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1.
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
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2.
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   

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   

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Angiostrongylus cantonensis is the most common cause of human eosinophilic meningitis. Humans become infected by ingesting food items contaminated with third-stage larvae that develop in mollusks. We report the development of a real-time PCR assay for the species-specific identification of A. cantonensis in mollusk tissue.Angiostrongylus cantonensis is the most common agent associated with eosinophilic meningitis in humans. Young adult worms develop in the brains of rodents and are carried to pulmonary arteries to reach sexual maturity. Eggs are laid in lung tissues, and first-stage (L1) larvae break into air spaces, migrate to the trachea, are swallowed, and are passed with rodent feces. The L1 larvae must infect mollusks to develop into third-stage (L3) larvae; L3 is the infective stage for rodents and other mammals. Humans become infected by ingesting raw produce contaminated with L3 larvae or infected raw or undercooked mollusks or paratenic hosts. The immature worms remain in the human brain, creating tissue damage and inflammation (2, 19, 21).A. cantonensis is endemic in Southeast Asia, parts of the Caribbean, and the Pacific Islands, including Hawaii (7, 12, 15-17). The worm has been detected in host animals in Louisiana (5, 14) and in one human patient from New Orleans (18), but it is currently unclear to what extent the nematode has spread into other U.S. states (8, 9). Ascertaining the geographic presence of the parasite is important to manage and prevent new cases of eosinophilic meningitis associated with ingestion of infective larvae (12, 18).Detection of A. cantonensis in mollusks can be performed by releasing the larvae from the tissue with pepsin digestion (11). However, that procedure requires access to living mollusks, which complicates analysis of large numbers of samples. After a recent outbreak of angiostrongyliasis in Hawaii (12), we developed a conventional PCR assay and applied it to survey the Hawaiian mollusk population using frozen tissue (20). That PCR assay, as well as morphological identification using pepsin digestion, can only identify the larvae on the superfamily level, so additional molecular work is required for species-specific classification. Here we describe a new real-time PCR assay that allows for a direct detection of A. cantonensis at the species level.The 18S rRNA gene is too conserved among nematode species to allow species-specific detection. The first and second internal transcribed spacers (ITS1 and ITS2) are comparatively more variable than the rRNA coding regions and have thus been used for differentiation of closely related species (1, 4, 6, 10, 22, 23). We PCR amplified and sequenced ITS1 from A. costaricensis (two laboratory strains from Costa Rica and Brazil), A. vasorum (from naturally infected hosts in United Kingdom), and A. cantonensis from three geographical regions (one laboratory strain from Japan plus nine environmental isolates from Hawaii and New Orleans, LA) to assess the variability of this potential PCR target. The oligonucleotide primers used were AngioF1674 (5′-GTCGTAACAAGGTATCTGTAGGTG-3′) and 58SR4 (5′-TAGCTGCGTTTTTCATCGATA-3′). The reaction mixtures contained 0.4 μM each primer and AmpliTaq Gold PCR master mix (Applied Biosystems, Foster City, CA) and were cycled 45 times at 94°C for 30 s, 65°C for 30 s, and 72°C for 1 min. PCR products were cloned into pCR2.1 vectors using the TOPO cloning technique (Invitrogen, Carlsbad, CA) and sequenced on both strands as described elsewhere (20).The sequence analysis revealed high interspecific and low intraspecific variability. A TaqMan assay targeting ITS1 was then designed using Primer Express version 2.3 (Applied Biosystems, Foster City, CA). The real-time PCR assay was performed in a 20-μl total volume containing Platinum qPCR Supermix (Invitrogen, Carlsbad, CA), 0.2 μM (each) primers AcanITS1F1 (5′-TTCATGGATGGCGAACTGATAG-3′) and AcanITS1R1 (5′-GCGCCCATTGAAACATTATACTT-3′), and 0.05 μM the TaqMan probe AcanITS1P1 (5′-6-carboxyfluorescein-ATCGCATATCTACTATACGCATGTGACACCTG-BHQ-3′). The standard cycling conditions for TaqMan assays were used (i.e., 40 cycles of 95°C for 15 s and 60°C for 1 min).We evaluated the real-time PCR assay with a set of 26 Parmarion martensi slugs from Hawaii. Seventeen slugs were positive for L3 larvae as determined by pepsin digestion, and nine slugs were negative. DNA was extracted from approximately 25 mg of tissue of each slug using the DNeasy tissue and blood DNA extraction kit (Qiagen, Inc., Valencia, CA). The real-time PCR performed on this set of samples returned an identical result to the morphological analysis. The real-time PCR amplified only DNA from A. cantonensis and did not react with DNA from other nematode species (Table (Table1).1). The detection limit of the assay was determined by serially diluting a recombinant plasmid containing the ITS1 sequence to less than 1 copy per μl of sample. The real-time PCR reliably detected down to 10 plasmid copies in the reaction.

TABLE 1.

Comparison of conventional and real-time PCR for detection of Angiostrongylus cantonensis in mollusks and nematode samples
Biological origin of DNA sampleGeographic originNo. of samples testedNo. of samples positive by:
18S rRNA-based conventional PCRITS1-based TaqMan PCR
Parmarion martensiHawaii1127583
Veronicella cubensisHawaii5023a22
Laevicaulis alteHawaii534
Achatina fulicaHawaii645
Other/unidentified mollusksHawaii1645
FlatwormsHawaii222
Slime from infected slugsHawaii1311
Pomacea insularumLouisiana3155
A. costaricensisBrazil, Costa Rica22b0
A. vasorumUnited Kingdom22b0
Other nematodescCDC collection1400
Total253121127
Open in a separate windowaThis number includes three samples positive by PCR but later identified as non-Angiostrongylus nematodes by DNA sequencing analysis of the amplicons (20). These three samples were negative in the real-time PCR assay.bThe conventional PCR detects other Angiostrongylus species besides A. cantonensis.cTwo stool samples containing Strongyloides worms, eight environmental samples containing unclassified free-living nematodes and one of each of the following parasitic nematodes: Dipetalonema sp., Toxocara cati, Dracunculus medinensis, and Ascaris lumbricoides.The real-time PCR assay was then used to analyze a larger set of naturally infected host animals from Hawaii, partly described elsewhere (13, 20), and Island Apple snails (Pomacea insularum) from New Orleans, LA. All samples had previously been characterized by the conventional PCR followed by DNA sequencing analysis (20).Table Table11 summarizes the PCR findings and highlights the enhanced performance of the real-time PCR in comparison to the conventional PCR. In addition, the real-time PCR assay was more practical to use since it did not require DNA sequence confirmation to rule out false positives.The findings from Island Apple snails from New Orleans infected with A. cantonensis concur with previous reports about the potential for angiostrongyliasis transmission in this area (5, 14). Another interesting finding was the positive PCR results in two samples of flatworms from Hawaii. Predatory flatworms that ingest infected mollusks are known to be paratenic hosts of A. cantonensis and have been suspected to be an important source of infection for humans in Japan because they hide in leafy vegetables (3).In conclusion, this real-time PCR assay can be a useful tool for environmental surveys of local wildlife to determine the geographic distribution of this reemerging human parasite.  相似文献   

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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   

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The three-dimensional structure of adeno-associated virus (AAV) serotype 6 (AAV6) was determined using cryo-electron microscopy and image reconstruction and using X-ray crystallography to 9.7- and 3.0-Å resolution, respectively. The AAV6 capsid contains a highly conserved, eight-stranded (βB to βI) β-barrel core and large loop regions between the strands which form the capsid surface, as observed in other AAV structures. The loops show conformational variation compared to other AAVs, consistent with previous reports that amino acids in these loop regions are involved in differentiating AAV receptor binding, transduction efficiency, and antigenicity properties. Toward structure-function annotation of AAV6 with respect to its unique dual glycan receptor (heparan sulfate and sialic acid) utilization for cellular recognition, and its enhanced lung epithelial transduction compared to other AAVs, the capsid structure was compared to that of AAV1, which binds sialic acid and differs from AAV6 in only 6 out of 736 amino acids. Five of these residues are located at or close to the icosahedral 3-fold axis of the capsid, thereby identifying this region as imparting important functions, such as receptor attachment and transduction phenotype. Two of the five observed amino acids are located in the capsid interior, suggesting that differential AAV infection properties are also controlled by postentry intracellular events. Density ordered inside the capsid, under the 3-fold axis in a previously reported, conserved AAV DNA binding pocket, was modeled as a nucleotide and a base, further implicating this capsid region in AAV genome recognition and/or stabilization.Adeno-associated viruses (AAVs) are nonpathogenic single-stranded DNA (ssDNA) parvoviruses that belong to the Dependovirus genus and require helper viruses, such as Adenovirus or Herpesvirus, for lytic infection (4, 8, 22, 67). These viruses package a genome of ∼4.7 kb inside an icosahedral capsid (∼260 Å in diameter) with a triangulation number equal to 1 assembled from a total of 60 copies of their overlapping capsid viral protein (VP) 1 (VP1), VP2, and VP3 in a predicted ratio of 1:1:8/10 (10). The VPs are encoded from a cap open reading frame (ORF). VP3 is 61 kDa and constitutes 90% of the capsid''s protein composition. The less abundant VPs, VP1 (87 kDa) and VP2 (73 kDa), share the same C-terminal amino acid sequence with VP3 but have additional N-terminal sequences. A rep ORF codes for four overlapping proteins required for replication and DNA packaging.To date, more than 100 AAV isolates have been identified (21). Among the human and nonhuman primate AAVs isolated, 12 serotypes (AAV serotype 1 [AAV1] to AAV12) have been described and are classified into six phylogenetic clades on the basis of their VP sequences and antigenic reactivities, with AAV4 and AAV5 considered to be clonal isolates (21). AAV1 and AAV6, which represent clade A, differ by only 6 out of 736 VP1 amino acids (5 amino acids within VP3) and are antigenically cross-reactive. Other clade representatives include AAV2 (clade B), AAV2-AAV3 hybrid (clade C), AAV7 (clade D), AAV8 (clade E), and AAV9 (clade F) (21).The AAVs are under development as clinical gene delivery vectors (e.g., see references 5, 9, 12, 13, 24, 25, 53, and 61), with AAV2, the prototype member of the genus, being the most extensively studied serotype for this application. AAV2 has been successfully used to treat several disorders, but its broad tissue tropism makes it less effective for tissue-specific applications and the prevalence of preexisting neutralizing antibodies in the human population (11, 43) limits its utilization, especially when readministration is required to achieve a therapeutic outcome. Efforts have thus focused on characterizing the capsid-associated tissue tropism and transduction properties conferred by the capsid of representative serotypes of other clades (21). Outcomes of these studies include the observation that AAV1 and AAV6, for example, transduce liver, muscle, and airway epithelial cells more efficiently (e.g., up to 200-fold) than AAV2 (27, 28, 30). In addition, the six residues (Table (Table1)1) that differ between the VPs of AAV1 and AAV6 (a natural recombinant of AAV1 and AAV2 [56]) confer functional disparity between these two viruses. For example, AAV6 shows ∼3-fold higher lung cell epithelium transduction than AAV1 (27), and AAV1 and AAV6 bind terminally sialylated proteoglycans as their primary receptor, whereas AAV6 additionally binds to heparan sulfate (HS) proteoglycans with moderate affinity (70, 71). Therefore, a comparison of the AAV1 and AAV6 serotypes and, in particular, their capsid structures can help pinpoint the capsid regions that confer differences in cellular recognition and tissue transduction.

TABLE 1.

Amino acid differences between AAV1 and AAV6 and their reported mutants
AAVAmino acid at positiona:
Glycan targetbReference
129418531532584598642
AAV1LEEDFANS70
AAV1-E/KLEKDFANHS+ (and S)c70
AAV6FDKDLVHHS and S70
AAV6.1FDEDLVHHS (and S)c40, 70
AAV6.2LDKDLVHHS (and S)c40, 70
AAV6R2LDEDLVHHS (and S)c40
HAE1LEEDLVN(HS and S)d39
HAE2LDKDLVN(HS and S)d39
shH10FDKNLVNHS (and S-inde)33
Open in a separate windowaMutant residues in boldface have an AAV6 parental original; those underlined have an AAV1 parental origin.bS, sialic acid; HS, heparan sulfate; HS+, HS positive.cThe sialic acid binding phenotypes of these mutants were not discussed in the respective publications but are assumed to be still present.dThe glycan targets for these mutants were not discussed in this publication; thus, the phenotypes indicated are assumed.eThis mutant is sialic acid independent (S-ind) for cellular transduction.The structures of AAV1 to AAV5 and AAV8 have been determined by X-ray crystallography and/or cryo-electron microscopy and image reconstruction (cryo-EM) (23, 36, 47, 52, 66, 73; unpublished data), and preliminary characterization of crystals has also been reported for AAV1, AAV5, AAV7, and AAV9 (15, 45, 46, 55). The capsid VP structures contain a conserved eight-stranded (βB to βI) β-barrel core and large loop regions between the strands that form the capsid surface. The capsid surface is characterized by depressions at the icosahedral 2-fold axes of symmetry, finger-like projections surrounding the 3-fold axes, and canyon-like depressions surrounding the 5-fold axes. A total of nine variable regions (VRs; VRI to VRIX) were defined when the two most disparate structures, AAV2 and AAV4, were compared (23). The VRs contain amino acids that contribute to slight differences in surface topologies and distinct functional phenotypes, such as in receptor binding, transduction efficiency, and antigenic reactivity (10, 23, 37, 47).The structure of virus-like particles (VLPs) of AAV6, produced in a baculovirus/Sf9 insect cell expression system, has been determined by two highly complementary approaches, cryo-EM and X-ray crystallography. The AAV6 VP structure contains the general features already described for the AAVs and has conformational differences in the VRs compared to the VRs of other AAVs. The 9.7-Å-resolution cryoreconstructed structure enabled the localization of the C-α positions of five of the six amino acids that differ between highly homologous AAV6 and AAV1 but did not provide information on the positions of the side chains or their orientations. The X-ray crystal structure determined to 3.0-Å resolution enabled us to precisely map the atomic positions of these five residues at or close to the icosahedral 3-fold axes of the capsid. Reported mutagenesis and biochemical studies had functionally annotated the six residues differing between AAV1 and AAV6 with respect to their roles in receptor attachment and differential cellular transduction. Their disposition identifies the 3-fold capsid region as playing essential roles in AAV infection.  相似文献   

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Halogenated organic compounds serve as terminal electron acceptors for anaerobic respiration in a diverse range of microorganisms. Here, we report on the widespread distribution and diversity of reductive dehalogenase homologous (rdhA) genes in marine subsurface sediments. A total of 32 putative rdhA phylotypes were detected in sediments from the southeast Pacific off Peru, the eastern equatorial Pacific, the Juan de Fuca Ridge flank off Oregon, and the northwest Pacific off Japan, collected at a maximum depth of 358 m below the seafloor. In addition, significant dehalogenation activity involving 2,4,6-tribromophenol and trichloroethene was observed in sediment slurry from the Nankai Trough Forearc Basin. These results suggest that dehalorespiration is an important energy-yielding pathway in the subseafloor microbial ecosystem.Scientific ocean drilling explorations have revealed that marine subsurface sediments harbor remarkable numbers of microbial cells that account for approximately 1/10 to 1/3 of all living biota on Earth (20, 25, 33). Thermodynamic calculations of pore-water chemistry suggest that subseafloor microbial activities are generally supported by nutrient and energy supplies from the seawater and/or underlying basaltic aquifers (6, 7). Although sulfate, nitrate, Fe(III), Mn(IV), and bicarbonate are known to be potential electron acceptors for anaerobic microbial respiration in marine subsurface sediments (5), the incidence of both the dissimilatory dehalorespiration pathway and microbial activity in halogenated organic substrates remains largely unknown.Previous molecular ecological studies using 16S rRNA gene sequences demonstrated that Chloroflexi is one of the most frequently detected phyla in subseafloor sediments of the Pacific Ocean margins (12-14). Some of the sequences within the Chloroflexi are closely related to sequences in the genus Dehalococcoides, which contains obligatory dehalorespiring bacteria that employ halogenated organic compounds as terminal electron acceptors (21, 29). The frequent detection of Dehalococcoides-related 16S rRNA genes from these environments implies the occurrence of dissimilatory dehalorespiration in marine subsurface sediments.In this study, we detected and phylogenetically analyzed the reductive dehalogenase homologous (rdhA) genes, key functional genes for dehalorespiration pathways, from frozen sediment core samples obtained by Ocean Drilling Program (ODP) Leg 201 (Peru margin and eastern equatorial Pacific) (7, 14); Integrated Ocean Drilling Program (IODP) Expedition 301 (Juan de Fuca Ridge flank) (8, 24); Chikyu Shakedown Expedition CK06-06 (Northwest Pacific off Japan) (20, 23); and IODP Expedition 315 (Nankai Trough Forearc Basin off Japan) (Table (Table1).1). DNA was extracted using an ISOIL bead-beating kit (Nippon Gene, Japan) and purified using a MagExtractor DNA fragment purification kit (Toyobo, Japan) according to the manufacturer''s instructions. To increase concentration, DNA was amplified by multiple displacement amplification using the phi29 polymerase supplied with a GenomiPhi kit (GE Healthcare, United Kingdom) (20). Putative rdhA genes were amplified by PCR using Ex Taq polymerase (TaKaRa, Japan) with degenerate primers RRF2 and B1R (17), dehaloF3, dehaloF4, dehaloF5, dehaloR2, dehaloR3, and dehaloR4 (32), and ceRD2S, ceRD2L, and RD7 (26) and the PCR conditions described in those studies. Amplicons of the approximate target size were gel purified and cloned into the pCR2.1 vector (Invitrogen, Japan). Sequence similarity was analyzed using FastGroupII web-based software (34), and sequences with a 95% identity were tentatively assigned to the same phylotype. Amino acid sequences were aligned by ClustalW (31), including known and putative reductive dehalogenase sequences in the genome of Dehalococcoides ethenogenes strain 195 (28), as well as several functionally characterized reductive dehalogenases from other species.

TABLE 1.

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

20.
Recent studies indicate that sexual transmission of human immunodeficiency virus type 1 (HIV-1) generally results from productive infection by only one virus, a finding attributable to the mucosal barrier. Surprisingly, a recent study of injection drug users (IDUs) from St. Petersburg, Russia, also found most subjects to be acutely infected by a single virus. Here, we show by single-genome amplification and sequencing in a different IDU cohort that 60% of IDU subjects were infected by more than one virus, including one subject who was acutely infected by at least 16 viruses. Multivariant transmission was more common in IDUs than in heterosexuals (60% versus 19%; odds ratio, 6.14; 95% confidence interval [CI], 1.37 to 31.27; P = 0.008). These findings highlight the diversity in HIV-1 infection risks among different IDU cohorts and the challenges faced by vaccines in protecting against this mode of infection.Elucidation of virus-host interactions during and immediately following the transmission event is one of the great challenges and opportunities in human immunodeficiency virus (HIV)/AIDS prevention research (14-16, 31, 34, 45). Recent innovations involving single-genome amplification (SGA), direct amplicon sequencing, and phylogenetic inference based on a model of random virus evolution (18-20, 43) have allowed for the identification of transmitted/founder viruses that actually cross from donor to recipient, leading to productive HIV type 1 (HIV-1) infection. Our laboratory and others have made the surprising finding that HIV-1 transmission results from productive infection by a single transmitted/founder virus (or virally infected cell) in ∼80% of HIV-infected heterosexuals and in ∼60% of HIV-infected men who have sex with men (MSM) (1, 13, 18, 24). These studies thus provided a precise quantitative estimate for the long-recognized genetic bottleneck in HIV-1 transmission (6, 11-13, 17, 25, 28, 30, 35, 38, 42, 47-49) and a plausible explanation for the low acquisition rate per coital act and for graded infection risks associated with different exposure routes and behaviors (15, 36).In contrast to sexual transmission of HIV-1, virus transmission resulting from injection drug use has received relatively little attention (2, 3, 29, 42) despite the fact that injection drug use-associated transmission accounts for as many as 10% of new infections globally (26, 46). We hypothesized that SGA strategies developed for identifying transmitted/founder viruses following mucosal acquisition are applicable to deciphering transmission events following intravenous inoculation and that, due to the absence of a mucosal barrier, injection drug users (IDUs) exhibit a higher frequency of multiple-variant transmission and a wider range in numbers of transmitted viruses than do acutely infected heterosexual subjects. We obtained evidence in support of these hypotheses from the simian immunodeficiency virus (SIV)-Indian rhesus macaque infection model, where we showed that discrete low-diversity viral lineages emanating from single or multiple transmitted/founder viruses could be identified following intravenous inoculation and that the rectal mucosal barrier to infection was 2,000- to 20,000-fold greater than with intravenous inoculation (19). However, we also recognized potentially important differences between virus transmission in Indian rhesus macaques and virus transmission in humans that could complicate an IDU acquisition study. For example, in the SIV macaque model, the virus inocula can be well characterized genetically and the route and timing of virus exposure in relation to plasma sampling precisely defined, whereas in IDUs, the virus inoculum is generally undefined and the timing of virus infection only approximated based on clinical history and seroconversion testing (8). In addition, IDUs may have additional routes of potential virus acquisition due to concomitant sexual activity. Finally, there is a paucity of IDU cohorts for whom incident infection is monitored sufficiently frequently and clinical samples are collected often enough to allow for the identification and enumeration of transmitted/founder viruses. To address these special challenges, we proposed a pilot study of 10 IDU subjects designed to determine with 95% confidence if the proportion of multivariant transmissions in IDUs was more than 2-fold greater than the 20% frequency established for heterosexual transmission (1, 13, 18, 24). A secondary objective of the study was to determine whether the range in numbers of transmitted/founder viruses in IDUs exceeded the 1-to-6 range observed in heterosexuals (1, 13, 18, 24). To ensure comparability among the studies, we employed SGA-direct amplicon sequencing approaches, statistical methods, and power calculations identical to those that we had used previously to enumerate transmitted/founder viruses in heterosexual and MSM cohorts (1, 13, 18, 20, 24).We first surveyed investigators representing acute-infection cohorts in the United States, Canada, Russia, and China; only one cohort—the Montreal Primary HIV Infection Cohort (41)—had IDU clinical samples and clinical data available for study. The Montreal cohort of subjects with acute and early-stage HIV-1 infection was established in 1996 and recruits subjects from both academic and private medical centers throughout the city. Injection drug use is an important contributing factor to Montreal''s HIV burden, with IDUs comprising approximately 20% of the city''s AIDS cases and 35% of the cohort (21, 40, 41). A large proportion of Montreal''s IDUs use injection cocaine, with 50 to 69% of subjects reporting cocaine as their injection drug of choice (4, 5, 9, 22, 23).Subjects with documented serological evidence of recent HIV-1 infection and a concurrent history of injection drug use were selected for study. These individuals had few or no reported risk factors for sexual HIV-1 acquisition. Clinical history and laboratory tests of HIV-1 viremia and antibody seroconversion were used to determine the Fiebig clinical stage (8) and to estimate the date of infection (Table (Table1).1). One subject was determined to be in Fiebig stage III, one subject was in Fiebig stage IV, five subjects were in Fiebig stage V, and three subjects were in Fiebig stage VI. We performed SGA-direct amplicon sequencing on stored plasma samples and obtained a total of 391 3′ half-genomes (median, 25 per subject; range, 19 to 167). Nine of these sequences contained large deletions or were G-to-A hypermutated and were excluded from subsequent analysis. Sequences were aligned, visually inspected using the Highlighter tool (www.hiv.lanl.gov/content/sequence/HIGHLIGHT/highlighter.html), and analyzed by neighbor-joining (NJ) phylogenetic-tree construction. A composite NJ tree of full-length gp160 env sequences from all 10 subjects (Fig. (Fig.1A)1A) revealed distinct patient-specific monophyletic lineages, each with high bootstrap support and separated from the others by a mean genetic distance of 10.79% (median, 11.29%; range, 3.00 to 13.42%). Maximum within-patient env gene diversity ranged from 0.23% to 3.34% (Table (Table1).1). Four subjects displayed distinctly lower within-patient maximum env diversities (0.23 to 0.49%) than the other six subjects (1.48% to 3.34%). The lower maximum env diversities in the former group are consistent with infection either by a single virus or by multiple closely related viruses, while the higher diversities can be explained only by transmission of more than one virus based on empirical observations (1, 13, 18, 24) and mathematical modeling (18, 20).Open in a separate windowFIG. 1.NJ trees and Highlighter plots of HIV-1 gp160 env sequences. (A) Composite tree of 382 gp160 env sequences from all study subjects. The numerals at the nodes indicate bootstrap values for which statistical support exceeded 70%. (B) Subject ACT54869022 sequences suggest productive infection by a single virus (V1). (C) Subject HDNDRPI032 sequences suggest productive infection by as many as three viruses. (D) Subject HDNDRPI001 sequences suggest productive infection by at least five viruses with extensive interlineage recombination. Sequences are color coded to indicate viral progeny from distinct transmitted/founder viruses. Recombinant virus sequences are depicted in black. Methods for SGA, sequencing, model analysis, Highlighter plotting, and identification of transmitted/founder virus lineages are described elsewhere (18, 20, 24, 44). The horizontal scale bars represent genetic distance. nt, nucleotide.

TABLE 1.

Subject demographics and HIV-1 envelope analysis results
Subject identifierAge (yr)SexaFiebig stageEstimated no. of days postinfectionbCD4 countPlasma viral load (log)No. of SGA ampliconsDiversity of env genes (%)c
No. of transmitted/ founder viruses
MeanInterquartile rangeMaximumdModel predictionePhylogenetic estimatef
HDNDRPI03447MIII292407.881631.070.553.34>116
HDNDRPI02918FIV484404.34290.160.150.4911
HTM38524MV624065.37220.120.080.2711
CQLDR0342MV66NDg5.01210.080.080.2311
HDNDRPI00136MV286905.94250.900.631.91>15
HTM31939MV685204.43250.770.461.54>13
HDNDRPI03237MV731,0403.53191.482.993.34>13
ACTDM58020839MVI933874.53301.170.972.64>13
ACT5486902228MVI687233.43270.070.040.2411
PSL02446MVI823404.46210.820.631.57>13
Open in a separate windowaM, male; F, female.bNumbers of days postinfection were estimated on the basis of serological markers, clinical symptoms, or a history of a high-risk behavior leading to virus exposure.cDiversity measurements determined by PAUP* analysis.dThe model prediction of the maximum achievable env diversity 100 days after transmission is 0.60% (95% CI, 0.54 to 0.68%). Diversity values exceeding this range imply transmission and productive infection by more than one virus. Diversity values less than 0.54% can be explained by transmission of one virus or of multiple closely related viruses (18).eModel described in Keele et al. (18).fMinimum estimate of transmitted/founder viruses.gND, not determined.An example of productive clinical infection by a single virus is shown in phylogenetic tree and Highlighter plots from subject ACT54869022 (Fig. (Fig.1B).1B). A similar phylogenetic pattern of single-variant transmission was found in 4 of 10 IDU subjects (Table (Table1).1). Examples of multivariant transmission are shown for subject HDNDRPI032, for whom there was evidence of infection by 3 transmitted/founder viruses (Fig. (Fig.1C)1C) and for subject HDNDRPI001, for whom there was evidence of infection by at least 5 transmitted/founder viruses (Fig. (Fig.1D).1D). One IDU subject, HDNDRPI034, had evidence of multivariant transmission to an extent not previously seen in any of 225 subjects who acquired their infection by mucosal routes (1, 13, 18, 24) or in any of 13 IDUs, as recently reported by Masharsky and colleagues (29). We greatly extended the depth of our analysis in this subject to include 163 3′ half-genome sequences in order to increase the sensitivity of detection of low-frequency viral variants. Power calculations indicated that a sample size of 163 sequences gave us a >95% probability of sampling minor variants comprising as little as 2% of the virus population. By this approach, we found evidence of productive infection by at least 16 genetically distinct viruses (Fig. (Fig.2).2). Fourteen of these could be identified unambiguously based on the presence of discrete low-diversity viral lineages, each consisting of between 2 and 48 sequences. Two additional unique viral sequences with long branch lengths (3F8 and G10) exhibited diversity that was sufficiently great to indicate a distinct transmission event as opposed to divergence from other transmitted/founder lineages (see the legend to Fig. Fig.2).2). It is possible that still other unique sequences from this subject also represented transmitted/founder viruses, but we could not demonstrate this formally. We also could not determine if all 16 (or more) transmission events resulted from a single intravenous inoculation or from a series of inoculations separated by hours or days; however, it is likely that all transmitted viruses in this subject resulted from exposure to plasma from a single infected individual, since the maximum env diversity was only 3.34% (Fig. (Fig.1A).1A). It is also likely that transmission occurred within a brief window of time, since the period from transmission to the end of Fiebig stage III is typically only about 25 days (95% CI, 22 to 37 days) (18, 20) and the diversity observed in all transmitted/founder viral lineages in subject HDNDRPI034 was exceedingly low, consistent with model predictions for subjects with very recent infections (18, 20).Open in a separate windowFIG. 2.NJ tree and Highlighter plot of HIV-1 3′ half-genome sequences from subject HDNDRPI034. Sequences emanating from 16 transmitted/founder viruses are color coded. Fourteen transmitted/founder viral lineages comprised of 2 or more identical or nearly identical sequences could be readily distinguished from recombinant sequences (depicted in black), which invariably appeared as unique sequences containing interspersed segments shared with other transmitted/founder virus lineages. The two sequences with the longest branch lengths (3F8 and G10) were interpreted to represent rare progeny of discrete transmitted/founder viruses because their unique polymorphisms far exceeded the maximum diversity estimated to occur in the first 30 days of infection (0.22%; CI, 0.15 to 0.31%) (18) and far exceeded the diversity observed within the other transmitted/founder virus lineages. The horizontal scale bar represents genetic distance.Lastly, we compared the multiplicity of HIV-1 transmission in the Montreal IDU subjects with that of non-IDU subjects for whom identical SGA methods had been employed. In this combined-cohort analysis, we found the frequency of multiple-variant transmission in heterosexuals to be 19% (34 of 175) and in MSM 38% (19 of 50) (Table (Table2)2) (24). The current study was powered to detect a >2-fold difference in multivariant transmission between IDUs and heterosexual subjects; in fact, we observed a 3-fold-higher frequency of multiple-variant transmission in Montreal IDUs (6 of 10 subjects [60%]) than in heterosexuals (odds ratio, 6.14; 95% CI, 1.37 to 31.27; Fisher exact test, P = 0.008) and a 1.5-fold-higher frequency in Montreal IDUs than in MSM (odds ratio, 2.41; 95% CI, 0.50 to 13.20; P = 0.294, not significant). In addition, we found that the range of numbers of transmitted/founder viruses was greater in IDUs (range, 1 to 16 viruses; median, 3) than in either heterosexuals (range, 1 to 6 viruses; median, 1) or MSM (range, 1 to 10 viruses; median, 1). The finding of larger numbers of transmitted/founder viruses in IDUs was not simply the result of more intensive sampling, since the numbers of sequences analyzed in all studies were comparable. Moreover, it is notable that in studies reported elsewhere, we sampled as many as 239 sequences by SGA or as many as 500,000 sequences by 454 pyrosequencing from four acutely infected MSM subjects and in each case found evidence of productive clinical infection by only a single virus (24; W. Fischer, B. Keele, G. Shaw, and B. Korber, unpublished). These results thus suggest that IDUs may be infected by more viruses and by a greater range of viruses than is the case following mucosal transmission. On this count, our findings differ from those reported by Masharsky and coworkers for an IDU cohort from St. Petersburg, Russia (29). Their study found a low frequency of multiple virus transmissions (31%), not significantly different from that of acutely infected heterosexuals, and a low number of transmitted/founder viruses (range, 1 to 3 viruses; median, 1). Because the SGA methods employed in both studies were identical, the numbers of sequences analyzed per subject were comparable (median of 25 sequences in Montreal versus 33 in St. Petersburg), and because the discriminating power of the SGA-direct sequencing method was sufficient to distinguish transmitted/founder viruses differing by as few as 3 nucleotides, or <0.1% of nucleotides (Fig. (Fig.2,2, compare lineages V4 and V5), it is unlikely that differences in the genetic diversity of HIV-1 in the two IDU populations explain the differences in findings between the two studies. Instead, we suspect that the explanation lies in the small cohort sizes (10 versus 13 subjects) and the particular risk behaviors of the IDUs in each cohort. The Russian cohort is heavily weighted toward heroine use, whereas the Montreal cohort is weighted toward injection cocaine use, the latter being associated with more frequent drug administration and the attendant infection risks of needle sharing (4).

TABLE 2.

Multiplicity of HIV-1 infection in IDU, heterosexual, and MSM subjects
CohortReferenceVirus subtypeTotal no. of subjectsSingle-variant transmission
Multiple-variant transmission
P valueOdds ratio95% CIMedianRange
No. of subjects% of totalNo. of subjects% of total
HeterosexualsKeele et al. (18)B796582.301417.7011-4
Abrahams et al. (1)C695478.301521.7011-5
Haaland et al. (13)A or C272281.50518.5011-6
Total17514180.603419.400.008a6.141.37-31.2711-6
MSMKeele et al. (18)B221359.10940.9011-6
Li et al. (24)B281864.301035.7011-10
Total503162.001938.000.294b2.410.50-13.2011-10
IDUsBarB10440.00660.0031-16
Open in a separate windowaFisher''s exact test of multiple-variant transmission in heterosexuals versus in IDUs.bFisher''s exact test of multiple-variant transmission in MSM versus in IDUs.The results from the present study indicate that transmission of HIV-1 to IDUs can be associated with a high frequency of multiple-variant transmission and a broad range in the numbers of transmitted viruses. This wide variation in the multiplicity of HIV-1 infection in IDUs is likely due to the absence of a mucosal barrier to virus transmission (12, 19) and differences in the virus inocula (27, 29, 32, 39). The findings substantiate concerns raised in recent HIV-1 vaccine efficacy trials that different vaccine candidates may be more efficacious in preventing infection by some exposure routes than by others (7, 10, 33, 37). They further suggest that biological comparisons of molecularly cloned transmitted/founder viruses responsible for vaginal, rectal, penile, and intravenous infection could facilitate a mechanistic understanding of HIV-1 transmission and vaccine prevention (24, 44).  相似文献   

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