcus xanthusWarwick 1Warwick, UK79
TORMyxococcus xanthusToronto 1Toronto, Ontario, Canada79
SUL2Myxococcus xanthusSulawesi 2Sulawesi, Indonesia79
KALMyxococcus xanthusKalalauKalalau, HI79
DAVMyxococcus xanthusDavis 1ADavis, CA79
GJV1Myxococcus xanthusGJV 1Unknown35, 72
MXFL1Myxococcus flavescensMx fl1Unknown65
MXV2Myxococcus virescensMx v2Unknown65
CCM8Myxococcus macrosporusCc m8Unknown65
Open in a separate window  相似文献   

3.
4.
A 30-probe assay was developed for simultaneous classification of Listeria monocytogenes isolates by lineage (I to IV), major serogroup (4b, 1/2b, 1/2a, and 1/2c), and epidemic clone (EC) type (ECI, ECIa, ECII, and ECIII). The assay was designed to facilitate rapid strain characterization and the integration of subtype data into risk-based inspection programs.Listeria monocytogenes is a facultative intracellular pathogen that can cause serious invasive illness (listeriosis) in humans and other animals. L. monocytogenes is responsible for over 25% of food-borne-disease-related deaths attributable to known pathogens and is a leading cause of food recalls due to microbial adulteration (12, 21). However, not all L. monocytogenes subtypes contribute equally to human illness, and substantial differences in the ecologies and virulence attributes of different L. monocytogenes subtypes have been identified (9, 13, 14, 23, 24, 33, 35, 36). Among the four major evolutionary lineages of L. monocytogenes, only lineages I and II are commonly isolated from contaminated food and human listeriosis patients (19, 27, 29, 33). Lineage I strains are overrepresented among human listeriosis isolates, particularly those associated with epidemic outbreaks, whereas lineage II strains are overrepresented in foods and the environment (13, 14, 24). Lineage III strains account for approximately 1% of human listeriosis cases but are common among animal listeriosis isolates and appear to be a host-adapted group that is poorly adapted to food-processing environments (6, 34-36). The ecological and virulence attributes of lineage IV are poorly understood, as this lineage is rare and was only recently described based on a small number of strains (19, 26, 29, 33).L. monocytogenes is differentiated into 13 serotypes; however, four major serogroups (4b, 1/2b, 1/2a, and 1/2c) from within lineages I and II account for more than 98% of human and food isolates (16, 31). Serogroups refer to evolutionary complexes typified by a predominant serotype but which include very rare serotypes that represent minor evolutionary variants (7, 9, 33). Phylogenetic analyses have indicated that rare serotypes may have evolved recently, or even multiple times, from one of the major serotypes (9), and numerous molecular methods fail to discriminate minor serotypes as independent groups (1, 4, 7, 9, 18, 22, 33, 38, 39). Serotyping is one of the most common methods for L. monocytogenes subtyping, and serogroup classifications are a useful component of strain characterization because ecotype divisions appear largely congruent with serogroup distinctions (16, 34). Serogroup 4b strains are of particular public health concern because contamination with these strains appears to increase the probability that a ready-to-eat (RTE) food will be implicated in listeriosis (16, 28). Serogroup 4b strains account for approximately 40% of sporadic listeriosis and also are responsible for the majority of listeriosis outbreaks despite being relatively rare contaminants of food products (9, 13, 17, 30, 34). In addition, serogroup 4b strains are associated with more severe clinical presentations and higher mortality rates than other serogroups (11, 16, 20, 31, 34). Serogroups 1/2a and 1/2b are overrepresented among food isolates but also contribute significantly to human listeriosis, whereas serogroup 1/2c rarely causes human illness and may pose a lower risk of listeriosis for humans (16). Serogroup-specific differences in association with human listeriosis are consistent with the prevalence of virulence-attenuating mutations in inlA within these serogroups (32, 34); however, a number of additional factors likely contribute to these differences.Four previously described epidemic clones (ECs; ECI, ECIa, ECII, and ECIII) of L. monocytogenes have been implicated in numerous listeriosis outbreaks and have contributed significantly to sporadic illness (15, 34). ECI, ECIa, and ECII are distinct groups within serogroup 4b that were each responsible for repeated outbreaks of listeriosis in the United States and Europe. ECIII is a lineage II clone of serotype 1/2a that persisted in the same processing facility for more than a decade prior to causing a multistate outbreak linked to contaminated turkey (15, 25). While there has been speculation that epidemic clones possess unique adaptations that explain their frequent involvement in listeriosis outbreaks (9, 34, 37), it is not clear that epidemic clones are more virulent than other strains with the same serotype. However, contamination of RTE food with EC strains would be cause for increased concern due to the previous involvement of these clones in major outbreaks of listeriosis (16).As a result of the L. monocytogenes subtype-specific differences in ecology, virulence, and association with human illness, molecular subtyping technologies have the potential to inform assessments of relative risk and to improve risk-based inspection programs. The objective of the present study was to develop a single assay for rapid and accurate classification of L. monocytogenes isolates by lineage, major serogroup, and epidemic clone in order to facilitate strain characterization and the integration of subtype data into inspection programs that are based on assessment of relative risk.A database of more than 5.3 Mb of comparative DNA sequences from 238 L. monocytogenes isolates (9, 33-35) was scanned for single nucleotide polymorphisms that could be used to differentiate lineages, major serogroups, and epidemic clones via a targeted multilocus genotyping (TMLGT) approach. The acronym TMLGT is used to distinguish this approach from previously published multilocus genotyping (MLGT) assays that were lineage specific and designed for haplotype discrimination (9, 33). To provide for simultaneous interrogation of the selected polymorphisms via TMLGT, six genomic regions (Table (Table1)1) were coamplified in a multiplex PCR. While the previous MLGT assays were based on three lineage-specific multiplexes and required prior identification of lineage identity, TMLGT was designed to target variation across all of the lineages simultaneously and is based on a unique set of amplicons. PCR was performed in 50-μl volumes with 1× High Fidelity PCR buffer (Invitrogen Life Technologies), 2 mM MgSO4, 100 μM deoxynucleoside triphosphate (dNTP), 300 nM primer, 1.5 U Platinum Taq high-fidelity DNA polymerase (Invitrogen Life Technologies), and 100 ng of genomic DNA. PCR consisted of an initial denaturation of 90 s at 96°C, followed by 40 cycles of 30 s at 94°C, 30 s at 50°C, and 90 s at 68°C. Amplification products were purified using Montage PCR cleanup filter plates (Millipore) and served as a template for allele-specific primer extension (ASPE) reactions utilizing subtype-specific probes.

TABLE 1.

Primers used in multiplex amplification for the TMLGT assay
AmpliconPositionaGene(s)PrimerSequence (5′-3′)b
INLa455381-456505inlAinl2-a1GTCCTTGATAGTCTACTG
inl2-a2ACCAAATTAGTAATCTAGCAC
INLb457726-458752inlBinl-f1dGAATTRTTTAGYCAAGAATGT
inlb-rCTACCGGRACTTTATAGTAYG
LMO325116-326096lmo0298-lmo0300lmo-a1AAGGCTTACAAGATGGCT
lmo1a-1rAAATAATAYGTGATACCGAC
VGCa205366-206622plcA, hlyplca-fCTCATCGTATCRTGTGTACC
hly-rTCTGGAAGGTCKTGTAGGTTC
VGCb208447-209465mplra_mpl-fGTGGAYAGAACTCATAAAGG
ra_mpl-rACTCCCTCCTYGTGATASGCT
VGCc209728-211239actAvgc1a-2fTTCMATRCCAGCAGAACG
vgc1a-2rGCAGACCTAATAGCAATGTTG
Open in a separate windowaCorresponding nucleotide positions in the complete genome sequence of L. monocytogenes strain EGD-e (GenBank accession number NC_003210).bSee IUPAC codes for definition of degenerate bases.ASPE was performed in multiplex reactions including 30 probes, with each lineage (I to IV), major serogroup (4b, 1/2b, 1/2a, and 1/2c), and epidemic clone (ECI, ECIa, ECII, and ECIII) targeted by two different probes (Table (Table2).2). In addition, positive-control probes were included to confirm the presence of each amplicon in the multiplex PCR. As serogroups and epidemic clones are nested within a particular lineage, probes for these groups were designed to be specific within the appropriate lineage and values for these probes were evaluated only for isolates of the appropriate lineage. For example, serogroup 1/2a probes were evaluated only for isolates that were positive for lineage II probes. ASPE probes were designed with a unique 5′ sequence tag specific to individual sets of xMAP fluorescent polystyrene microspheres (Luminex Corporation) used to sort extension products. Extension and hybridization reactions were performed as described previously (9) except microspheres were twice pelleted by centrifugation (4 min at 2,250 × g) and resuspended in 75 μl 1× TM buffer prior to being pelleted and resuspended in 100 μl 1× TM buffer containing 2 μg/ml streptavidin-R-phycoerythrin (Invitrogen Life Technologies). Samples were incubated for 15 min at 37°C prior to detecting the microsphere complexes with a Luminex 100 flow cytometer (Luminex Corporation). The median fluorescence intensity (MFI) from biotinylated extension products attached to 100 microspheres was measured for each probe. The average MFI from three template-free control samples was also determined and subtracted from the raw MFI of each sample to account for background fluorescence. Probe performance was initially evaluated via the index of discrimination (ID) as described by Ducey et al. (9), and probes with ID values less than 2.0 were redesigned.

TABLE 2.

TMLGT probes and probe performance data
ProbebTarget (n)cProbe sequencedIDeSensitivity (%)Specificity (%)
VGCb-21Lineage I (506)AATCCTTTCTTTAATCTCAAATCAgcggaagcttgggaagcggtc7.3100100
VGCa-94Lineage ICTTTCTATCTTTCTACTCAATAATcaacccgatgttcttcctgtc51.7100100
VGCc-8Lineage II (340)AATCCTTTTACATTCATTACTTACattagctgattcgctttcct14.1100100
INLb-51Lineage IITCATTTCAATCAATCATCAACAATagcgccaataaagctggc21.9100100
VGCb-19Lineage III (50)TCAATCAATTACTTACTCAAATACccgctattaaaatgtactcca31.0100100
VGCb-29Lineage IIIAATCTTACTACAAATCCTTTCTTTggtataccgctattaaaatgt45.1100100
LMO-17Lineage IV (10)CTTTAATCCTTTATCACTTTATCAgaaccaaacaatgttattggt11.8100100
VGCa-27Lineage IVCTTTTCAAATCAATACTCAACTTTttaacgacggtaacgtgccac58.3100100
INLb-84Serogroup 4b (213)TCAACTAACTAATCATCTATCAATggtaaaaatatgcgaatattg9.7100100
INLb-85Serogroup 4bATACTACATCATAATCAAACATCActcgtgaacaagctttcc5.5100100
INLb-16Serogroup 1/2b (293)AATCAATCTTCATTCAAATCATCAggtaaaaatatgcgtatctta11.7100100
INLb-100Serogroup 1/2bCTATCTTTAAACTACAAATCTAACgtgaataagctatcggtctat13.0100100
LMO-42Serogroup 1/2a (268)CTATCTTCATATTTCACTATAAACtggcgttgctgrctaagtttg6.6100100
VGCb-40Serogroup 1/2aCTTTCTACATTATTCACAACATTAaatcaagcsgctcatatgaag10.410098.6
LMO-9Serogroup 1/2c (72)TAATCTTCTATATCAACATCTTACtttactggtgaaatggcg13.5100100
VGCb-5Serogroup 1/2cCAATTCAAATCACAATAATCAATCaagattacgaatcgcttccac20.898.6100
LMO-10ECI (111)ATCATACATACATACAAATCTACAatgattaaaagtcagggaaag19.0100100
LMO-28ECICTACAAACAAACAAACATTATCAAaatcgaggcttacgaacgt23.7100100
VGCc-80ECIa (44)CTAACTAACAATAATCTAACTAACactacaacgaaaacagcgc10.7100100
VGCa-35ECIaCAATTTCATCATTCATTCATTTCAgttacttttatgtcgagt9.2100100
LMO-12ECII (35)TACACTTTCTTTCTTTCTTTCTTTataccgattatttggacggtt3.8100100
LMO-30ECIITTACCTTTATACCTTTCTTTTTACgacttgtagcagttgatttcaa7.5100100
VGCc-45ECIII (10)TCATTTCACAATTCAATTACTCAActcttatttgcttttgttggtc21.110099.4
INLa-3ECIIITACACTTTATCAAATCTTACAATCgagcttaatgaaaatcagcta17.010099.4
INLa-1INLa controlCTTTAATCTCAATCAATACAAATCagaagtggaagctgggaaNAaNANA
INLb-13INLb controlCAATAAACTATACTTCTTCACTAAtgcacctaaacctccgacNANANA
LMO-88LMO controlTTACTTCACTTTCTATTTACAATCccgtttccttatgccacaNANANA
VGCa-23VGCa controlTTCAATCATTCAAATCTCAACTTTcaagycctaagacgccaatcgNANANA
VGCb-25VGCb controlCTTTTCAATTACTTCAAATCTTCAgcatgcgttagttcatgrccaNANANA
VGCc-82VGCc controlTACATACACTAATAACATACTCATgactgcatgctagaatctaagNANANA
Open in a separate windowaNA, not applicable for positive amplicon control probes.bLuminex microsphere sets (Luminex Corporation) used for hybridization reactions are indicated following the hyphen.cn, number of isolates representing the target subtype among the 906 tested isolates.dThe 5′ sequence tag portions of extension probes are capitalized. See IUPAC codes for definitions of degenerate bases.eID, index of discrimination.Validation of the TMLGT assay was performed using 906 L. monocytogenes isolates for which the lineage, major serogroup, and epidemic clone type had been determined independently (see Table S1 in the supplemental material). A subset of 92 isolates, including at least five isolates from each lineage, serogroup, and epidemic clone type, was used to evaluate the discriminatory power of subtype-specific probes and the repeatability of the assay (see Table S1). Two independent runs of the 30-probe TMLGT assay produced identical results for these 92 isolates. In addition, genotypes matched expectations for all isolate/probe combinations, and the fluorescence intensities for positive genotypes (those targeted by a particular probe) were 3.8 to 58.3 (mean, 18.5) times as high as background values for isolates with negative genotypes (those not targeted by a particular probe) (Table (Table2).2). The performances of individual probes also were assessed in terms of sensitivity and specificity, where sensitivity is defined as the percentage of positive samples that produced positive results and specificity indicates the percentage of negative samples that produce negative results (5). Based on results from all 906 isolates analyzed by TMLGT, probe sensitivity was at least 98.6% and 23 of the 24 subtype-specific probes exhibited 100% sensitivity (Table (Table2).2). The specificities for all probes were also greater than 98.6%, and 21 of the 24 subtype-specific probes exhibited 100% specificity (Table (Table22).All but three of the 906 isolates in the validation panel were fully and accurately typed relative to lineage, serogroup, and epidemic clone by using the TMLGT assay (typeability, 99.9%; accuracy of isolate assignment, 99.8%). One of the lineage II isolates, NRRL B-33880, could not be assigned to a serogroup based on the TMLGT results because this isolate was positive for one of the serogroup 1/2a probes (VGCb-40) and one of the serogroup 1/2c probes (LMO-9). This isolate was previously identified as a member of serogroup 1/2c based on mapping lineage-specific MLGT data onto a multilocus phylogeny (34) but produced a serogroup 1/2a-specific banding pattern (data not shown) with the multiplex PCR assay described by Doumith et al. (7). Similar strains, including the common laboratory strain EGD-e, were found to have genomes that are more similar to serogroup 1/2c strains than to strains from the 1/2a serogroup (8, 33) and likely represent intermediates in the evolution of the 1/2c clade from 1/2a ancestors. There is a poor correlation between genomic and antigenic variation for such isolates (34), consistent with the ambiguous results produced by application of the TMLGT assay to NRRL B-33880. The two other problematic isolates, NRRL B-33555 and NRRL B-33559, were accurately identified based on TMLGT data as lineage II isolates from the 1/2a serogroup. However, these two isolates were positive for both ECIII-specific probes in the TMLGT assay but have lineage-specific MLGT haplotypes (Lm2.46), indicating that they are representatives of a sister group closely related to ECIII (33).In 2005, the Food Safety and Inspection Service (FSIS) implemented an approach to inspection that includes consideration of relative risk in order to determine L. monocytogenes sampling frequency among establishments that produce certain RTE products. This approach incorporates information on production volume, outgrowth potential in the product, steps taken to prevent postlethality contamination, and FSIS sampling history. However, L. monocytogenes subtype-specific variation in ecology and virulence indicates that information on the lineage, major serogroup, and epidemic clone identities of isolates could be used to inform assessments of relative risk and to improve inspection programs that are based on consideration of risk. Several PCR-based methods have been described for differentiation of various combinations of these subgroups (1-3, 5, 7, 10, 35, 37); however, these approaches have focused on a single subgroup or a smaller set of subgroups than is differentiated by TMLGT analysis. Although we previously developed a set of three MLGT assays that can be used to differentiate all of the major serogroups and epidemic clones of L. monocytogenes (9, 33, 34), those assays did not include probes for lineage discrimination and require identification of the lineage prior to application of one of three unique sets of probes. In addition, the MLGT assays were designed to maximize strain discrimination, as opposed to subgroup identification, and require the use of at least twice as many probes as is needed for TMLGT analysis. MLGT data analysis is also more complicated than analysis of TMLGT data, and serogroup or epidemic clone type identification via MLGT requires phylogenetic analyses to place novel haplotypes within an established phylogenetic framework.In the present study, we developed the first assay for simultaneous discrimination of the four lineages, the four major serogroups, and the four previously described epidemic clones of L. monocytogenes. The assay includes multiple markers for each of these subtype probes as well as control probes to ensure that negative probe data were not the result of amplification failure, providing a high degree of internal validation required for use in inspection programs that consider risk in making sampling decisions. In addition, the utility of the assay has been validated with a large and diverse panel of 906 isolates, including 567 isolates from FSIS surveillance of RTE products and processing facilities (see Table S1 in the supplemental material). Data produced by the TMLGT assay are amenable to high-throughput analysis, and a simple spreadsheet utility has been developed to semiautomate subtype identifications and to alert investigators to potentially conflicting probe data (available upon request). In addition to having a potential application in inspection programs, the TMLGT assay provides a rapid and accurate means of characterizing L. monocytogenes isolates from different environments, which would facilitate pathogen tracking and improve understanding of L. monocytogenes ecology.   相似文献   

5.
6.
7.
8.
9.
10.
11.
12.
Par-1 is an evolutionarily conserved protein kinase required for polarity in worms, flies, frogs, and mammals. The mammalian Par-1 family consists of four members. Knockout studies of mice implicate Par-1b/MARK2/EMK in regulating fertility, immune homeostasis, learning, and memory as well as adiposity, insulin hypersensitivity, and glucose metabolism. Here, we report phenotypes of mice null for a second family member (Par-1a/MARK3/C-TAK1) that exhibit increased energy expenditure, reduced adiposity with unaltered glucose handling, and normal insulin sensitivity. Knockout mice were protected against high-fat diet-induced obesity and displayed attenuated weight gain, complete resistance to hepatic steatosis, and improved glucose handling with decreased insulin secretion. Overnight starvation led to complete hepatic glycogen depletion, associated hypoketotic hypoglycemia, increased hepatocellular autophagy, and increased glycogen synthase levels in Par-1a−/− but not in control or Par-1b−/− mice. The intercrossing of Par-1a−/− with Par-1b−/− mice revealed that at least one of the four alleles is necessary for embryonic survival. The severity of phenotypes followed a rank order, whereby the loss of one Par-1b allele in Par-1a−/− mice conveyed milder phenotypes than the loss of one Par-1a allele in Par-1b−/− mice. Thus, although Par-1a and Par-1b can compensate for one another during embryogenesis, their individual disruption gives rise to distinct metabolic phenotypes in adult mice.Cellular polarity is a fundamental principle in biology (6, 36, 62). The prototypical protein kinase originally identified as a regulator of polarity was termed partitioning defective (Par-1) due to early embryonic defects in Caenorhabditis elegans (52). Subsequent studies revealed that Par-1 is required for cellular polarity in worms, flies, frogs, and mammals (4, 17, 58, 63, 65, 71, 89). An integral role for Par-1 kinases in multiple signaling pathways has also been established, and although not formally addressed, multifunctionality for individual Par-1 family members is implied in reviews of the list of recognized upstream regulators and downstream substrates (Table (Table1).1). Interestingly, for many Par-1 substrates the phosphorylated residues generate 14-3-3 binding sites (25, 28, 37, 50, 59, 61, 68, 69, 78, 95, 101, 103). 14-3-3 binding in turn modulates both nuclear/cytoplasmic as well as cytoplasmic/membrane shuttling of target proteins, thus allowing Par-1 activity to establish intracellular spatial organization (15, 101). The phosphorylation of Par-1 itself promotes 14-3-3 binding, thereby regulating its subcellular localization (37, 59, 101).

TABLE 1.

Multifunctionality of Par-1 polarity kinase pathwaysa
Regulator or substrateFunctionReference(s)
Regulators (upstream function)
    LKB1Wnt signaling, Peutz-Jeghers syndrome, insulin signal transduction, pattern formation2, 63, 93
    TAO1MEK3/p38 stress-responsive mitogen-activated protein kinase (MAPK) pathway46
    MARKKNerve growth factor signaling in neurite development and differentiation98
    aPKCCa2+/DAG-independent signal transduction, cell polarity, glucose metabolism14, 37, 40, 45, 59, 75, 95
    nPKC/PKDDAG-dependent, Ca2+-independent signal transduction (GPCR)101
    PAR-3/PAR-6/aPKC(−); regulates Par-1, assembly of microtubules, axon-dendrite specification19
    GSK3β(−); tau phosphorylation, Alzheimer''s dementia, energy metabolism, body patterning54, 97
    Pim-1 oncogene(−); G2/M checkpoint, effector of cytokine signaling and Jak/STAT(3/5)5
    CaMKI(−); Ca2+-dependent signal transduction, neuronal differentiation99
Substrates (downstream function)
    Cdc25CRegulation of mitotic entry by activation of the cdc2-cyclin B complex25, 72, 78, 103
    Class II HDACControl of gene expression and master regulator of subcellular trafficking28, 50
    CRTC2/TORC2Gluconeogenesis regulator via LKB1/AMPK/TORC2 signaling, PPARγ1a coactivator49
    Dlg/PSD-95Synaptogenesis and neuromuscular junction, tumor suppressor (102)104
    DisheveledWnt signaling, translocation of Dsh from cytoplasmic vesicles to cortex73, 94
    KSR1Regulation of the Ras-MAPK pathway68, 69
    MAP2/4/TAUDynamic instability (67, 83) of microtubules, Alzheimer''s dementia (30)11, 31-33, 47, 70, 96
    Mib/NotchMind bomb (Mib degradation and repression of Notch signaling results in neurogenesis)57, 74, 81
    Par3/OSKAR/LglCytoplasmic protein segregation, cell polarity, and asymmetric cell division7, 10
    Pkp2Desmosome assembly and organization; nuclear shuttling68, 69
    PTPH1Linkage between Ser/Thr and Tyr phosphorylation-dependent signaling103
    Rab11-FIPRegulation of endocytosis (23), trafficking of E-cadherin (64)34
Open in a separate windowaLKB1 also is known as Par-4; MARKK also is known as Ste20-like; (−), inhibitory/negative regulation has been shown; GPCR, G protein-coupled receptors. MARKK is highly homologous to TAO-1 (thousand-and-one amino acid kinase) (46).The mammalian Par-1 family contains four members (Table (Table2).2). Physiological functions of the Par-1b kinase have been studied using targeted gene knockout approaches in mice (9, 44). Two independently derived mouse lines null for Par-1b have implicated this protein kinase in diverse physiological processes, including fertility (9), immune system homeostasis (44), learning and memory (86), the positioning of nuclei in pancreatic beta cells (35, 38), and growth and metabolism (43).

TABLE 2.

Terminology and localization of mammalian Par-1 family members
SynonymsaSubcellular localization
Par-1a, MARK3, C-TAK1, p78/KP78, 1600015G02Rik, A430080F22Rik, Emk2, ETK-1, KIAA4230, mKIAA1860, mKIAA4230, M80359Basolateralb/apicalc
Par-1b, EMK, MARK2, AU024026, mKIAA4207Basolateral
Par1c, MARK1Basolateral
Par1d, MARK4, MARKL1Not asymmetricd
Open in a separate windowaPar should not to be confused with protease-activated receptor 1 (PAR1 [29]); C-TAK1, Cdc twenty-five C-associated kinase 1; MARK, microtubule affinity regulating kinase; MARKL, MAP/microtubule affinity-regulating kinase-like 1.bBasolateral to a lesser degree than Par-1b (37).cHuman KP78 is asymmetrically localized to the apical surface of epithelial cells (76).dVariant that does not show asymmetric localization in epithelial cells when overexpressed (95).Beyond Par-1b, most information regarding the cell biological functions of the Par-1 kinases comes from studies of Par-1a. Specifically, Par-1a has been implicated in pancreatic (76) and hepatocarcinogenesis (51), as well as colorectal tumors (77), hippocampal function (100), CagA (Helicobacter pylori)-associated epithelial cell polarity disruption (82), and Peutz-Jeghers syndrome (48), although the latter association has been excluded recently (27). As a first step toward determining unique and redundant functions of Par-1 family members, mice disrupted for a second member of the family (Par-1a/MARK3/C-TAK1) were generated. We report that Par-1a−/− mice are viable and develop normally, and adult mice are hypermetabolic, have decreased white and brown adipose tissue mass, and unaltered glucose/insulin handling. However, when challenged by a high-fat diet (HFD), Par-1a−/− mice exhibit resistance to hepatic steatosis, resistance to glucose intolerance, and the delayed onset of obesity relative to that of control littermates. Strikingly, overnight starvation results in a complete depletion of glycogen and lipid stores along with an increase in autophagic vacuoles in the liver of Par-1a−/− but not Par-1b−/− mice. Correspondingly, Par-1a−/− mice develop hypoketotic hypoglycemia. These findings reveal unique metabolic functions of two Par-1 family members.  相似文献   

13.
14.
A total of 210 Salmonella isolates, representing 64 different serovars, were isolated from imported seafood samples, and 55/210 isolates were found to be resistant to at least one antibiotic. Class 1 integrons from three multidrug-resistant Salmonella enterica strains (Salmonella enterica serovars Newport [strain 62], Typhimurium var. Copenhagen [strain 629], and Lansing [strain 803], originating from Hong Kong, the Philippines, and Taiwan, respectively) were characterized. Southern hybridization of plasmids isolated from these strains, using a class 1 integron probe, showed that trimethoprim-sulfamethoxazole and streptomycin resistance genes were located on a megaplasmid in strain 629. Our study indicates that imported seafood could be a reservoir for Salmonella isolates resistant to multiple antibiotics.Salmonella spp. are recognized as major food-borne pathogens of humans worldwide. In the United States, there are an estimated 800,000 to 4 million Salmonella infections annually, and approximately 500 of the cases are fatal (8, 26). A variety of foods have been implicated as vehicles transmitting salmonellosis to humans, including poultry, beef, pork, eggs, milk, cheese, fish, shellfish, fruits, juice, and vegetables (1, 4, 9, 12, 23). Previous studies by field laboratories of the U.S. Food and Drug Administration have shown the prevalences of Salmonella isolates in imported and domestic seafood as 7.2% and 1.3%, respectively (6, 11, 27).Mobile genetic elements, such as plasmids, transposons, and integrons, which disseminate antibiotic resistance genes by horizontal or vertical transfer, as part of either resistance plasmids or conjugative transposons, play an important role in the evolution and dissemination of multidrug resistance (2, 3, 10, 17). Salmonella genomic island 1 (SGI1), the first genomic island reported to contain an antibiotic resistance gene cluster, was identified in the multidrug-resistant Salmonella enterica serovar Typhimurium strain DT 104 (21).Most studies of the prevalence and characterization of antimicrobial resistance genes and integrons in Salmonella spp. have focused on strains from clinical and veterinary sources. However, little is known about the occurrence of SGI1 and its variants in Salmonella spp. isolated from seafood. We have screened a set of drug-resistant S. enterica strains from seafood belonging to 64 different serovars for SGI1 and class 1 integron conserved sequences (CS). We report the presence of a class I variant integron carrying the dfrXII and aadA2 genes on a megaplasmid in serovar Typhimurium var. Copenhagen and on the chromosome in Salmonella enterica serovar Lansing. We also found the variant class 1 integron carrying the dfrA1 and orfC genes in Salmonella enterica serovar Newport strains from seafood.A total of 210 Salmonella enterica strains isolated from seafood imported into the United States between 2000 and 2005 were identified and serotyped by the Pacific Regional Laboratory-Southwest of the FDA, Irvine, CA. The Salmonella strains represented 20 serogroups (Table (Table1)1) from various imported seafood items. The Salmonella strains were tested with 16 antibiotics (14) commonly used in either human or veterinary medicine on Mueller-Hinton agar (Difco Laboratories, Detroit, MI), using a disk diffusion method. The sensitivity and resistance were determined by the criteria of the Clinical and Laboratory Standards Institute (1999).

TABLE 1.

Salmonella serotypes isolated from imported foods
No. of strainsS. enterica serovar(s) or Salmonella group(s)
39Weltevreden
16Newport
13Saintpaul
10Senftenberg
8Lexington
7Virchow
6Enteritidis, Bareily
5Bovismorbificans, Brunei, Java, Hvittingfoss
4Paratyphi B var. Java, Thompson
3Aberdeen, Cubana, Stanley, Derby, Lansing
2Montevideo, Hadar, Agona, San Diego, Braenderup, Lanka, Salmonella enterica subsp. diarizonae, Oslo, Bareily variant, Salmonella monophasic group C2
1Ouakam, Cannstatt, Albany, Newport/Bardo, Adelaide, S. enterica subsp. diarizonae, Houten, Giza, Miami, Onderstepoof, Infantis, Salmonella monophasic group D1, Mbandaka, Salmonella monophasic group G2, Ohio, Rutgers, Salmonella monophasic group D2, Amsterdam, Salmonella enterica subsp. IV serotype 43:z4z23, Paratyphi B var. Java, Wentworth, Potsdam, Muenster var. 15+, 34+, Lexington var. 15+, Weltevreden var. 15+, S. enterica subsp. I, Madella, Alachua, London, Singapore, Uphill, Thielallee, Typhimurium var. Copenhagen
Open in a separate windowAll Salmonella strains that were resistant to three or four antibiotics and trimethoprim were screened by PCR for the presence of class 1 integrons, using the CSL1 and CSR1 primers (Table (Table2)2) (14). To confirm other antibiotic resistance genes, we used primers and PCR methods described previously (13, 14, 16). To identify SGI1 in multidrug-resistant strains, PCR was performed by using primers U7-L12/LJ-R1 and 104-RJ/104-D (Table (Table2),2), corresponding to the left and right junctions of SGI1 in the Salmonella chromosome, respectively (16). For a positive control, serovar Typhimurium DT104 strain DT7 (13) was used. As a negative control, Escherichia coli cells or DNA was used. A reagent blank included in each PCR contained distilled water instead of template DNA. For sequencing, the PCR-amplified integrons were purified and cloned into plasmid vector pCR2.1 (Invitrogen Corp., Carlsbad, CA). The clones were investigated for the presence of inserts by isolating the recombinant plasmid, which was confirmed by digestion with the restriction enzyme EcoRI. Sequencing of both strands was performed. DNA sequences were analyzed with Lasergene (DNASTAR, Inc., Madison, WI) software. Oligonucleotide primers and probes were purchased from MWG Biotech (High Point, NC).

TABLE 2.

Primer pairs for integron PCR and sequencing
PrimerSequence (5′-3′)LocationPCR product size (bp)
CSL1GGC ATC CAA GCA GCA AGC5′ CS
CSR1AAG CAG ACT TGA CCT GAT3′ CS
U7-L12ACA CCT TGA GCA GGG CAA AGthdF500
LJ-R1AGT TCT AAA GGT TCG TAG TCG
104-RJTGA CGA GCT GAA GCG AAT TGS044
104DACC AGG GCA AAA CTA CAC AGyidY
aadA2FTGT TGG TTA CTG TGG CCG TAaadA2380
aadA2RGCT GCG AGT TCC ATA GCT TC
Open in a separate windowPlasmid DNA was isolated using an alkaline lysis method with modifications described previously (19). Plasmids were separated by electrophoresis in 1× Tris-acetate-EDTA buffer at 64 V for 2 h on 1.0% agarose gels, stained with 40 μl of ethidium bromide (0.625 mg/ml) for visualization, and then transferred and cross-linked to positively charged nylon membranes (Roche, Indianapolis, IN). The resulting blots were hybridized at 65°C for 18 h with digoxigenin-labeled DNA probes (1.2-kb and 1.9-kb PCR-amplified products), using CSL1 and CSR1 primers specific for class 1 integrons (22).  相似文献   

15.
16.
17.
Feeding high levels of zinc oxide to piglets significantly increased the relative abundance of ileal Weissella spp., Leuconostoc spp., and Streptococcus spp., reduced the occurrence of Sarcina spp. and Neisseria spp., and led to numerical increases of all Gram-negative facultative anaerobic genera. High dietary zinc oxide intake has a major impact on the porcine ileal bacterial composition.Zinc oxide (ZnO) is used as a feed additive for diarrhea prophylaxis in piglets (23). However, the mode of action of ZnO is not fully understood. Besides its effects on the host (10, 30, 31), high dietary zinc levels may affect the diversity of intestinal microbial communities (2, 11, 20). The prevention of postweaning diarrhea in piglets due to high dietary ZnO intake may not be directly related to a reduction of pathogenic E. coli (8) but, rather, to the diversity of the coliform community (15). Studies on the impact of high ZnO levels on the porcine ileal bacterial community are scarce but nevertheless important, as bacterial diarrhea is initiated in the small intestine (9, 17). The small intestine is a very complex habitat with many different factors shaping the bacterial community. Studies on the ecophysiology (22) and maturation of the porcine ileal microbiota (13, 27) indicate a drastic impact directly after weaning and a gradual decline of modifications during the following 2 weeks. Thus, the time point for analysis chosen in this study (14 days postweaning) does reflect a more stable period of the ileal porcine microbiota. In this study, we used bar-coded pyrosequencing of 16S rRNA genes to gain further insight into the mode of action of pharmacological levels of ZnO in the gastrointestinal tract of young pigs.Total DNA was extracted from the ileal digesta of 40- to 42-day-old piglets using a commercial kit (Qiagen stool kit; Qiagen, Hilden, Germany) and PCR amplified with unique bar-coded primer sets targeting the V1-to-V3 and the V6-to-V8 hypervariable regions (see the supplemental material for detailed methods). The rationale behind this approach was derived from the fact that no single “universal” primer pair can completely cover a complex bacterial habitat (4, 24, 32, 33). Furthermore, these studies also show that in silico information on the coverage of selected primer sets diverges from empirical results, and hence, two hypervariable regions were chosen in this study to maximize the detection of phylogenetically diverse bacterial groups.Equimolar dilutions of all samples were combined into one master sample. Pyrosequencing was performed by Agowa (Berlin, Germany) on a Roche genome sequencer FLX system using a Titanium series PicoTiterPlate. The resulting data files were uploaded to the MG-RAST server (http://metagenomics.nmpdr.org/) (19) and processed with its SEED software tool using the RDP database (5) as the reference database. After automated sequence analysis, all sequences with less than five identical reads per sample were deleted in order to increase the confidence of sequence reads and reduce bias from possible sequencing errors (12, 16). Thus, 0.43% of all sequences were not considered (1,882 of 433,302 sequences). These sequences were assigned to a total of 238 genera, of which most only occurred in a few samples (see the supplemental material). Furthermore, all unclassified sequences were removed (8.7%; 41,467 of 474,769 sequences). Due to the use of the RDP reference database, the SEED software incorrectly assigned the majority of unclassified sequences as unclassified Deferribacterales (83%; 34,393 sequences), which were actually identified as 16S soybean or wheat chloroplasts by BLAST or as cyanobacterial chloroplasts by the RDP II seqmatch tool.The pyrosequencing results for the two primer combinations were merged by taking only sequences from the primer combination that yielded the higher number of reads for a specific sequence assignment in a sample. The remaining reads were used to calculate the relative contribution of assigned sequences to total sequence reads in a sample.The Firmicutes phylum dominated the small intestinal bacterial communities in both the control group and the group with high dietary ZnO intake, with 98.3% and 97.0% of total sequence reads, respectively. No significant influence of high dietary ZnO intake was found for the main phyla Proteobacteria (0.92% versus 1.84%), Actinobacteria (0.61% versus 0.75%), Bacteroidetes (0.15% versus 0.17%), and Fusobacteria (0.09% versus 0.12%).On the order level, a total of 20 bacterial orders were detected (data not shown). Lactobacillales dominated bacterial communities in the control and high-dietary-ZnO-intake groups, with 83.37% and 93.24% of total reads. Lactic acid bacteria are well known to dominate the bacterial community in the ileum of piglets (11, 22). No significant difference between the control group and the group with high dietary ZnO intake was observed on the order level, although high dietary ZnO intake led to a strong numerical decrease for Clostridiales (14.4 ± 24.0% [mean ± standard deviation] versus 2.8 ± 1.7%), as well as to numerical increases for Pseudomonadales (0.3 ± 0.3% versus 0.6 ± 0.6%) and Enterobacteriales (0.2 ± 0.2% versus 0.5 ± 0.6%).On the genus level, a total of 103 genera were detected. Table Table11 summarizes the main 31 genera which exceeded 0.05% of total reads (see the supplemental material for a complete list). Lactobacilli clearly dominated the bacterial communities in both trial groups, but they also were numerically lower due to high dietary ZnO intake.

TABLE 1.

Bacterial genera in the ileum of piglets fed diets supplemented with 200 or 3,000 ppm ZnO
GenusProportion (% ± SD) of ileal microbiota in groupa receiving:
200 ppm ZnO3,000 ppm ZnO
Lactobacillus59.3 ± 30.640.7 ± 19.1
Weissella11.6 ± 7.8 A24.1 ± 8.3 B
Sarcina11.4 ± 20.5 A0.84 ± 1.2 B
Leuconostoc4.7 ± 3.2 A9.4 ± 3.1 B
Streptococcus1.8 ± 1.6 A5.7 ± 5.1 B
Lactococcus1.6 ± 1.52.6 ± 3.1
Veillonella0.57 ± 0.630.34 ± 0.30
Gemella0.34 ± 0.67 A0.45 ± 0.25 B
Acinetobacter0.25 ± 0.210.44 ± 0.50
Clostridium0.25 ± 0.400.22 ± 0.21
Enterococcus0.19 ± 0.150.26 ± 0.24
Acidovorax0.14 ± 0.040.16 ± 0.19
Arcobacter0.14 ± 0.150.16 ± 0.17
Neisseria0.14b0.03 ± 0.01
Enterobacter0.13 ± 0.090.29 ± 0.34
Lachnospira0.12 ± 0.130.13 ± 0.03
Peptostreptococcus0.11 ± 0.100.07 ± 0.09
Chryseobacterium0.10 ± 0.070.15 ± 0.16
Actinomyces0.09 ± 0.040.15 ± 0.16
Anaerobacter0.07 ± 0.080.02 ± 0.01
Aerococcus0.07 ± 0.040.07 ± 0.04
Dorea0.07b0.05 ± 0.05
Fusobacterium0.06 ± 0.090.08 ± 0.11
Microbacterium0.06 ± 0.010.07 ± 0.04
Carnobacterium0.06 ± 0.020.08 ± 0.13
Granulicatella0.06 ± 0.020.09 ± 0.10
Staphylococcus0.06 ± 0.040.05 ± 0.02
Facklamia0.05 ± 0.060.03 ± 0.01
Comamonas0.05 ± 0.030.04 ± 0.02
Citrobacter0.05 ± 0.020.07 ± 0.08
Erysipelothrix0.05 ± 0.010.22 ± 0.40
Open in a separate windowan = 6 piglets per trial group. A,B, results are significantly different by Kruskal-Wallis test.bSingle sample.Significant changes due to high dietary ZnO intake were observed for other lactic acid bacteria, including Weissella spp., Leuconostoc spp., and Streptococcus spp. A significant and strong decrease was observed for Sarcina spp., which is a genus of acid-tolerant strictly anaerobic species found in the intestinal tract of piglets and other mammals (6, 28, 29). This genus thus appeared to be very sensitive to modifications induced by high dietary ZnO intake.An interesting result was observed for Gram-negative Proteobacteria, (i.e., enterobacteria and relatives). Although not statistically significant, virtually all detected proteobacteria increased numerically due to high dietary ZnO intake (Enterobacter spp., Microbacterium spp., Citrobacter spp., Neisseria spp., and Acinetobacter spp.). Apparently, enterobacteria gained colonization potential by high dietary ZnO intake. This is in good agreement with the results of studies by Hojberg et al. (11), Amezcua et al. (1), and Castillo et al. (3). Therefore, the frequently observed diarrhea-reducing effect of zinc oxide may not be directly related to a reduction of pathogenic E. coli strains. Considering a possible antagonistic activity of lactobacilli against enterobacteria (25), it can be speculated that a numerical decrease of dominant lactobacilli may lead to increased colonization with Gram-negative enterobacteria. On the other hand, specific plasmid-borne genes for resistance against heavy metals have been reported for both Gram-positive and Gram-negative bacteria present in the intestine (21, 26), and an increased resistance against Zn ions may exist for Gram-negative enterobacteria. Zinc oxide is an amphoteric molecule and shows a high solubility at acid pH. The low pH in the stomach of piglets (pH 3.5 to 4.5) transforms a considerable amount of insoluble ZnO into zinc ions (54 to 84% free Zn2+ at 150 ppm and 24 ppm ZnO, respectively) (7), and thus, high concentrations of toxic zinc ions exist in the stomach. The stomach of piglets harbors large numbers of lactic acid bacteria, especially lactobacilli. Zn ions may thus lead to a modification of the lactic acid bacterial community in the stomach, and the changes observed in the ileum could have been created in the stomach. A reduction of dominant lactobacilli may thus point to an increased adaptation potential of Gram-negative facultative anaerobes and a generally increased bacterial diversity.Additionally, the direct effects of dietary ZnO on intestinal tissues include altered expression of genes responsible for glutathione metabolism and apoptosis (30), enhanced gastric ghrelin secretion, which increases feed intake (31), and increased production of digestive enzymes (10). An analysis of the intestinal morphology was beyond the scope of this study, but although ZnO concentrations are markedly increased in intestinal tissue, the influence of ZnO on morphology is apparently not always observed (10, 14, 18). Consequently, any changes in epithelial cell turnover, feed intake, or digestive capacity may influence the composition of bacterial communities in the small intestine.In conclusion, this study has shown that high dietary zinc oxide has a major impact on ileal bacterial communities in piglets. Future studies on the impact of zinc oxide in pigs should include a detailed analysis of host responses in order to identify the cause for the observed modifications of intestinal bacterial communities.  相似文献   

18.
19.
20.
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号