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1.
All cultivated Thermotogales are thermophiles or hyperthermophiles. However, optimized 16S rRNA primers successfully amplified Thermotogales sequences from temperate hydrocarbon-impacted sites, mesothermic oil reservoirs, and enrichment cultures incubated at <46°C. We conclude that distinct Thermotogales lineages commonly inhabit low-temperature environments but may be underreported, likely due to “universal” 16S rRNA gene primer bias.Thermotogales, a bacterial group in which all cultivated members are anaerobic thermophiles or hyperthermophiles (5), are rarely detected in anoxic mesothermic environments, yet their presence in corresponding enrichment cultures, bioreactors, and fermentors has been observed using metagenomic methods and 16S rRNA gene amplification (6) (see Table S1 in the supplemental material). The most commonly detected lineage is informally designated here “mesotoga M1” (see Table S1 in the supplemental material). PCR experiments indicated that mesotoga M1 sequences amplified inconsistently using “universal” 16S rRNA gene primers, perhaps explaining their poor detection in DNA isolated from environmental samples (see text and Table S2 in the supplemental material). We therefore designed three 16S rRNA PCR primer sets (Table (Table1)1) targeting mesotoga M1 bacteria and their closest cultivated relative, Kosmotoga olearia. Primer set A was the most successful set, detecting a wider diversity of Thermotogales sequences than set B and being more Thermotogales-specific than primer set C (Table (Table22).

TABLE 1.

Primers targeting mesotoga M1 bacteria constructed and used in this study
PrimerSequence (5′ to 3′)Position in mesotoga 16S rRNA geneNo. of heterogeneity hot spotsaPotential primer match in other Thermotogales lineages
Primer set A1 (helix 17)
    NMes16S.286FCGGCCACAAGGAYACTGAGA286Perfect match in Kosmotoga olearia. The last 7 or 8 nucleotides at the 3′ end are conserved in other Thermotogales lineages.
    NMes16S.786RTGAACATCGTTTAGGGCCAG786One 5′ mismatch in Kosmotoga olearia and Petrotoga mobilis; 2-4 internal and 5′ mismatches in other lineages
Primer set BNone
    BaltD.42FATCACTGGGCGTAAAGGGAG540Perfect match in Kosmotoga olearia; one or two 3′ mismatches in most other Thermotogales lineages
    BaltD.494RGTGGTCGTTCCTCTTTCAAT992No match in other Thermotogaleslineages. The primer is located in heterogeneity hot spot helices 33 and 34. This primer also fails to amplify some mesotoga M1 sequences.
Primer set C9 (all 9 regions)
    TSSU-3FTATGGAGGGTTTGATCCTGG3Perfect match in Thermotoga spp., Kosmotoga olearia, and Petrotoga mobilis; two or three 5′ mismatches in other Thermotogales lineages; one 5′ mismatch to mesotoga M1 16S rRNA genes
    Mes16S.RACCAACTCGGGTGGCTTGAC1390One 5′ mismatch in Kosmotoga olearia; 1-3 internal or 5′ mismatches in other Thermotogales lineages
Open in a separate windowaHeterogeneity hot spots identified in reference 1.

TABLE 2.

Mesotoga clade sequences detected in environmental samples and enrichment cultures screened in this studya
Site (abbreviation)Temp in situ(°C)WaterfloodedEnvironmental samplesb
Enrichment cultures
Primer set A
Primer set B
Primer set C
Thermotogalesdetected by primer setc:
Lineage(s) detected
No. of OTUs (no. of clones)LineageNo. of OTUs (no. of clones)LineageNo. of OTUs (no. of clones)LineageABC
Sidney Tar Ponds sediment (TAR)TemperateNA1 (5)M11M1+++M1, M2, M5
Oil sands settling basin tailings (05mlsb)∼12dNA1 (6)M1+M1
Grosmont A produced water (GrosA)20No1 (15)M11 (22)M12 (14)M1+++M1
Foster Creek produced water (FC)14No1 (21)M11 (23)M11 (1)M1+NDM1
Oil field D wellhead water (DWH)e,f52-53gYes1 (14)Kosmotogai1 (6)M1i1 (1)KosmotogaiNANANANA
Oil field D FWKO water (DF)f,h20-30Yes1 (45)Kosmotogai1 (17)M1i++M1, Kosmotoga, Petrotoga
Oil field H FWKO water (HF)j30-32Yes7 (59)M1, M2, M3, M4, Kosmotoga1 (29)M1++M1, Petrotoga
Oil field H satellite water (HSAT)e,j41 and 50gYes1 (8)M12 (16)Kosmotoga, ThermotogaNANANANA
Oil field H wellhead water (HWH)e,j41 and 50gYesNANANANA+++M1, Petrotoga
Open in a separate windowaSee the supplemental material for site and methodological details. NA, not applicable; ND, not determined.bThe number of OTUs observed at a 0.01 distance cutoff is given for each primer set. The numbers of clones with Thermotogales sequences are in parentheses. —, PCR was attempted but no Thermotogales sequences were obtained or the PCR consistently failed.c+, sequence(s) detected; −, not detected. For more information on the enrichments, see the text and Table S3 in the supplemental material.dFrom April to May 2004, the temperature at the depth where the sample was taken was 12°C (7).eThere were no water samples from DWH and HSAT available for enrichment cultures, and no DNA was available from HWH.fThis reservoir has been treated with biocides; moreover, at this site, the water is filtered before being reinjected into the reservoir.gTemperatures of the oil pool where the water sample was obtained. The HSAT facility receives water from two oil pools, one at 41°C and one at 50°C.hWe screened DNA from samples taken in 2006 and 2008 but detected the same sequences in both, so sequences from the two samples were pooled.iThe mesotoga M1 and Kosmotoga sequences from DWH and DF were >99% similar and were assembled into one sequence in Fig. Fig.11.jThis reservoir has been injected with water from a neighboring oil reservoir.Since the putative mesophilic Thermotogales have been overwhelmingly associated with polluted and hydrocarbon-impacted environments and mesothermic oil reservoirs are the only natural environments where mesotoga M1 sequences previously were detected (see Table S1 in the supplemental material), we selected four oil reservoirs with in situ temperatures of 14°C to 53°C and two temperate, chronically hydrocarbon-impacted sites for analysis (Table (Table2).2). Total community DNA was extracted, the 16S rRNA genes were amplified, cloned, and sequenced as described in the supplemental material.  相似文献   

2.
Escherichia coli isolates (72 commensal and 10 O157:H7 isolates) were compared with regard to physiological and growth parameters related to their ability to survive and persist in the gastrointestinal tract and found to be similar. We propose that nonhuman hosts in E. coli O157:H7 strains function similarly to other E. coli strains in regard to attributes relevant to gastrointestinal colonization.Escherichia coli is well known for its ecological versatility (15). A life cycle which includes both gastrointestinal and environmental stages has been stressed by both Savageau (15) and Adamowicz et al. (1). The gastrointestinal stage would be subjected to acid and detergent stress. The environmental stage is implicit in E. coli having transport systems for fungal siderophores (4) as well as pyrroloquinoline quinone-dependent periplasmic glucose utilization (1) because their presence indicates evolution in a location containing fungal siderophores and pyrroloquinoline quinone (1).Since its recognition as a food-borne pathogen, there have been numerous outbreaks of food-borne infection due to E. coli O157:H7, in both ground beef and vegetable crops (6, 13). Cattle are widely considered to be the primary reservoir of E. coli O157:H7 (14), but E. coli O157:H7 does not appear to cause disease in cattle. To what extent is E. coli O157:H7 physiologically unique compared to the other naturally occurring E. coli strains? We feel that the uniqueness of E. coli O157:H7 should be evaluated against a backdrop of other wild-type E. coli strains, and in this regard, we chose the 72-strain ECOR reference collection originally described by Ochman and Selander (10). These strains were chosen from a collection of 2,600 E. coli isolates to provide diversity with regard to host species, geographical distribution, and electromorph profiles at 11 enzyme loci (10).In our study we compared the 72 strains of the ECOR collection against 10 strains of E. coli O157:H7 and six strains of E. coli which had been in laboratory use for many years (Table (Table1).1). The in vitro comparisons were made with regard to factors potentially relevant to the bacteria''s ability to colonize animal guts, i.e., acid tolerance, detergent tolerance, and the presence of the Entner-Doudoroff (ED) pathway (Table (Table2).2). Our longstanding interest in the ED pathway (11) derives in part from work by Paul Cohen''s group (16, 17) showing that the ED pathway is important for E. coli colonization of the mouse large intestine. Growth was assessed by replica plating 88 strains of E. coli under 40 conditions (Table (Table2).2). These included two LB controls (aerobic and anaerobic), 14 for detergent stress (sodium dodecyl sulfate [SDS], hexadecyltrimethylammonium bromide [CTAB], and benzalkonium chloride, both aerobic and anaerobic), 16 for acid stress (pH 6.5, 6.0, 5.0, 4.6, 4.3, 4.2, 4.1, and 4.0), four for the ability to grow in a defined minimal medium (M63 glucose salts with and without thiamine), and four for the presence or absence of a functional ED pathway (M63 with gluconate or glucuronate). All tests were done with duplicate plates in two or three separate trials. The data are available in Tables S1 to S14 in the supplemental material, and they are summarized in Table Table22.

TABLE 1.

E. coli strains used in this study
E. coli strain (n)Source
ECOR strains (72)Thomas Whittman
Laboratory adapted (6)
    K-12 DavisPaul Blum
    CG5C 4401Paul Blum
    K-12 StanfordPaul Blum
    W3110Paul Blum
    BTyler Kokjohn
    AB 1157Tyler Kokjohn
O157:H7 (10)
    FRIK 528Andrew Benson
    ATCC 43895Andrew Benson
    MC 1061Andrew Benson
    C536Tim Cebula
    C503Tim Cebula
    C535Tim Cebula
    ATCC 43889William Cray, Jr.
    ATCC 43890William Cray, Jr.
    ATCC 43888Willaim Cray, Jr.
    ATCC 43894William Cray, Jr.
Open in a separate window

TABLE 2.

Physiological comparison of 88 strains of Escherichia coli
Growth medium or conditionOxygencNo. of strains with type of growthb
ECOR strains (n = 72)
Laboratory strains (n = 6)
O157:H7 strains (n = 10)
GoodPoorNoneVariableGoodPoorNoneVariableGoodPoorNoneVariable
LB controlaBoth72000600010000
1% SDSAerobic6930060008002
5% SDSAerobic6840060008200
1% SDSAnaerobic53154023101702
5% SDSAnaerobic0684004200704
CTABd (all)Both00720006000100
0.05% BACAerobic31158202220091
0.2% BACAerobic01710105000100
0.05% BACAnaerobic2367001500091
0.2% BACAnaerobic00720006000100
pH 6.5Both72000600010000
pH 6Both72000600010000
pH 5Both7020060009001
pH 4.6Both70200600010000
pH 4.3Aerobic14015731203205
pH 4.3Anaerobic6930031201100
pH 4.1 or 4.2Aerobic00720NDgND
pH 4.0Both0072000600091
M63 with supplemente
    GlucoseAerobicf6912050109010
    GlucoseAnaerobicf7002050109010
    GluconateBoth6912050109010
    GlucuronateAerobic6822050109010
    GlucuronateAnaerobic6912050109010
Open in a separate windowaEight LB controls were run, two for each set of LB experiments: SDS, CTAB, benzalkonium chloride (BAC), and pH stress.bGrowth was measured as either +++, +, or 0 (good, poor, and none, respectively), with +++ being the growth achieved on the LB control plates. “Variable” means that two or three replicates did not agree. All experiments were done at 37°C.c“Anaerobic” refers to use of an Oxoid anaerobic chamber. Aerobic and anaerobic growth data are presented together when the results were identical and separately when the results were not the same or the anaerobic set had not been done. LB plates were measured after 1 (aerobic) or 2 (anaerobic) days, and the M63 plates were measured after 2 or 3 days.dCTAB used at 0.05, 0.2%, and 0.4%.eM63 defined medium (3) was supplemented with glucose, gluconate, or glucuronate, all at 0.2%.fIdentical results were obtained with and without 0.0001% thiamine.gND, not determined.  相似文献   

3.
Canada geese (Branta canadensis) are prevalent in North America and may contribute to fecal pollution of water systems where they congregate. This work provides two novel real-time PCR assays (CGOF1-Bac and CGOF2-Bac) allowing for the specific and sensitive detection of Bacteroides 16S rRNA gene markers present within Canada goose feces.The Canada goose (Branta canadensis) is a prevalent waterfowl species in North America. The population density of Canada geese has doubled during the past 15 years, and the population was estimated to be close to 3 million in 2007 (4). Canada geese often congregate within urban settings, likely due to available water sources, predator-free grasslands, and readily available food supplied by humans (6). They are suspected to contribute to pollution of aquatic environments due to the large amounts of fecal matter that can be transported into the water. This can create a public health threat if the fecal droppings contain pathogenic microorganisms (6, 7, 9, 10, 12, 13, 19). Therefore, tracking transient fecal pollution of water due to fecal inputs from waterfowl, such as Canada geese, is of importance for protecting public health.PCR detection of host-specific 16S rRNA gene sequences from Bacteroidales of fecal origin has been described as a promising microbial source-tracking (MST) approach due to its rapidity and high specificity (2, 3). Recently, Lu et al. (15) characterized the fecal microbial community from Canada geese by constructing a 16S rRNA gene sequence database using primers designed to amplify all bacterial 16S rRNA gene sequences. The authors reported that the majority of the 16S rRNA gene sequences obtained were related to Clostridia or Bacilli and to a lesser degree Bacteroidetes, which represent possible targets for host-specific source-tracking assays.The main objective of this study was to identify novel Bacteroidales 16S rRNA gene sequences that are specific to Canada goose feces and design primers and TaqMan fluorescent probes for sensitive and specific quantification of Canada goose fecal contamination in water sources.Primers 32F and 708R from Bernhard and Field (2) were used to construct a Bacteroidales-specific 16S rRNA gene clone library from Canada goose fecal samples (n = 15) collected from grass lawns surrounding Wascana Lake (Regina, SK, Canada) in May 2009 (for a detailed protocol, see File S1 in the supplemental material). Two hundred eighty-eight clones were randomly selected and subjected to DNA sequencing (at the Plant Biotechnology Institute DNA Technologies Unit, Saskatoon, SK, Canada). Representative sequences of each operational taxonomic unit (OTU) were recovered using an approach similar to that described by Mieszkin et al. (16). Sequences that were less than 93% similar to 16S rRNA gene sequences from nontarget host species in GenBank were used in multiple alignments to identify regions of DNA sequence that were putatively goose specific. Subsequently, two TaqMan fluorescent probe sets (targeting markers designated CGOF1-Bac and CGOF2-Bac) were designed using the RealTimeDesign software provided by Biosearch Technologies (http://www.biosearchtech.com/). The newly designed primer and probe set for the CGOF1-Bac assay included CG1F (5′-GTAGGCCGTGTTTTAAGTCAGC-3′) and CG1R (5′-AGTTCCGCCTGCCTTGTCTA-3′) and a TaqMan probe (5′-6-carboxyfluorescein [FAM]-CCGTGCCGTTATACTGAGACACTTGAG-Black Hole Quencher 1 [BHQ-1]-3′), and the CGOF2-Bac assay had primers CG2F (5′-ACTCAGGGATAGCCTTTCGA-3′) and CG2R (5′-ACCGATGAATCTTTCTTTGTCTCC-3′) and a TaqMan probe (5′-FAM-AATACCTGATGCCTTTGTTTCCCTGCA-BHQ-1-3′). Oligonucleotide specificities for the Canada goose-associated Bacteroides 16S rRNA primers were verified through in silico analysis using BLASTN (1) and the probe match program of the Ribosomal Database Project (release 10) (5). Host specificity was further confirmed using DNA extracts from 6 raw human sewage samples from various geographical locations in Saskatchewan and 386 fecal samples originating from 17 different animal species in Saskatchewan, including samples from Canada geese (n = 101) (Table (Table1).1). An existing nested PCR assay for detecting Canada goose feces (15) (targeting genetic marker CG-Prev f5) (see Table S1 in the supplemental material) was also tested for specificity using the individual fecal and raw sewage samples (Table (Table1).1). All fecal DNA extracts were obtained from 0.25 g of fecal material by using the PowerSoil DNA extraction kit (Mo Bio Inc., Carlsbad, CA) (File S1 in the supplemental material provides details on the sample collection).

TABLE 1.

Specificities of the CGOF1-Bac, CGOF2-Bac, and CG-Prev f5 PCR assays for different species present in Saskatchewan, Canada
Host group or sample typeNo. of samplesNo. positive for Bacteroidales marker:
CGOF1-BacCGOF2-BacCG-Prev f5All-Bac
Individual human feces2500125
Raw human sewage60006
Cows4100041
Pigs4800148
Chickens3400834
Geese10158515995a
Gulls1600614
Pigeons2510222
Ducks1000010
Swans10001
Moose1000010
Deer
    White tailed1000010
    Mule1000010
    Fallow1000010
Caribou1000010
Bison1000010
Goats1000010
Horses1500015
Total392595177381
Open in a separate windowaThe 6 goose samples that tested negative for the All-Bac marker also tested negative for the three goose markers.The majority of the Canada goose feces analyzed in this study (94%; 95 of 101) carried the Bacteroidales order-specific genetic marker designated All-Bac, with a relatively high median concentration of 8.2 log10 copies g1 wet feces (Table (Table11 and Fig. Fig.1).1). The high prevalence and abundance of Bacteroidales in Canada goose feces suggested that detecting members of this order could be useful in identifying fecal contamination associated with Canada goose populations.Open in a separate windowFIG. 1.Concentrations of the Bacteroidales (All-Bac, CGOF1-Bac, and CGOF2-Bac) genetic markers in feces from various individual Canada geese.The composition of the Bacteroidales community in Canada goose feces (n = 15) was found to be relatively diverse since 52 OTUs (with a cutoff of 98% similarity) were identified among 211 nonchimeric 16S rRNA gene sequences. Phylogenetic analysis of the 52 OTUs (labeled CGOF1 to CGOF52) revealed that 43 (representing 84% of the 16S rRNA gene sequences) were Bacteroides like and that 9 (representing 16% of the 16S rRNA gene sequences) were likely to be members of the Prevotella-specific cluster (see Fig. S2 in the supplemental material). Similarly, Jeter et al. (11) reported that 75.7% of the Bacteroidales 16S rRNA clone library sequences generated from goose fecal samples were Bacteroides like. The majority of the Bacteroides- and Prevotella-like OTUs were dispersed among a wide range of previously characterized sequences from various hosts and did not occur in distinct clusters suitable for the design of Canada goose-associated real-time quantitative PCR (qPCR) assays (see Fig. S2 in the supplemental material). However, two single Bacteroides-like OTU sequences (CGOF1 and CGOF2) contained putative goose-specific DNA regions that were identified by in silico analysis (using BLASTN, the probe match program of the Ribosomal Database Project, and multiple alignment). The primers and probe for the CGOF1-Bac and CGOF2-Bac assays were designed with no mismatches to the clones CGOF1 and CGOF2, respectively.The CGOF2-Bac assay demonstrated no cross-amplification with fecal DNA from other host groups, while cross-amplification for the CGOF1-Bac assay was limited to one pigeon fecal sample (1 of 25, i.e., 4% of the samples) (Table (Table1).1). Since the abundance in the pigeon sample was low (3.3 log10 marker copies g1 feces) and detection occurred late in the qPCR (with a threshold cycle [CT] value of 37.1), it is unlikely that this false amplification would negatively impact the use of the assay as a tool for detection of Canada goose-specific fecal pollution in environmental samples. In comparison, the nested PCR CG-Prev f5 assay described by Lu and colleagues (15) demonstrated non-host-specific DNA amplification with fecal DNA samples from several animals, including samples from humans, pigeons, gulls, and agriculturally relevant pigs and chickens (Table (Table11).Both CGOF1-Bac and CGOF2-Bac assays showed limits of quantification (less than 10 copies of target DNA per reaction) similar to those of other host-specific Bacteroidales real-time qPCR assays (14, 16, 18). The sensitivities of the CGOF1-Bac and CGOF2-Bac assays were 57% (with 58 of 101 samples testing positive) and 50% (with 51 of 101 samples testing positive) for Canada goose feces, respectively (Table (Table1).1). A similar sensitivity of 58% (with 59 of 101 samples testing positive) was obtained using the CG-Prev f5 PCR assay. The combined use of the three assays increased the detection level to 72% (73 of 101) (Fig. (Fig.2).2). Importantly, all markers were detected within groups of Canada goose feces collected each month from May to September, indicating relative temporal stability of the markers. The CG-Prev f5 PCR assay is an end point assay, and therefore the abundance of the gene marker in Canada goose fecal samples could not be determined. However, development of the CGOF1-Bac and CGOF2-Bac qPCR approach allowed for the quantification of the host-specific CGOF1-Bac and CGOF2-Bac markers. In the feces of some individual Canada geese, the concentrations of CGOF1-Bac and CGOF2-Bac were high, reaching levels up to 8.8 and 7.9 log10 copies g1, respectively (Fig. (Fig.11).Open in a separate windowFIG. 2.Venn diagram for Canada goose fecal samples testing positive with the CGOF1-Bac, CGOF2-Bac, and/or CG-Prev f5 PCR assay. The number outside the circles indicates the number of Canada goose fecal samples for which none of the markers were detected.The potential of the Canada goose-specific Bacteroides qPCR assays to detect Canada goose fecal pollution in an environmental context was tested using water samples collected weekly during September to November 2009 from 8 shoreline sampling sites at Wascana Lake (see File S1 and Fig. S1 in the supplemental material). Wascana Lake is an urban lake, located in the center of Regina, that is routinely frequented by Canada geese. In brief, a single water sample of approximately 1 liter was taken from the surface water at each sampling site. Each water sample was analyzed for Escherichia coli enumeration using the Colilert-18/Quanti-Tray detection system (IDEXX Laboratories, Westbrook, ME) (8) and subjected to DNA extraction (with a PowerSoil DNA extraction kit [Mo Bio Inc., Carlsbad, CA]) for the detection of Bacteroidales 16S rRNA genetic markers using the Bacteroidales order-specific (All-Bac) qPCR assay (14), the two Canada goose-specific (CGOF1-Bac and CGOF2-Bac) qPCR assays developed in this study, and the human-specific (BacH) qPCR assay (17). All real-time and conventional PCR procedures as well as subsequent data analysis are described in the supplemental material and methods. The E. coli and All-Bac quantification data demonstrated that Wascana Lake was regularly subjected to some form of fecal pollution (Table (Table2).2). The All-Bac genetic marker was consistently detected in high concentrations (6 to 7 log10 copies 100 ml1) in all the water samples, while E. coli concentrations fluctuated according to the sampling dates and sites, ranging from 0 to a most probable number (MPN) of more than 2,000 100 ml1. High concentrations of E. coli were consistently observed when near-shore water experienced strong wave action under windy conditions or when dense communities of birds were present at a given site and time point.

TABLE 2.

Levels of E. coli and incidences of the Canada goose-specific (CGOF1-Bac and CGOF2-Bac), human-specific (BacH), and generic (All-Bac) Bacteroidales 16S rRNA markers at the different Wascana Lake sites sampled weeklya
SiteE. coli
All-Bac
CGOF1-Bac
CGOF2-Bac
BacH
No. of positive water samples/total no. of samples analyzed (%)Min level-max level (MPN 100 ml−1)Mean level (MPN 100 ml−1)No. of positive water samples/total no. of samples analyzed (%)Min level-max level (log copies 100 ml−1)Mean level (log copies 100 ml−1)No. of positive water samples/total no. of samples analyzed (%)Min level-max level (log copies 100 ml−1)Mean level (log copies 100 ml−1)No. of positive water samples/total no. of samples analyzed (%)Min level-max level (log copies 100 ml−1)Mean level (log copies 100 ml−1)No. of positive water samples/total no. of samples analyzedMin level-max level (log copies 100 ml−1)Mean level (log copies 100 ml−1)
W18/8 (100)6-19671.18/8 (100)6.2-8.16.96/8 (75)0-4.72.44/8 (50)0-41.72/80-3.71.7
W29/10 (90)0-1,12019410/10 (100)5.8-6.86.49/10 (90)0-3.72.68/10 (80)0-3.32.20/1000
W310/10 (100)6-1,55053410/10 (100)6-7.8710/10 (100)2.9-4.83.810/10 (100)2-4.53.40/1000
W410/10 (100)16-1,73252910/10 (100)6.4-7.6710/10 (100)3.2-4.63.910/10 (100)2.8-4.33.40/1000
W510/10 (100)2-2,42068710/10 (100)5.5-6.96.37/10 (70)0-3.21.75/10 (50)0-3.11.20/1000
W610/10 (100)3-1,99038910/10 (100)5.5-76.39/10 (90)0-4.32.86/10 (60)0-5.121/100-3.41.3
W77/7 (100)5-2,4204457/7 (100)5.7-7.876/7 (86)0-3.82.65/7 (71)0-4.42.42/70-5.12.8
W810/10 (100)17-98016010/10 (100)6.3-8.67.18/10 (80)0-4.62.87/10 (70)0-4.42.30/1000
Open in a separate windowaMin, minimum; max, maximum.The frequent detection of the genetic markers CGOF1-Bac (in 65 of 75 water samples [87%]), CGOF2-Bac (in 55 of 75 samples [73%]), and CG-Prev f5 (in 60 of 75 samples [79%]) and the infrequent detection of the human-specific Bacteroidales 16S rRNA gene marker BacH (17) (in 5 of 75 water samples [7%[) confirmed that Canada geese significantly contributed to the fecal pollution in Wascana Lake during the sampling period. Highest mean concentrations of both CGOF1-Bac and CGOF2-Bac markers were obtained at the sampling sites W3 (3.8 and 3.9 log10 copies 100 ml1) and W4 (3.4 log10 copies 100 ml1 for both), which are heavily frequented by Canada geese (Table (Table2),2), further confirming their significant contribution to fecal pollution at these particular sites. It is worth noting that concentrations of the CGOF1-Bac and CGOF2-Bac markers in water samples displayed a significant positive relationship with each other (correlation coefficient = 0.87; P < 0.0001), supporting the accuracy of both assays for identifying Canada goose-associated fecal pollution in freshwater.In conclusion, the CGOF1-Bac and CGOF2-Bac qPCR assays developed in this study are efficient tools for estimating freshwater fecal inputs from Canada goose populations. Preliminary results obtained during the course of the present study also confirmed that Canada geese can serve as reservoirs of Salmonella and Campylobacter species (see Fig. S3 in the supplemental material). Therefore, future work will investigate the cooccurence of these enteric pathogens with the Canada goose fecal markers in the environment.  相似文献   

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This work demonstrates that Vibrio vulnificus biotype 2, serovar E, an eel pathogen able to infect humans, can become resistant to quinolone by specific mutations in gyrA (substitution of isoleucine for serine at position 83) and to some fluoroquinolones by additional mutations in parC (substitution of lysine for serine at position 85). Thus, to avoid the selection of resistant strains that are potentially pathogenic for humans, antibiotics other than quinolones must be used to treat vibriosis on farms.Vibrio vulnificus is an aquatic bacterium from warm and tropical ecosystems that causes vibriosis in humans and fish (http://www.cdc.gov/nczved/dfbmd/disease_listing/vibriov_gi.html) (33). The species is heterogeneous and has been subdivided into three biotypes and more than eight serovars (6, 15, 33; our unpublished results). While biotypes 1 and 3 are innocuous for fish, biotype 2 can infect nonimmune fish, mainly eels, by colonizing the gills, invading the bloodstream, and causing death by septicemia (23). The disease is rapidly transmitted through water and can result in significant economic losses to fish farmers. Surviving eels are immune to the disease and can act as carriers, transmitting vibriosis between farms. Interestingly, biotype 2 isolates belonging to serovar E have been isolated from human infections, suggesting that serovar E is zoonotic (2). This serovar is also the most virulent for fish and has been responsible for the closure of several farms due to massive losses of fish. A vaccine, named Vulnivaccine, has been developed from serovar E isolates and has been successfully tested in the field (14). Although the vaccine provides fish with long-term protection from vibriosis, at present its use is restricted to Spain. For this reason, in many fish farms around the world, vibriosis is treated with antibiotics, which are usually added to the food or water.Quinolones are considered the most effective antibiotics against human and fish vibriosis (19, 21, 31). These antibiotics can persist for a long time in the environment (20), which could favor the emergence of resistant strains under selective pressure. In fact, spontaneous resistances to quinolones by chromosomal mutations have been described for some gram-negative bacteria (10, 11, 17, 24, 25, 26). Therefore, improper antibiotic treatment of eel vibriosis or inadequate residue elimination at farms could favor the emergence of human-pathogenic serovar E strains resistant to quinolones by spontaneous mutations. Thus, the main objective of the present work was to find out if the zoonotic serovar of biotype 2 can become quinolone resistant under selective pressure and determine the molecular basis of this resistance.Very few reports on resistance to antibiotics in V. vulnificus have been published; most of them have been performed with biotype 1 isolates. For this reason, the first task of this study was to determine the antibiotic resistance patterns in a wide collection of V. vulnificus strains belonging to the three biotypes that had been isolated worldwide from different sources (see Table S1 in the supplemental material). Isolates were screened for antimicrobial susceptibility to the antibiotics listed in Table S1 in the supplemental material by the agar diffusion disk procedure of Bauer et al. (5), according to the standard guideline (9). The resistance pattern found for each isolate is shown in Table S1 in the supplemental material. Less than 14% of isolates were sensitive to all the antibiotics tested, and more than 65% were resistant to more than one antibiotic, irrespective of their biotypes or serovars. The most frequent resistances were to ampicillin-sulbactam (SAM; 65.6% of the strains) and nitrofurantoin (F; 60.8% of the strains), and the least frequent were to tetracycline (12%) and oxytetracycline (8%). In addition, 15% of the strains were resistant to nalidixic acid (NAL) and oxolinic acid (OA), and 75% of these strains came from fish farms (see Table S1 in the supplemental material). Thus, high percentages of strains of the three biotypes were shown to be resistant to one or more antibiotics, with percentages similar to those found in nonbiotyped environmental V. vulnificus isolates from Asia and North America (4, 27, 34). In those studies, resistance to antibiotics could not be related to human contamination. However, the percentage of quinolone-resistant strains found in our study is higher than that reported in other ones, probably due to the inclusion of fish farm isolates, where the majority of quinolone-resistant strains were concentrated. This fact suggests that quinolone resistance could be related to human contamination due to the improper use of these drugs in therapy against fish diseases, as has been previously suggested (18, 20). Although no specific resistance pattern was associated with particular biotypes or serovars, we found certain differences in resistance distribution, as shown in Table Table1.1. In this respect, biotype 3 displayed the narrowest spectrum of resistances and biotype 1 the widest. The latter biotype encompassed the highest number of strains with multiresistance (see Table S1 in the supplemental material). Within biotype 2, there were differences among serovars, with quinolone resistance being restricted to the zoonotic serovar (Table (Table11).

TABLE 1.

Percentage of resistant strains distributed by biotypes and serovars
V. vulnificusNo. of isolatesResistance distribution (%) for indicated antibiotica
SAMCTXENALFOTOASXT-TMPTE
Biotype 14975.524.514.330.683.78.230.628.68.2
Biotype 2 (whole)7258.313.912.54.247.29.74.24.213.9
Biotype 2
    Serovar E3630.312.139.127.315.29.1321.2
    Serovar A231009.118.2077.3009.14.6
    Nontypeable82914.325057.114.30014.3
    Serovar I5100202002020000
Biotype 3510002008000020
Open in a separate windowaCTX, cefotaxime; E, erythromycin; OT, oxytetracycline; SXT-TMP, sulfamethoxazole-trimethoprim; TE, tetracycline.The origin of resistance to quinolones in the zoonotic serovar was further investigated. To this end, spontaneous mutants of sensitive strains were selected from colonies growing within the inhibition halo around OA or NAL disks. Two strains (strain CG100 of biotype 1 and strain CECT 4604 of biotype 2, serovar E) developed isolated colonies within the inhibition zone. These colonies were purified, and maintenance of resistance was confirmed by serial incubations on medium without antibiotics. Using the disk diffusion method, CG100 was shown to be resistant to SAM and F and CECT 4604 to F (see Table S1 in the supplemental material). The MICs for OA, NAL, flumequine (UB), and ciprofloxacin (CIP) were determined by using the microplate assay according to the recommendations of the Clinical and Laboratory Standards Institute and the European Committee for Antimicrobial Susceptibility Testing of the European Society of Clinical Microbiology and Infectious Diseases (8, 12) and interpreted according to the European Committee for Antimicrobial Susceptibility Testing of the European Society of Clinical Microbiology and Infectious Diseases (13). The MICs for OA and NAL and for the fluoroquinolones UB and CIP exhibited by the mutants and their counterparts are shown in Table Table2.2. The inhibition zone diameters correlated well with MICs (data not shown). Mutants FR1, FR2, FR3, and FR4 were resistant to NAL and sensitive to the remaining quinolones, although they showed higher resistances than their parental strains (Table (Table2).2). Thus, these four mutants showed increases of 32- to 128-fold for NAL MICs, 4- to 8-fold for UB MICs, and 16-fold for CIP MICs (Table (Table2).2). The fifth mutant, FR5, was resistant to the two tested quinolones and to UB, a narrow-spectrum fluoroquinolone. This mutant, although sensitive to CIP, multiplied its MIC for this drug by 128 with respect to the parental strain (Table (Table22).

TABLE 2.

MICs for quinolones and fluoroquinolones and mutations in gyrA, gyrB, and parC detected in naturally and artificially induced resistant strains
Strain(s)MIC (μg ml−1) for indicated antibioticb
Gene mutationa
gyrA
gyrB
parC
Position
Codon changeaa changePosition
Codon changeaa changePosition
Codon changeaa change
NALOAUBCIPntaantaantaa
CG1000.5 (S)0.125 (S)0.0625 (S)0.0078 (S)
FR116 (R)1 (S)0.25 (S)0.125 (S)24883AGT→ATTS→INCNCNCNCNCNCNCNC
FR216 (R)1 (S)0.25 (S)0.125 (S)24883AGT→ATTS→INCNCNCNCNCNCNCNC
CECT 46040.25 (S)0.0625 (S)0.0625 (S)0.0078 (S)
FR332 (R)2 (S)0.5 (S)0.125 (S)24883AGT→ATTS→INCNCNCNCNCNCNCNC
FR432 (R)2 (S)0.5 (S)0.125 (S)24883AGT→ATTS→INCNCNCNCNCNCNCNC
FR5256 (R)16 (R)16 (R)1 (S)24883AGT→ATTS→I1156386GCA→ACAA→T25485TCA→TTAS→L
1236412CAG→CACQ→H
CECT 4602128 (R)8 (R)64 (R)1 (S)24883AGT→ATTS→INCNCNCNC25485TCA→TTAS→L
CECT 4603, CECT 4606, CECT 4608, PD-5, PD-12, JE32 (R)2 (S)<1 (S)<1 (S)24883AGT→ATTS→INCNCNCNCNCNCNCNC
CECT 486264 (R)2 (S)2 (S)<1 (S)24983AGT→AGAS→RNCNCNCNCNCNCNCNC
A2, A4, A5, A6, A7, PD-1, PD-364-128 (R)2 (S)4 (S)<1 (S)24883AGT→ATTS→INCNCNCNC338113GCA→GTAA→V
V1128 (R)4 (S)4 (S)<1 (S)24883AGT→ATTS→I1274425GAG→GGGE→GNCNCNCNC
1314438AAC→AAAN→K
Open in a separate windowaMutations in a nucleotide (nt) that gave rise to a codon change and to a change in amino acids (aa) are indicated. NC, no change detected.bThe resistance (R) or sensitivity (S) against the antibiotic determined according to the Clinical and Laboratory Standards Institute and the European Committee for Antimicrobial Susceptibility Testing of the European Society of Clinical Microbiology and Infectious Diseases (9, 13) is indicated in parentheses.For other gram-negative pathogens, quinolone resistance relies on spontaneous mutations in the gyrA, gyrB, parC, and parE genes that occur in a specific region of the protein known as the quinolone resistance-determining region (QRDR) (1, 11, 17, 24, 25, 26, 28). To test the hypothesis that mutations in these genes could also produce quinolone resistance in V. vulnificus, the QRDRs of these genes were sequenced in the naturally resistant strains and in the two sensitive strains that had developed resistances by selective pressure in vitro. The genomic DNA was extracted (3), and the QRDRs of gyrA, gyrB, parE, and parC were amplified using the primers shown in Table Table3,3, which were designed from the published genomes of biotype 1 strains YJ016 and CMCP6 (7, 22). PCR products of the predicted size were sequenced in an ABI 3730 sequencer (Applied Biosystems). Analysis of the QRDR sequences for gyrA, gyrB, parC, and parE of the mutants and the naturally resistant strains revealed that all naturally resistant strains, except one, shared a specific mutation at nucleotide position 248 with the laboratory-induced mutants (Table (Table2).2). This mutation gave rise to a change from serine to isoleucine at amino acid position 83. The exception was a mutation in the adjacent nucleotide that gave rise to a substitution of arginine for serine at the same amino acid position (Table (Table2).2). All the isolates that were resistant to the quinolone NAL had a unique mutation in the gyrA gene, irrespective of whether resistance was acquired naturally or in the laboratory (Table (Table2).2). This result strongly suggests that a point mutation in gyrA that gives rise to a change in nucleotide position 83 can confer resistance to NAL in V. vulnificus biotypes 1 and 2 and that this mutation could be produced by selective pressure under natural conditions. gyrA mutations consisting of a change from serine 83 to isoleucine have also been described in isolates of Aeromonas from water (17) and in diseased fish isolates of Vibrio anguillarum (26). Similarly, replacement of serine by arginine at amino acid position 83 in diseased fish isolates of Yersinia ruckeri (16) suggests that this mechanism of quinolone resistance is widespread among gram-negative pathogens. In all cases, these single mutations were also related to increased resistance to other quinolones (OA) and fluoroquinolones (UB and CIP) (Table (Table2),2), although the mutants remained sensitive according to the standards of the Clinical and Laboratory Standards Institute and the European Committee for Antimicrobial Susceptibility Testing of the European Society of Clinical Microbiology and Infectious Diseases (9, 13). A total of 50% of the naturally resistant strains, all of them of biotype 1, showed additional mutations that affected parC (a change in amino acid position 113) or gyrB (changes in amino acids at positions 425 and 438) (Table (Table2).2). These strains exhibited higher MICs for OA and fluoroquinolones (Table (Table2),2), although they were still sensitive to these drugs (9, 13). Finally, one isolate of biotype 2, serovar E, which was naturally resistant to quinolones and UB, showed a mutation in parC that gave rise to a substitution of leucine for serine at amino acid position 85 (Table (Table2).2). This mutation was shared only with the laboratory-induced mutant, also a biotype 2, serovar E mutant, which was resistant to the fluoroquinolone UB. The same mutation in parC had been previously described in diseased fish isolates of V. anguillarum that were highly resistant to quinolones (28), but this had not been related to fluoroquinolone resistance in Vibrio spp. nor in other gram-negative bacteria. These results strongly suggest that resistance to fluoroquinolones in V. vulnificus is related to specific mutations in gyrA and parC and that mutations in different positions for parC or in gyrB could contribute to increased resistance to quinolones and fluoroquinolones. Our results also agree with previous studies confirming that the acquisition of higher quinolone resistance is more probable when arising from a gyrA parC double mutation than from a gyrA gyrB double mutation (29).

TABLE 3.

Oligonucleotides used in this study
PrimerSequenceAnnealing temp (°C)Size (bp)
GyrAFGGCAACGACTGGAATAAACC55.8416
GyrARCAGCCATCAATCACTTCCGTC
ParCFCGCAAGTTCACCGAAGATGC56.6411
ParCRGGCATCCGCAACTTCACG
GyrBFCGACTTCTGGTGACGATGCG57.4642
GyrBRGACCGATACCACAACCTAGTG
ParEFGCCAGGTAAGTTGACCGATTG56.8512
ParERCACCCAGACCTTTGAATCGTTG
Open in a separate windowFinally, the evolutionary history for each protein was inferred from previously published DNA sequences of the whole genes from different Vibrio species after multiple sequence alignment with MEGA4 software (32) by applying the neighbor-joining method (30) with the Poisson correction (35). The distance tree for each whole protein showed a topology similar to the phylogenetic tree based on 16S rRNA analysis, with the two isolates of V. vulnificus forming a single group, closely related to Vibrio parahaemolyticus, Vibrio cholerae, V. anguillarum, and Vibrio harveyi (see Fig. S1A in the supplemental material). A second analysis was performed with the QRDR sequences of the different mutants and isolates of V. vulnificus (GenBank accession numbers FJ379836 to FJ379927) to infer the intraspecies relationships (see Fig. S1B in the supplemental material). This analysis showed that QRDRs of gyrA, gyrB, parC, and parE were highly homogeneous within V. vulnificus.In summary, the zoonotic serovar of V. vulnificus can mutate spontaneously to gain quinolone resistance, under selective pressure in vitro, due to specific mutations in gyrA that involve a substitution of isoleucine for serine at amino acid position 83. This mutation appears in biotype 2, serovar E diseased-fish isolates and biotype 1 strains, mostly recovered from fish farms. An additional mutation in parC, resulting in a substitution of lysine for serine at amino acid position 85, seems to endow partial fluoroquinolone resistance on biotype 2, serovar E strains. This kind of double mutation is present in diseased-fish isolates of the zoonotic serovar but not in resistant biotype 1 isolates, which show different mutations in gyrB or in parC that increase their resistance levels but do not make the strains resistant to fluoroquinolones. Thus, antibiotics other than quinolones should be used at fish farms to prevent the emergence and spread of quinolone resistances, especially to CIP, a drug widely recommended for human vibriosis treatment.  相似文献   

9.
The effects of the challenge dose and major histocompatibility complex (MHC) class IB alleles were analyzed in 112 Mauritian cynomolgus monkeys vaccinated (n = 67) or not vaccinated (n = 45) with Tat and challenged with simian/human immunodeficiency virus (SHIV) 89.6Pcy243. In the controls, the challenge dose (10 to 20 50% monkey infectious doses [MID50]) or MHC did not affect susceptibility to infection, peak viral load, or acute CD4 T-cell loss, whereas in the chronic phase of infection, the H1 haplotype correlated with a high viral load (P = 0.0280) and CD4 loss (P = 0.0343). Vaccination reduced the rate of infection acquisition at 10 MID50 (P < 0.0001), and contained acute CD4 loss at 15 MID50 (P = 0.0099). Haplotypes H2 and H6 were correlated with increased susceptibility (P = 0.0199) and resistance (P = 0.0087) to infection, respectively. Vaccination also contained CD4 depletion (P = 0.0391) during chronic infection, independently of the challenge dose or haplotype.Advances in typing of the major histocompatibility complex (MHC) of Mauritian cynomolgus macaques (14, 20, 26) have provided the opportunity to address the influence of host factors on vaccine studies (13). Retrospective analysis of 22 macaques vaccinated with Tat or a Tat-expressing adenoviral vector revealed that monkeys with the H6 or H3 MHC class IB haplotype were overrepresented among aviremic or controller animals, whereas macaques with the H2 or H5 haplotype clustered in the noncontrollers (12). More recently, the H6 haplotype was reported to correlate with control of chronic infection with simian immunodeficiency virus (SIV) mac251, regardless of vaccination (18).Here, we performed a retrospective analysis of 112 Mauritian cynomolgus macaques, which included the 22 animals studied previously (12), to evaluate the impact of the challenge dose and class IB haplotype on the acquisition and severity of simian/human immunodeficiency virus (SHIV) 89.6Pcy243 infection in 45 control monkeys and 67 monkeys vaccinated with Tat from different protocols (Table (Table11).

TABLE 1.

Summary of treatment, challenge dose, and outcome of infection in cynomolgus monkeys
Protocol codeNo. of monkeysImmunogen (dose)aAdjuvantbSchedule of immunization (wk)RoutecChallenged (MID50)Virological outcomee
Reference(s) or source
ACV
ISS-ST6Tat (10)Alum or RIBI0, 2, 6, 12, 15, 21, 28, 32, 36s.c., i.m.104114, 17
ISS-ST1Tat (6)None0, 5, 12, 17, 22, 27, 32, 38, 42, 48i.d.101004, 17
ISS-PCV3pCV-tat (1 mg)Bupivacaine + methylparaben0, 2, 6, 11, 15, 21, 28, 32, 36i.m.103006
ISS-ID3Tat (6)none0, 4, 8, 12, 16, 20, 24, 28, 39, 43, 60i.d.10111B. Ensoli, unpublished data
ISS-TR6Tat (10)Alum-Iscom0, 2, 6, 11, 16, 21, 28, 32, 36s.c., i.d., i.m.10420Ensoli, unpublished
ISS-TGf3Tat (10)Alum0, 4, 12, 22s.c.1503Ensoli, unpublished
ISS-TG3Tatcys22 (10)Alum1503Ensoli, unpublished
ISS-TG4Tatcys22 (10) + Gag (60)Alum1504Ensoli, unpublished
ISS-TG4Tat (10) + Gag (60)Alum1504Ensoli, unpublished
ISS-MP3Tat (10)H1D-Alum0, 4, 12, 18, 21, 38s.c., i.m.15021Ensoli, unpublished
ISS-MP3Tat (10)Alums.c.15003Ensoli, unpublished
ISS-GS6Tat (10)H1D-Alum0, 4, 12, 18, 21, 36s.c., i.m.15132Ensoli, unpublished
NCI-Ad-tat/Tat7Ad-tat (5 × 108 PFU), Tat (10)Alum0, 12, 24, 36i.n., i.t., s.c.15232Ensoli, unpublished
NCI-Tat9Tat (6 and 10)Alum/Iscom0, 2, 6, 11, 15, 21, 28, 32, 36s.c., i.d., i.m.1524312
ISS-NPT3pCV-tat (1 mg)Bupivacaine + methylparaben-Iscom0, 2, 8, 13, 17, 22, 28, 46, 71i.m.20003Ensoli, unpublished
ISS-NPT3pCV-tatcys22 (1 mg)Bupivacaine + methylparaben-Iscom0, 2, 8, 13, 17, 22, 28, 46, 71i.m.20111
    Total vaccinated67191731
        Naive11NoneNoneNAgNA10 or 15137
        Control34None, Ad, or pCV-0Alum, RIBI, H1D, Iscom or bupivacaine + methylparaben-Iscoms.c., i.d., i.n., i.t., i.m.10, 15, or 2051316
    Total controls4561623
    Total112253354
Open in a separate windowaAll animals were inoculated with the indicated dose of Tat plasmid DNA (pCV-tat [8], adenovirus-tat [Ad-tat] [27]) or protein, Gag protein, or empty vectors (pCV-0, adenovirus [Ad]) by the indicated route. Doses are in micrograms unless indicated otherwise.bAlum, aluminum phosphate (4); RIBI oil-in-water emulsions containing squalene, bacterial monophosphoryl lipid A, and refined mycobacterial products (4); Iscom, immune-stimulating complex (4); H1D are biocompatible anionic polymeric microparticles used for vaccine delivery (10, 12, 25a).cs.c., subcutaneous; i.m., intramuscular; i.d., intradermal; i.n., intranasal; i.t., intratracheal.dAll animals were inoculated intravenously with the indicated dose of the same SHIV89.6.Pcy243 stock.eAccording to the virological outcome upon challenge, monkeys were grouped as aviremic (A), controllers (C), or viremic (V).fBecause of the short follow-up, controller status could not be determined and all infected monkeys of the ISS-TG protocol were therefore considered viremic.gNA, not applicable.  相似文献   

10.
11.
Alexey Yanchukov 《Genetics》2009,182(4):1117-1127
A model of genomic imprinting with complete inactivation of the imprinted allele is shown to be formally equivalent to the haploid model of parental selection. When single-locus dynamics are considered, an internal equilibrium is possible only if selection acts in the opposite directions in males and females. I study a two-locus version of the latter model, in which maternal and paternal effects are attributed to the single alleles at two different loci. A necessary condition for the allele frequency equilibria to remain on the linkage equilibrium surface is the multiplicative interaction between maternal and paternal fitness parameters. In this case the equilibrium dynamics are independent at both loci and results from the single-locus model apply. When fitness parameters are additive, analytic treatment was not possible but numerical simulations revealed that stable polymorphism characterized by association between loci is possible only in several special cases in which maternal and paternal fitness contributions are precisely balanced. As in the single-locus case, antagonistic selection in males and females is a necessary condition for the maintenance of polymorphism. I also show that the above two-locus results of the parental selection model are very sensitive to the inclusion of weak directional selection on the individual''s own genotypes.PARENTAL genetic effects refer to the influence of the mother''s and father''s genotypes on the phenotypes of their offspring, not attributable just to the transfer of genes. Examples have been documented across a wide range of areas of organism biology; see, for example, Wade (1998) and and22 in Rasanen and Kruuk (2007). Parental selection is a more formal concept used in theoretical modeling and concerns situations where the fitness of the offspring depends, besides other factors, on the genotypes of its parent(s) (generalizing from Kirkpatrick and Lande 1989).

TABLE 1

Frequencies of genotypes and fitness parameterizations in model 1
Gametes/haploidsFrequency before selectionFitness
ZygoteMaleFemale
(A)AApfpm1 − α1 − δ
(A)a1/2 A 1/2 apf(1 − pm)11
(a)A1/2 a 1/2 A(1 − pf)pm1 − α1 − δ
(a)aA(1 − pf)(1 − pm)11
Open in a separate windowParentheses in the first column indicate maternal genotype (parental selection model) or inactivation of the maternally derived allele (imprinting model). Whether selection occurs at the diploid (first column) or subsequent haploid (second column) stage does not change the resulting allele frequencies.

TABLE 2

Offspring genotypic proportions from different mating types, sorted among four phenotypic groups/combinations of maternal and paternal effects: model 2
Offspring genotypes/phenotypes
Parental genotypes
Paternal (φ = 1)
Joint (φ = 4)
MaleFemaleABAbaBAbABAbaBab
ABAB1
Ab
aB
ab(1−r)/2r/2r/2(1−r)/2
AbAB
Ab1
aBr/2(1−r)/2(1−r)/2r/2
ab
Offspring genotypes/phenotypes
Parental genotypes
Maternal (φ = 2)
None (φ = 3)
MaleFemaleABAbaBAbABAbaBab
aBAB
Abr/2(1 − r)/2(1 − r)/2r/2
aB1
ab
abAB(1 − r)/2(1 − r)/2
Ab
aB
ab1
Open in a separate windowAnother well-known parent-of-origin phenomenon is genomic imprinting. Here, the level of expression of one of the alleles depends on which parent it is inherited from. Often it is difficult to tell apart the phenotypic patterns due to parental effects and genomic imprinting, and thus a problem arises in the process of identifying the candidate genes for such effects (Hager et al. 2008). Analytic methods (Weinberg et al. 1998; Santure and Spencer 2006; Hager et al. 2008) have been developed to quantify subtle differences between the two. In this article, I point out that a simple mathematical model, first suggested for genomic imprinting at a diploid locus, can be interpreted, without any formal changes, to describe parental selection on haploids.While there has been much progress in understanding the evolution of genomic imprinting (Hunter 2007), including advances in modeling (Spencer 2000, 2008), the population genetics theory of parental effects received less attention. Existing major-locus effect models of parental selection are single-locus, two-allele, and mostly concern uniparental (maternal) selection (Wright 1969; Spencer 2003; Gavrilets and Rice 2006; Santure and Spencer 2006), with only one specific case where the fitness effects of both parents interact studied by Gavrilets and Rice (2006). No attempt to extend this theory into multilocus systems has yet been made. Considering a two-locus model with both parents playing a role in selection on the offspring is called for by the observation that many maternal and paternal effects aim at the different traits or different life stages of their progeny. Among birds, for example, body condition soon after hatching is largely determined by the mother, while paternally transmitted sexual display traits develop much later in life (Price 1998). Such effects are therefore unlikely to be regulated within a single locus. Sometimes the effects are on the same trait, but still attributed to different loci: expression of gene Avy that causes the “agouti” phenotype (yellow fur coat and obesity) in mice is enhanced by maternal epigenetic modification (Rakyan et al. 2003), while paternal mutations at the other locus, MommeD4, contribute to a reverse phenotypic pattern in the offspring (Rakyan et al. 2003). The epigenetic state of the murine AxinFu allele is both maternally and paternally inherited (Rakyan et al. 2003).Focusing selection on haploids reduces the number of genotypes that need to be taken into account, while preserving the main properties of the multilocus system. Genes with haploid expression and a potential of parental effects can be found in two major taxonomic kingdoms. A notable candidate is Spam1 in mice, which is expressed during spermogenesis and encodes a factor that enables sperm to penetrate the egg cumulus (Zheng et al. 2001). This gene remains a target for effectively haploid selection, because its product is not shared via cytoplasm bridges between developing spermatides. Mutations at Spam1 alter performance of the male gametes that carry it and might indirectly, perhaps by altering the timing of fertilization, affect the fitness of the zygote. The highest estimated number of mouse genes expressed in the male gametes is currently 2375 (Joseph and Kirkpatrick 2004), and one might expect some of them to have similar paternal effects. Plants go through a profound haploid stage in their life cycles, and genes involved at this stage have an inevitable effect on the fitness of the future generations. In angiosperms, seed development is known to be controlled by both maternal (Chaudhury and Berger 2001; Yadegari and Drews 2004) and paternal (Nowack et al. 2006) effect genes, expressed, respectively, in female and male gametophytes.Under haploid selection, there can be no overdominance, and thus polymorphism is much more difficult to maintain than in diploid selection models (summarized in Feldman 1971). Nevertheless, differential or antagonistic selection between sexes can lead to a new class of stable internal equilibria in the diploid systems (Owen 1953; Bodmer 1965; Mandel 1971; Kidwell et al. 1977; Reed 2007), and I make use of this property in the haploid models developed below. In the experiment by Chippindale and colleagues (Chippindale et al. 2001), ∼75% of the total fitness variation in the adult stage of Drosophila melanogaster was negatively correlated between males and females, which suggests that a substantial portion of the fruit fly expressed genome is under sexually antagonistic selection. I assume that the effect of either parent on the fitness of the individual depends on the sex of the latter, which in respect to modeling is equivalent to the assumption of differential viability between the sexes in the progeny of the same parent(s). Biological systems that satisfy the latter assumptions can be found among colonial green algae: many members of the order Volvocales are haploid except for the short zygotic stage, and during sexual reproduction, they are also dioecious and anisogametic. I return to this example in the discussion. The possibility that genes expressed in animal gametes may be under antagonistic selection between sexes has been discussed (Bernasconi et al. 2004). For example, a (hypothetical) mutation increasing the ATP production in mitochondria would be beneficial in sperm, because of the increased mobility of the latter, but neutral or detrimental in the egg, due to a higher level of oxidative damage to DNA (Zeh and Zeh 2007).My main purpose was to derive conditions for existence and stability of the internal equilibria of the model(s). I begin with a simple one-locus case, which can be analyzed explicitly, and show how these one-locus results can be extended to the case of two recombining loci with multiplicative fitness. Then, I assume an additive relation between the maternal and paternal effect parameters and study the special cases where parental effects are symmetric.  相似文献   

12.
A molecular diagnostic system using single nucleotide polymorphisms (SNPs) was developed to identify four Sclerotinia species: S. sclerotiorum (Lib.) de Bary, S. minor Jagger, S. trifoliorum Erikss., and the undescribed species Sclerotinia species 1. DNAs of samples are hybridized with each of five 15-bp oligonucleotide probes containing an SNP site midsequence unique to each species. For additional verification, hybridizations were performed using diagnostic single nucleotide substitutions at a 17-bp sequence of the calmodulin locus. The accuracy of these procedures was compared to that of a restriction fragment length polymorphism (RFLP) method based on Southern hybridizations of EcoRI-digested genomic DNA probed with the ribosomal DNA-containing plasmid probe pMF2, previously shown to differentiate S. sclerotiorum, S. minor, and S. trifoliorum. The efficiency of the SNP-based assay as a diagnostic test was evaluated in a blind screening of 48 Sclerotinia isolates from agricultural and wild hosts. One isolate of Botrytis cinerea was used as a negative control. The SNP-based assay accurately identified 96% of Sclerotinia isolates and could be performed faster than RFLP profiling using pMF2. This method shows promise for accurate, high-throughput species identification.Sclerotinia is distinguished morphologically from other genera in the Sclerotiniaceae (Ascomycota, Pezizomycotina, Leotiomycetes) by the production of tuberoid sclerotia that do not incorporate host tissue, by the production of microconidia that function as spermatia but not as a disseminative asexual state, and by the development of a layer of textura globulosa composing the outer tissue of apothecia (8). Two hundred forty-six species of Sclerotinia have been reported, most distinguished morphotaxonomically (Index Fungorum [www.indexfungorum.org]). These include the four species of agricultural importance now recognized plus many that are imperfectly known, seldom collected, or apparently endemic to relatively small geographic areas (2, 5, 6, 7, 8, 9, 17).The main species of phythopathological interest in the genus Sclerotinia are S. sclerotiorum (Lib.) de Bary, S. minor Jagger, S. trifoliorum Erikss., and the undescribed species Sclerotinia species 1. Sclerotinia species 1 is an important cause of disease in vegetables in Alaska (16) and has been found in association with wild Taraxacum sp., Caltha palustris, and Aconitum septentrionalis in Norway (7). It is morphologically indistinguishable from S. sclerotiorum, but it was shown to be a distinct species based on distinctive polymorphisms in sequences from internal transcribed spacer 2 (ITS2) of the nuclear ribosomal repeat (7). The other three species have been delimited using morphological, cytological, biochemical, and molecular characters (3, 8, 9, 10, 12, 15). Interestingly, given that the ITS is sufficiently polymorphic in many fungal genera to resolve species, in Sclerotinia, only species 1 and S. trifoliorum are distinguished by characteristic ITS sequence polymorphisms; S. sclerotiorum and S. minor cannot be distinguished based on ITS sequence (2, 7).Sclerotinia sclerotiorum is a necrotrophic pathogen with a broad host range (1). S. minor has a more restricted host range but causes disease in a variety of important crops such as lettuce, peanut, and sunflower crops (11). S. trifoliorum has a much narrower host range, limited to the Fabaceae (3, 8, 9). Sclerotial and ascospore characteristics also serve to differentiate among the three species. Sclerotinia minor has small sclerotia that develop throughout the colony in vitro and aggregate to form crusts on the host, while the sclerotia of S. sclerotiorum and S. trifoliorum are large and form at the colony periphery in vitro, remaining separate on the host (8, 9). The failure of an isolate to produce sclerotia or apothecia in vitro is not unusual, especially after serial cultivation (8). The presence of dimorphic, tetranucleate ascospores characterizes S. trifoliorum, while S. sclerotiorum and S. minor both have uniformly sized ascospores that are binucleate and tetranucleate, respectively (9, 14).With the apparent exception of Sclerotinia species 1, morphological characteristics are sufficient to delimit Sclerotinia species given that workers have all manifestations of the life cycle in hand. In cultures freshly isolated from infected plants, investigators usually have mycelia and sclerotia but not apothecia. Restriction fragment length polymorphisms (RFLPs) in ribosomal DNA (rDNA) are diagnostic for Sclerotinia species (3, 10), but the assay requires cloned probes (usually accessed from other laboratories) hybridized to Southern blots from vertical gels, an impractical procedure for large samples. We have analyzed sequence data from previous phylogenetic studies (2) and have identified diagnostic variation for the rapid identification of the four Sclerotinia species. The single nucleotide polymorphism (SNP) assay that we report here is amenable to a high throughput of samples and requires only PCR amplification with a standard set of primers and oligonucleotide hybridizations to Southern blots in a dot format.The SNP assay was performed using two independent sets of species-specific oligonucleotide probes, all with SNP sites shown to differentiate the four Sclerotinia species (Fig. (Fig.1).1). A panel of 49 anonymously coded isolates (Table (Table1)1) was screened using these species-specific SNP probes, as outlined in Fig. Fig.1.1. The assay was validated by comparison to Southern hybridizations of EcoRI-digested genomic DNA hybridized with pMF2, a plasmid probe containing the portion of the rDNA repeat with the 18S, 5.8S, and 26S rRNA cistrons of Neurospora crassa (4, 10).Open in a separate windowFIG. 1.Protocol for the SNP-based identification of Sclerotinia species, with diagnostic SNP sites underlined and in boldface type for each hybridization probe.

TABLE 1.

Isolates and hybridization results for all SNP-based oligonucleotide probesf
Collector''s isolateAnonymous codePrescreened presumed species identityOriginHostSpecies-specific SNP
IGS50CAL448 S.trifolCAL124CAL448 S.minorRAS148CAL446 S.sp1CAL19ACAL19BCAL448 S.sclero
LMK1849Botrytis cinereaOntario, CanadaAllium cepa
FA2-13Sclerotinia minorNorth CarolinaArachis hypogaea++
W15Sclerotinia minorNorth CarolinaCyperus esculentus++
W1030Sclerotinia minorNorth CarolinaOenothra laciniata++
PF1-138Sclerotinia minorNorth CarolinaArachis hypogaea++
PF18-49714Sclerotinia minorOklahomaArachis hypogaea++
PF17-48246Sclerotinia minorOklahomaArachis hypogaea++
PF19-51948Sclerotinia minorOklahomaArachis hypogaea++
LF-2720Sclerotinia minorUnited StatesLactuca sativa++
AR12811Sclerotinia sclerotiorumArgentinaArachis hypogaea++
AR128216Sclerotinia sclerotiorumArgentinaArachis hypogaea++
LMK2116Sclerotinia sclerotiorumCanadaBrassica napus++
LMK5725Sclerotinia sclerotiorumNorwayRanunculus ficaria++
LMK75415Sclerotinia sclerotiorumNorwayRanunculus ficaria++
UR1939Sclerotinia sclerotiorumUruguayLactuca sativa++
UR4789Sclerotinia sclerotiorumUruguayLactuca sativa++
CA90132Sclerotinia sclerotiorumCaliforniaLactuca sativa++
CA99540Sclerotinia sclerotiorumCaliforniaLactuca sativa++
CA104441Sclerotinia sclerotiorumCaliforniaLactuca sativa++
1980a34Sclerotinia sclerotiorumNebraskaPhaseolus vulgaris++
Ss00113Sclerotinia sclerotiorumNew YorkbGlycine max++
Ssp00531Sclerotinia sclerotiorumNew YorkGlycine max++
H02-V2833Sclerotinia species 1AlaskacUnknown vegetable crop++
H01-V1426Sclerotinia species 1AlaskaUnknown vegetable crop++
LMK74521Sclerotinia species 1NorwayTaraxacum sp.++
02-2611Sclerotinia trifoliorumFinlanddTrifolium pratense+
06-1429Sclerotinia trifoliorumFinlandTrifolium pratense++
2022Sclerotinia trifoliorumFinlandTrifolium pratense++
2-L945Sclerotinia trifoliorumFinlandTrifolium pratense++
3-A524Sclerotinia trifoliorumFinlandTrifolium pratense
5-L912Sclerotinia trifoliorumFinlandTrifolium pratense++
K14Sclerotinia trifoliorumFinlandTrifolium pratense++
K237Sclerotinia trifoliorumFinlandTrifolium pratense++
L-11223Sclerotinia trifoliorumFinlandTrifolium pratense++
L-11944Sclerotinia trifoliorumFinlandTrifolium pratense++
LMK3619Sclerotinia trifoliorumTasmaniaTrifolium repens++
Ssp00118Sclerotinia trifoliorumNew YorkLotus corniculatus++
Ssp00210Sclerotinia trifoliorumNew YorkLotus corniculatus++
Ssp00328Sclerotinia trifoliorumNew YorkLotus corniculatus++
Ssp00436Sclerotinia trifoliorumNew YorkLotus corniculatus++
LMK4743Sclerotinia trifoliorumVirginiaMedicago sativa++
MBRS-127UnknownAustraliaeBrassica spp.++
MBRS-27UnknownAustraliaBrassica spp.++
MBRS-342UnknownAustraliaBrassica spp.++
MBRS-522UnknownAustraliaBrassica spp.++
WW-135UnknownAustraliaBrassica spp.++
WW-28UnknownAustraliaBrassica spp.++
WW-317UnknownAustraliaBrassica spp.++
WW-447UnknownAustraliaBrassica spp.++
Open in a separate windowaThe annotated genome for S. sclerotiorum strain 1980 (ATCC 18683) is publicly available through the Broad Institute, Cambridge, MA (http://www.broad.mit.edu/annotation/genome/sclerotinia_sclerotiorum/Home.html).bAll isolates from New York were provided by Gary C. Bergstrom, Cornell University, Ithaca, NY. Isolates Ss001 and Ssp005 were submitted as S. sclerotiorum, and Ssp001 through Ssp004 were submitted as S. trifoliorum.cAll isolates from Alaska, submitted as Sclerotinia species 1, were provided by Lori Winton, USDA-ARS Subarctic Agricultural Research Unit, University of Alaska, Fairbanks.dAll isolates from Finland, submitted as S. trifoliorum, were provided by Tapani Yli-Mattila, University of Turku, Turku, Finland.eAll isolates from Australia, presumed to be S. sclerotiorum but requiring species confirmation, were provided by Martin Barbetti, DAF Plant Protection Branch, South Perth, Australia.fThe probes that are diagnostic for S. minor, S. sclerotiorum, S. trifoliorum, and Sclerotinia species 1 are listed, with a “+” indicating a positive hybridization for the probe and a “−” indicating no hybridization of the probe.  相似文献   

13.
Therapeutic monoclonal antibodies (mAbs) are currently being approved for marketing in Europe and the United States, as well as other countries, on a regular basis. As more mAbs become available to physicians and patients, keeping track of the number, types, production cell lines, antigenic targets, and dates and locations of approvals has become challenging. Data are presented here for 34 mAbs that were approved in either Europe or the United States (US) as of March 2012, and nimotuzumab, which is marketed outside Europe and the US. Of the 34 mAbs, 28 (abciximab, rituximab, basiliximab, palivizumab, infliximab, trastuzumab, alemtuzumab, adalimumab, tositumomab-I131, cetuximab, ibrituximab tiuxetan, omalizumab, bevacizumab, natalizumab, ranibizumab, panitumumab, eculizumab, certolizumab pegol, golimumab, canakinumab, catumaxomab, ustekinumab, tocilizumab, ofatumumab, denosumab, belimumab, ipilimumab, brentuximab) are currently marketed in Europe or the US. Data for six therapeutic mAbs (muromonab-CD3, nebacumab, edrecolomab, daclizumab, gemtuzumab ozogamicin, efalizumab) that were approved but have been withdrawn or discontinued from marketing in Europe or the US are also included.Of the 28 mAbs currently marketed in the European Union or the US, 26 are marketed in Europe and 27 are marketed in the US, with 25 marketed in both regions (1 Of the 28 mAbs that are marketed in one or the other region, 43% (12/28) are produced in Chinese hamster ovary (CHO) cells, 25% (7/28) are produced in SP2/0 cells,2 18% (5/28) are produced in NS0 cells,3 and 7% (2/28) are produced in hybridomas. The remaining two products (ranibizumab, certolizumab pegol) are antigen-binding fragments (Fab) that are produced in E. coli. Humanized and human mAbs comprise 36% (10/28) and 32% (9/28) of the total, respectively, while 21% (6/28) are chimeric and 11% (3/28) are murine. Most (75%; 21/28) are canonical full-length mAbs. Of the 7 non-canonical mAbs, three (abciximab, ranibizumab, certolizumab pegol) are Fab, with one of these (certolizumab pegol) pegylated; two (tositumomab-I131, ibrituximab tiuxetan) are radiolabeled when administered to patients; one (brentuximab vedotin) is an antibody-drug conjugate (ADC); and one is bispecific (catumaxomab). Although 16 marketed mAbs target unique antigens, CD20 and tumor necrosis factor are each targeted by 4 mAbs, and epidermal growth factor receptor (EGFR) and vascular endothelial growth factor are each targeted by 2 mAbs. If approved, pertuzumab, which is undergoing regulatory review in Europe and the US as a treatment for breast cancer, would be one of 2 mAbs that target human epidermal growth factor receptor 2 on the market.Table 1. Therapeutic monoclonal antibodies marketed or in review in the European Union or United States
International non-proprietary name (Trade name)Manufacturing cell lineTypeTargetFirst EU (US) approval year
Abciximab (Reopro®)
Sp2/0
Chimeric IgG1κ Fab
GPIIb/IIIa
1995# (1994)
Rituximab (MabThera®, Rituxan®)
CHO
Chimeric IgG1κ
CD20
1998 (1997)
Basiliximab (Simulect®)
Sp2/0
Chimeric IgG1κ
IL2R
1998 (1998)
Palivizumab (Synagis®)
NS0
Humanized IgG1κ
RSV
1999 (1998)
Infliximab (Remicade®)
Sp2/0
Chimeric IgG1κ
TNF
1999 (1998)
Trastuzumab (Herceptin®)
CHO
Humanized IgG1κ
HER2
2000 (1998)
Alemtuzumab (MabCampath, Campath-1H®)
CHO
Humanized IgG1κ
CD52
2001 (2001)
Adalimumab (Humira®)
CHO
Human IgG1κ
TNF
2003 (2002)
Tositumomab-I131 (Bexxar®)
Hybridoma
Murine IgG2aλ
CD20
NA (2003)
Cetuximab (Erbitux®)
Sp2/0
Chimeric IgG1κ
EGFR
2004 (2004)
Ibritumomab tiuxetan (Zevalin®)
CHO
Murine IgG1κ
CD20
2004 (2002)
Omalizumab (Xolair®)
CHO
Humanized IgG1κ
IgE
2005 (2003)
Bevacizumab (Avastin®)
CHO
Humanized IgG1κ
VEGF
2005 (2004)
Natalizumab (Tysabri®)
NS0
Humanized IgG4κ
α4-integrin
2006 (2004)
Ranibizumab (Lucentis®)
E. coli
Humanized IgG1κ Fab
VEGF
2007 (2006)
Panitumumab (Vectibix®)
CHO
Human IgG2κ
EGFR
2007 (2006)
Eculizumab (Soliris®)
NS0
Humanized IgG2/4κ
C5
2007 (2007)
Certolizumab pegol (Cimzia®)
E. coli
Humanized IgG1κ Fab, pegylated
TNF
2009 (2008)
Golimumab (Simponi®)
Sp2/0
Human IgG1κ
TNF
2009 (2009)
Canakinumab (Ilaris®)
Sp2/0
Human IgG1κ
IL1b
2009 (2009)
Catumaxomab (Removab®)
Hybrid
hybridoma
Rat IgG2b/mouse IgG2a bispecific
EpCAM/CD3
2009 (NA)
Ustekinumab (Stelara®)
Sp2/0
Human IgG1κ
IL12/23
2009 (2009)
Tocilizumab (RoActemra, Actemra®)
CHO
Humanized IgG1κ
IL6R
2009 (2010)
Ofatumumab (Arzerra®)
NS0
Human IgG1κ
CD20
2010 (2009)
Denosumab (Prolia®)
CHO
Human IgG2λ
RANK-L
2010 (2010)
Belimumab (Benlysta®)
NS0
Human IgG1κ
BLyS
2011 (2011)
Raxibacumab (Pending)
NS0**
Human IgG1κ
B. anthrasis PA
NA (In review)
Ipilimumab (Yervoy®)
CHO
Human IgG1κ
CTLA-4
2011 (2011)
Brentuximab vedotin (Adcentris®)
CHO
Chimeric IgG1κ; conjugated to monomethyl auristatin E
CD30
In review (2011)
Pertuzumab (Pending)CHOHumanized IgG1κHER2In review (in review)
Open in a separate window*As of March 10, 2012. #Country-specific approval; approved under concertation procedure **Product manufactured for Phase 1 study in humans. Abbreviations: BLyS, B lymphocyte stimulator; C5, complement 5; CD, cluster of differentiation; CHO, Chinese hamster ovary; CTLA-4, cytotoxic T lymphocyte antigen 4; EGFR, epidermal growth factor receptor; EpCAM, epithelial cell adhesion molecule; Fab, antigen-binding fragment; GP glycoprotein; IL, interleukin; NA, not approved; PA, protective antigen; RANK-L, receptor activator of NFκb ligand; RSV, respiratory syncytial virus; TNF, tumor necrosis factor; VEGF, vascular endothelial growth factor. Sources: European Medicines Agency public assessment reports, United States Food and Drug Administration (drugs@fda), the international ImMunoGeneTics information system® (www.imgt.org/mAb-DB/index).In addition to the 28 mAbs currently marketed, six mAbs were approved in at least one country of Europe or in the US, but were subsequently withdrawn or discontinued from marketing for various reasons (4,5 Nebacumab (Centoxin®), a human IgM, was approved in The Netherlands, Britain, Germany and France during 1991 as a treatment for Gram-negative sepsis,6 but the product was subsequently withdrawn for safety, efficacy and commercial reasons.7 The murine anti-epithelial cell adhesion molecule (EpCAM) edrecolomab (Panorex®) was approved in Germany in 1995 as an adjuvant treatment for colon cancer, but subsequently withdrawn because of the product’s lack of efficacy.8 Daclizumab was first approved in 1997 for prophylaxis of acute organ rejection in patients receiving renal transplants, but the product was voluntarily withdrawn from the market in Europe effective January 1, 20099 and discontinued for the US market because of the availability of alternative therapy and the diminished market demand.10 The first ADC to be approved, gemtuzumab ozogamicin was marketed in the US for a decade before being voluntarily withdrawn in 2010. The product was approved under the accelerated approval mechanism as a treatment for acute myeloid leukemia (AML), but was withdrawn when a confirmatory clinical trial and post-approval use did not show evidence of clinical benefit in AML patients.11 Efalizumab (Raptiva®) was approved in the US and Europe in 2003 and 2004, respectively, as a treatment for adults with moderate to severe plaque psoriasis, but the product was voluntarily withdrawn from both markets in 2009 because of the risk of side effects, including progressive multifocal leukoencephalopathy.12,13Table 2. Therapeutic monoclonal antibodies withdrawn or discontinued from marketing in the European Union or United States
International proprietary name (Trade name)Manufacturing
cell line
TypeTargetFirst EU (US) approval year
Muromonab-CD3 (Orthoclone OKT3®)
Hybridoma
Murine IgG2a
CD3
1986* (1986)
Nebacumab (Centoxin®)
Hybridoma
Human IgM
Endotoxin
1991*(NA)
Edrecolomab (Panorex®)
Hybridoma
Murine IgG2a
EpCAM
1995*(NA)
Daclizumab (Zenapax®)
NS0
Humanized IgG1κ
IL2R
1999 (1997)
Gemtuzumab ozogamicin (Mylotarg®)
NS0
Humanized IgG4κ
CD33
NA (2000)
Efalizumab (Raptiva®)CHOHumanized IgG1κCD11a2004 (2003)
Open in a separate windowNote: Information current as of March 10, 2012. *European country-specific approval. Abbreviations: CD, cluster of differentiation; CHO, Chinese hamster ovary; EpCAM, epithelial cell adhesion molecule; IL, interleukin; NA, not approved. Sources: European Medicines Agency public assessment reports, United States Food and Drug Administration (drugs@fda), the international ImMunoGeneTics information system® (www.imgt.org/mAb-DB/index).The European Union and the US are not necessarily the first or only markets for therapeutic mAbs (14 Mogamulizumab is a defucosylated humanized anti-CC chemokine receptor 4 (CCR4) antibody developed by Kyowa Hakko Kirin Co Ltd.15 The mAb is undergoing regulatory review in Japan as a treatment for adult T-cell leukemia-lymphoma and peripheral T-cell lymphoma.Table 3. Therapeutic monoclonal antibodies marketed or in review outside the European Union or United States
International proprietary name (Trade name)Manufacturing
cell line
TypeTargetFirst approval year
Nimotuzumab (TheraCIM®, BIOMAB-EGFR®)
NS0
Humanized IgG1κ
EGFR
1999
Mogamulizumab[Not found]Humanized IgG1κCCR4In review in Japan
Open in a separate windowNote: Information current as of March 10, 2012. Abbreviations: CCR, chemokine receptor; EGFR, epidermal growth factor receptor.The 35 marketed mAbs, most of which are canonical full-length IgG1, paved the way for the next generation of antibody-based therapeutics such as ADCs, bispecific antibodies, engineered antibodies, and antibody fragments or domains. The commercial pipeline includes ~350 mAbs now being evaluated in clinical studies around the world as treatments for many indications, including cancer, immunological disorders and infectious diseases.16 The compendium of marketed therapeutic antibodies may thus be substantially larger in the future.  相似文献   

14.
15.
16.
Sulfonamide-resistant Escherichia coli and Salmonella isolates from pigs and chickens in Ontario and Québec were screened for sul1, sul2, and sul3 by PCR. Each sul gene was distributed differently across populations, with a significant difference between distribution in commensal E. coli and Salmonella isolates and sul3 restricted mainly to porcine E. coli isolates.Resistance to sulfonamides is frequent in bacteria from farm animals (7, 8, 9, 10) and is usually caused by the acquisition of the genes sul1, sul2, and sul3 (20, 22). The objectives of this study were (i) to assess the distribution of these genes in Escherichia coli and Salmonella enterica isolates in swine and chickens from two major provinces in Canada, (ii) to assess whether differences occur in the distribution of these genes among bacterial species found within two different animal host species, and (iii) to assess whether significant differences in the distribution of these genes are present between the commensal E. coli strains used as indicators for surveillance of antimicrobial resistance and the zoonotic Salmonella pathogens found in the same ecological niche. In contrast to previous studies, a multivariable logistic regression model was used to analyze the data, control for confounding factors, and assess the interaction effect between animal and bacterial species in terms of the probability of an isolate carrying a specific sul gene. The distribution of sulfonamide resistance genes among sulfonamide-resistant E. coli (393 isolates from chickens and 311 from swine) and Salmonella (13 isolates from chickens and 221 from swine) isolates was assessed. These isolates were collected by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) between 2003 and 2005 from ceca of apparently healthy animals at abattoirs in Ontario (n = 435) and Québec (n = 503). The methods used by CIPARS are presented in detail elsewhere (8-10). The isolates were screened with a previously published multiplex PCR for sul1, sul2, and sul3 (16). The sul1 and sul2 genes were found in E. coli and Salmonella isolates from both animal species. The sul3 gene was detected in both E. coli and Salmonella isolates from swine but only in E. coli isolates from chickens (Table (Table1).1). Three percent of the isolates had no detectable sul gene, 12.5% possessed two genes, and two isolates carried three genes (Table (Table1).1). Similar (2, 3, 14, 19) or higher (4, 11, 17) values for multiple genes have been reported by others. The overall higher prevalence of sul1 in Salmonella isolates and of sul2 and sul3 in E. coli isolates was in agreement with the results of previous studies (2-4, 11, 12, 14, 21).

TABLE 1.

Frequency of the three resistance genes sul1, sul2, and sul3 in sulfonamide-resistant E. coli and Salmonella isolates from chickens and swine in Ontario and Québec between 2003 and 2005
Bacterial speciesSource (no. of isolates)No. (%) of isolates with indicated gene(s)
sul1sul2sul3sul1 + sul2sul1+ sul3sul2 + sul3sul1 + sul2 + sul3None
E. coliSwine (311)61 (19.6)66 (21.2)132 (42.4)11 (3.5)9 (2.9)11 (3.5)2 (0.6)19 (6.1)
Chickens (393)103 (26.2)211 (53.7)9 (2.3)64 (16.3)0 (0.0)0 (0.0)0 (0.0)6 (1.5)
Total (704)164 (23.3)277 (39.3)141 (20.0)75 (10.7)9 (1.3)11 (1.6)2 (0.3)25 (3.6)
SalmonellaSwine (221)173 (78.3)20 (9.0)5 (2.3)7 (3.2)0 (0.0)14 (6.3)0 (0.0)2 (0.9)
Chickens (13)7 (53.8)5 (38.5)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (7.7)
Total (234)180 (76.9)25 (10.7)5 (2.1)7 (3.0)0 (0.0)14 (6.0)0 (0.0)3 (1.3)
Open in a separate windowThree logistic regression models (Table (Table2)2) for associations between the presence of each sul gene and the bacterial species, animal species, province of origin of the animals, and year of isolation were built using Stata 9 (StataCorp, College Station, TX). Statistical interactions between bacterial and animal species were assessed in the sul1 and sul2 models but not in the sul3 model (the sample size was insufficient). Tests were two tailed, with significance at a P value of ≤0.05. A significant interaction between bacterial and animal species was observed for sul1 (Table (Table2).2). The presence of statistical interactions indicates that the effect of each variable depends on the state of the other variable. Thus, the effects of bacterial and animal species on the distribution of sul1 cannot be interpreted independently. For instance, sul1 was more frequent in Salmonella isolates from swine than from chickens, but the reverse was true for E. coli isolates (Table (Table3).3). Genomic islands containing sul1 are present in some Salmonella serovars, including S. enterica serovar Typhimurium and S. Derby (1, 6, 18), which were the most frequent in the swine samples of this study (Table (Table4).4). This contrasts with E. coli strains, in which sul1 is usually associated with transposons and large transferable plasmids (22). Thus, the presence of significant statistical interactions in the sul1 model could be an indicator of the differential importance of horizontal gene transfer in E. coli strains versus clonal expansion of specific Salmonella serovars in the animal species investigated. No significant interaction was detected for sul2 (P = 0.66) (Table (Table2).2). This could be the consequence of the relatively small number of sul2-positive Salmonella isolates and the resultant lack of statistical power; however, it is also possible that sul2 has a different epidemiology than sul1. The sul2 gene has not been shown to be located on genomic islands and is usually plasmid borne (22). It may therefore be transferred more frequently than sul1 between E. coli and Salmonella and between bacteria from swine and chickens, leading to the absence of a significant interaction in the sul2 model. Serotyping, molecular typing, and assessment of gene transferability would be required to test these hypotheses.

TABLE 2.

Multivariable models for the distribution of the sul1, sul2, and sul3 sulfonamide resistance genes from swine and chickens at slaughter in Ontario and Québec between 2003 and 2005
Explanatory variable (referent group) or interactionOdds ratio (95% confidence interval)b
sul1sul2sul3
Salmonella (E. coli)1.54 (0.50-4.74)0.33 (0.21-0.51)0.10 (0.06-0.16)
Swine (chickens)0.49 (0.36-0.68)c0.16 (0.12-0.23)c39.57 (20.21-77.48)c
Québec (Ontario)0.80 (0.60-1.07)2.20 (1.61-2.99)c0.83 (0.56-1.23)
2004 (2003)0.77 (0.56-1.06)0.99 (0.71-1.40)1.84 (1.18-2.86)
2005 (2003)0.68 (0.45-1.04)1.36 (0.88-2.09)1.66 (0.99-2.79)
2005 (2004)0.88 (0.58-1.36)1.36 (0.88-2.11)0.90 (0.53-1.53)
Bacterial species × animal speciesa12.84 (3.79-43.46)cNINI
Open in a separate windowaStatistical interaction between data for bacterial species and animal species. The terms for this interaction are described in Table Table33.bExample of odds ratio interpretation: the odds of a porcine isolate carrying sul3 were 39.57 times higher than for an isolate obtained from chickens. NI, not included in the model. The sul2 model was not included because the P value for this interaction was equal to 0.66, and the sul3 model was not included because it did not converge when including this interaction.cP < 0.001.

TABLE 3.

Interaction terms for the association between bacterial and animal species for the presence of sul1
Contrast variablesOdds ratioa95% Confidence intervalP value
Salmonella in pigs vs Salmonella in chickens6.301.95-20.390.002
E. coli in pigs vs E. coli in chickens0.490.36-0.67<0.001
Salmonella in chickens vs E. coli in chickens1.540.50-4.740.451
Salmonella in pigs vs E. coli in pigs19.7912.28-31.87<0.001
Open in a separate windowaExample of interpretation: the interaction effect suggests that sul1-mediated sulfonamide resistance is 19.79 times more likely to occur in Salmonella in pigs than in E. coli in pigs.

TABLE 4.

Salmonella serovars and frequency of resistance genes detected in each serovar
Salmonella serovarNo. of isolatesaNo. of isolates with indicated genea
sul1sul2sul3
Agona14/014/00/00/0
Berta3/00/03/00/0
Bovismorbificans1/00/00/00/0
Brandenburg3/01/01/00/0
Derby63/059/04/02/0
Give O:15+1/01/00/00/0
Heidelberg2/40/30/02/0
4,12:−:−3/03/00/00/0
4,12:i:−2/02/00/00/0
4,5,12:−:−1/01/00/01/0
Rough-O:fg:−1/01/00/00/0
Rough-O:l,v:enz151/01/01/00/0
Infantis3/01/02/00/0
Johannesburg1/01/00/00/0
London2/01/00/01/0
Manhattan2/00/02/00/0
Mbandaka6/06/01/00/0
Ohio O:14+1/00/01/00/0
Putten1/01/00/00/0
Schwarzengrund0/60/10/50/0
Typhimurium110/3101/312/013/0
Total221/13194/727/519/0
Open in a separate windowaThe first and second numbers in each column represent swine and chicken isolates, respectively; the total number of tabulated occurrences of sulfonamide genes is larger than the number of resistant isolates investigated because some isolates carried several genes simultaneously.A significant increase in the prevalence of sul3 was detected between 2003 and 2004 (P = 0.007) but not between 2004 and 2005 (P = 0.055) nor at any time for sul1 and sul2 (Table (Table2).2). The sul3 gene has emerged recently (5), and its prevalence was probably still increasing in 2003. The odds of finding sul3 in Salmonella isolates were 10 times lower than for E. coli isolates and 40 times higher in swine than in chickens (Table (Table2).2). Other studies have also found high frequencies of sul3 in porcine E. coli isolates (5, 12, 20) and much lower frequencies in other sources (4, 11, 12, 14). Although these isolates were not typed, previous results have shown that sul3 is present in both pathogenic and commensal porcine E. coli isolates (5) of at least 13 different serotypes (P. Boerlin and R. M. Travis, unpublished data). The sul3 gene has spread extensively across porcine E. coli populations in North America and Europe but remains uncommon in other major farm animal species and in Salmonella populations (Table (Table1)1) (2, 13). It may require more time to spread to other populations. There may be biological and ecological barriers slowing its spread to bacteria of other animal species or coselection factors that favor its presence in porcine E. coli populations.Using the example of sulfonamides as a model for the application of multivariable statistical approaches to the study of antimicrobial resistance epidemiology, this study indicates that the relative frequencies of genes encoding resistance to the same antimicrobial either present in bacterial populations for decades or recently emerged can vary significantly between animal hosts and phylogenetically related bacterial species sharing the same ecological niche. Differences in the distribution of resistance determinants may remain hidden when assessing resistance phenotypes. Similar antimicrobial susceptibility results do not necessarily imply similar resistance genes. These findings highlight the need to further explore the interactions between commensals and pathogens and the ways in which commensal bacteria are interpreted as indicators of antimicrobial resistance in pathogens.  相似文献   

17.
18.
Riboflavin significantly enhanced the efficacy of simulated solar disinfection (SODIS) at 150 watts per square meter (W m−2) against a variety of microorganisms, including Escherichia coli, Fusarium solani, Candida albicans, and Acanthamoeba polyphaga trophozoites (>3 to 4 log10 after 2 to 6 h; P < 0.001). With A. polyphaga cysts, the kill (3.5 log10 after 6 h) was obtained only in the presence of riboflavin and 250 W m−2 irradiance.Solar disinfection (SODIS) is an established and proven technique for the generation of safer drinking water (11). Water is collected into transparent plastic polyethylene terephthalate (PET) bottles and placed in direct sunlight for 6 to 8 h prior to consumption (14). The application of SODIS has been shown to be a simple and cost-effective method for reducing the incidence of gastrointestinal infection in communities where potable water is not available (2-4). Under laboratory conditions using simulated sunlight, SODIS has been shown to inactivate pathogenic bacteria, fungi, viruses, and protozoa (6, 12, 15). Although SODIS is not fully understood, it is believed to achieve microbial killing through a combination of DNA-damaging effects of ultraviolet (UV) radiation and thermal inactivation from solar heating (21).The combination of UVA radiation and riboflavin (vitamin B2) has recently been reported to have therapeutic application in the treatment of bacterial and fungal ocular pathogens (13, 17) and has also been proposed as a method for decontaminating donor blood products prior to transfusion (1). In the present study, we report that the addition of riboflavin significantly enhances the disinfectant efficacy of simulated SODIS against bacterial, fungal, and protozoan pathogens.Chemicals and media were obtained from Sigma (Dorset, United Kingdom), Oxoid (Basingstoke, United Kingdom), and BD (Oxford, United Kingdom). Pseudomonas aeruginosa (ATCC 9027), Staphylococcus aureus (ATCC 6538), Bacillus subtilis (ATCC 6633), Candida albicans (ATCC 10231), and Fusarium solani (ATCC 36031) were obtained from ATCC (through LGC Standards, United Kingdom). Escherichia coli (JM101) was obtained in house, and the Legionella pneumophila strain used was a recent environmental isolate.B. subtilis spores were produced from culture on a previously published defined sporulation medium (19). L. pneumophila was grown on buffered charcoal-yeast extract agar (5). All other bacteria were cultured on tryptone soy agar, and C. albicans was cultured on Sabouraud dextrose agar as described previously (9). Fusarium solani was cultured on potato dextrose agar, and conidia were prepared as reported previously (7). Acanthamoeba polyphaga (Ros) was isolated from an unpublished keratitis case at Moorfields Eye Hospital, London, United Kingdom, in 1991. Trophozoites were maintained and cysts prepared as described previously (8, 18).Assays were conducted in transparent 12-well tissue culture microtiter plates with UV-transparent lids (Helena Biosciences, United Kingdom). Test organisms (1 × 106/ml) were suspended in 3 ml of one-quarter-strength Ringer''s solution or natural freshwater (as pretreated water from a reservoir in United Kingdom) with or without riboflavin (250 μM). The plates were exposed to simulated sunlight at an optical output irradiance of 150 watts per square meter (W m−2) delivered from an HPR125 W quartz mercury arc lamp (Philips, Guildford, United Kingdom). Optical irradiances were measured using a calibrated broadband optical power meter (Melles Griot, Netherlands). Test plates were maintained at 30°C by partial submersion in a water bath.At timed intervals for bacteria and fungi, the aliquots were plated out by using a WASP spiral plater and colonies subsequently counted by using a ProtoCOL automated colony counter (Don Whitley, West Yorkshire, United Kingdom). Acanthamoeba trophozoite and cyst viabilities were determined as described previously (6). Statistical analysis was performed using a one-way analysis of variance (ANOVA) of data from triplicate experiments via the InStat statistical software package (GraphPad, La Jolla, CA).The efficacies of simulated sunlight at an optical output irradiance of 150 W m−2 alone (SODIS) and in the presence of 250 μM riboflavin (SODIS-R) against the test organisms are shown in Table Table1.1. With the exception of B. subtilis spores and A. polyphaga cysts, SODIS-R resulted in a significant increase in microbial killing compared to SODIS alone (P < 0.001). In most instances, SODIS-R achieved total inactivation by 2 h, compared to 6 h for SODIS alone (Table (Table1).1). For F. solani, C. albicans, ands A. polyphaga trophozoites, only SODIS-R achieved a complete organism kill after 4 to 6 h (P < 0.001). All control experiments in which the experiments were protected from the light source showed no reduction in organism viability over the time course (results not shown).

TABLE 1.

Efficacies of simulated SODIS for 6 h alone and with 250 μM riboflavin (SODIS-R)
OrganismConditionaLog10 reduction in viability at indicated h of exposureb
1246
E. coliSODIS0.0 ± 0.00.2 ± 0.15.7 ± 0.05.7 ± 0.0
SODIS-R1.1 ± 0.05.7 ± 0.05.7 ± 0.05.7 ± 0.0
L. pneumophilaSODIS0.7 ± 0.21.3 ± 0.34.8 ± 0.24.8 ± 0.2
SODIS-R4.4 ± 0.04.4 ± 0.04.4 ± 0.04.4 ± 0.0
P. aeruginosaSODIS0.7 ± 0.01.8 ± 0.04.9 ± 0.04.9 ± 0.0
SODIS-R5.0 ± 0.05.0 ± 0.05.0 ± 0.05.0 ± 0.0
S. aureusSODIS0.0 ± 0.00.0 ± 0.06.2 ± 0.06.2 ± 0.0
SODIS-R0.2 ± 0.16.3 ± 0.06.3 ± 0.06.3 ± 0.0
C. albicansSODIS0.2 ± 0.00.4 ± 0.10.5 ± 0.11.0 ± 0.1
SODIS-R0.1 ± 0.00.7 ± 0.15.3 ± 0.05.3 ± 0.0
F. solani conidiaSODIS0.2 ± 0.10.3 ± 0.00.2 ± 0.00.7 ± 0.1
SODIS-R0.3 ± 0.10.8 ± 0.11.3 ± 0.14.4 ± 0.0
B. subtilis sporesSODIS0.3 ± 0.00.2 ± 0.00.0 ± 0.00.1 ± 0.0
SODIS-R0.1 ± 0.10.2 ± 0.10.3 ± 0.30.1 ± 0.0
SODIS (250 W m−2)0.1 ± 0.00.1 ± 0.10.1 ± 0.10.0 ± 0.0
SODIS-R (250 W m−2)0.0 ± 0.00.0 ± 0.00.2 ± 0.00.4 ± 0.0
SODIS (320 W m−2)0.1 ± 0.10.1 ± 0.00.0 ± 0.14.3 ± 0.0
SODIS-R (320 W m−2)0.1 ± 0.00.1 ± 0.10.9 ± 0.04.3 ± 0.0
A. polyphaga trophozoitesSODIS0.4 ± 0.20.6 ± 0.10.6 ± 0.20.4 ± 0.1
SODIS-R0.3 ± 0.11.3 ± 0.12.3 ± 0.43.1 ± 0.2
SODIS, naturalc0.3 ± 0.10.4 ± 0.10.5 ± 0.20.3 ± 0.2
SODIS-R, naturalc0.2 ± 0.11.0 ± 0.22.2 ± 0.32.9 ± 0.3
A. polyphaga cystsSODIS0.4 ± 0.10.1 ± 0.30.3 ± 0.10.4 ± 0.2
SODIS-R0.4 ± 0.20.3 ± 0.20.5 ± 0.10.8 ± 0.3
SODIS (250 W m−2)0.0 ± 0.10.2 ± 0.30.2 ± 0.10.1 ± 0.2
SODIS-R (250 W m−2)0.4 ± 0.20.3 ± 0.20.8 ± 0.13.5 ± 0.3
SODIS (250 W m−2), naturalc0.0 ± 0.30.2 ± 0.10.1 ± 0.10.2 ± 0.1
SODIS-R (250 W m−2), naturalc0.1 ± 0.10.2 ± 0.20.6 ± 0.13.4 ± 0.2
Open in a separate windowaConditions are at an intensity of 150 W m−2 unless otherwise indicated.bThe values reported are means ± standard errors of the means from triplicate experiments.cAdditional experiments for this condition were performed using natural freshwater.The highly resistant A. polyphaga cysts and B. subtilis spores were unaffected by SODIS or SODIS-R at an optical irradiance of 150 W m−2. However, a significant reduction in cyst viability was observed at 6 h when the optical irradiance was increased to 250 W m−2 for SODIS-R only (P < 0.001; Table Table1).1). For spores, a kill was obtained only at 320 W m−2 after 6-h exposure, and no difference between SODIS and SODIS-R was observed (Table (Table1).1). Previously, we reported a >2-log kill at 6 h for Acanthamoeba cysts by using SODIS at the higher optical irradiance of 850 W m−2, compared to the 0.1-log10 kill observed here using the lower intensity of 250 W m−2 or the 3.5-log10 kill with SODIS-R.Inactivation experiments performed with Acanthamoeba cysts and trophozoites suspended in natural freshwater gave results comparable to those obtained with Ringer''s solution (P > 0.05; Table Table1).1). However, it is acknowledged that the findings of this study are based on laboratory-grade water and freshwater and that differences in water quality through changes in turbidity, pH, and mineral composition may significantly affect the performance of SODIS (20). Accordingly, further studies are indicated to evaluate the enhanced efficacy of SODIS-R by using natural waters of varying composition in the areas where SODIS is to be employed.Previous studies with SODIS under laboratory conditions have employed lamps delivering an optical irradiance of 850 W m−2 to reflect typical natural sunlight conditions (6, 11, 12, 15, 16). Here, we used an optical irradiance of 150 to 320 W m−2 to obtain slower organism inactivation and, hence, determine the potential enhancing effect of riboflavin on SODIS.In conclusion, this study has shown that the addition of riboflavin significantly enhances the efficacy of simulated SODIS against a range of microorganisms. The precise mechanism by which photoactivated riboflavin enhances antimicrobial activity is unknown, but studies have indicated that the process may be due, in part, to the generation of singlet oxygen, H2O2, superoxide, and hydroxyl free radicals (10). Further studies are warranted to assess the potential benefits from riboflavin-enhanced SODIS in reducing the incidence of gastrointestinal infection in communities where potable water is not available.  相似文献   

19.
Twelve cluster groups of Escherichia coli O26 isolates found in three cattle farms were monitored in space and time. Cluster analysis suggests that only some O26:H11 strains had the potential for long-term persistence in hosts and farms. As judged by their virulence markers, bovine enterohemorrhagic O26:H11 isolates may represent a considerable risk for human infection.Shiga toxin (Stx)-producing Escherichia coli (STEC) strains comprise a group of zoonotic enteric pathogens (42). In humans, infections with some STEC serotypes result in hemorrhagic or nonhemorrhagic diarrhea, which can be complicated by hemolytic-uremic syndrome (HUS) (49). These STEC strains are also designated “enterohemorrhagic E. coli” (EHEC). Consequently, EHEC strains represent a subgroup of STEC with a high pathogenic potential for humans. Strains of the E. coli serogroup O26 were originally classified as enteropathogenic E. coli due to their association with outbreaks of infantile diarrhea in the 1940s. In 1977, Konowalchuk et al. (37) recognized that these bacteria produced Stx, and 10 years later, the Stx-producing E. coli O26:H11/H− strains were classified as EHEC. EHEC O26 strains constitute the most common non-O157 EHEC group associated with diarrhea and HUS in Europe (12, 21, 23, 24, 26, 27, 55, 60). Reports on an association between EHEC O26 and HUS or diarrhea from North America including the United States (15, 30, 33), South America (51, 57), Australia (22), and Asia (31, 32) provide further evidence for the worldwide spread of these organisms. Studies in Germany and Austria (26, 27) on sporadic HUS cases between 1996 and 2003 found that EHEC O26 accounted for 14% of all EHEC strains and for ∼40% of non-O157 EHEC strains obtained from these patients. A proportion of 11% EHEC O26 strains was detected in a case-control study in Germany (59) between 2001 and 2003. In the age group <3 years, the number of EHEC O26 cases was nearly equal to that of EHEC O157 cases, although the incidence of EHEC O26-associated disease is probably underestimated because of diagnostic limitations in comparison to the diagnosis of O157:H7/H− (18, 34). Moreover, EHEC O26 has spread globally (35). Beutin (6) described EHEC O26:H11/H−, among O103:H2, O111:H, O145:H28/H−, and O157:H7/H−, as the well-known pathogenic “gang of five,” and Bettelheim (5) warned that we ignore the non-O157 STEC strains at our peril.EHEC O26 strains produce Stx1, Stx2, or both (15, 63). Moreover, these strains contain the intimin-encoding eae gene (11, 63), a characteristic feature of EHEC (44). In addition, EHEC strains possess other markers associated with virulence, such as a large plasmid that carries further potential virulence genes, e.g., genes coding for EHEC hemolysin (EHEC-hlyA), a catalase-peroxidase (katP), and an extracellular serine protease (espP) (17, 52). The efa1 (E. coli factor for adherence 1) gene was identified as an intestinal colonization factor in EHEC (43). EHEC O26 represents a highly dynamic group of organisms that rapidly generate new pathogenic clones (7, 8, 63).Ruminants, especially cattle, are considered the primary reservoir for human infections with EHEC. Therefore, the aim of this study was the molecular characterization of bovine E. coli field isolates of serogroup O26 using a panel of typical virulence markers. The epidemiological situation in the beef herds from which the isolates were obtained and the spatial and temporal behavior of the clonal distribution of E. coli serogroup O26 were analyzed during the observation period. The potential risk of the isolates inducing disease in humans was assessed.In our study, 56 bovine E. coli O26:H11 isolates and one bovine O26:H32 isolate were analyzed for EHEC virulence-associated factors. The isolates had been obtained from three different beef farms during a long-term study. They were detected in eight different cattle in farm A over a period of 15 months (detected on 10 sampling days), in 3 different animals in farm C over a period of 8 months (detected on 3 sampling days), and in one cow on one sampling day in farm D (Table (Table1)1) (28).

TABLE 1.

Typing of E. coli O26 isolates
Sampling day, source, and isolateSerotypeVirulence profile by:
fliC PCR-RFLPstx1 genestx2 geneStx1 (toxin)Stx2 (toxin)Subtype(s)
efa1 genebEHEC-hlyA genekatP geneespP genePlasmid size(s) in kbCluster
stx1/stx2eaetirespAespB
Day 15
    Animal 6 (farm A)
        WH-01/06/002-1O26:H11H11++stx1ββββ+/++++110, 127
        WH-01/06/002-2O26:H11H11++stx1ββββ+/++++110, 127
        WH-01/06/002-3O26:H11H11++stx1ββββ+/++++110, 127
    Animal 8 (farm A)
        WH-01/08/002-2O26:H11H11++stx1ββββ+/++++110, 127
    Animal 26 (farm A)
        WH-01/26/001-2O26:H11H11++stx1ββββ+/++++130, 127
        WH-01/26/001-5O26:H11H11++stx1ββββ+/++++110, 127
        WH-01/26/001-6O26:H11H11++stx1ββββ+/++++110, 127
        WH-01/26/001-7O26:H11H11++stx1ββββ+/−+++110, 127
Day 29
    Animal 2 (farm A)
        WH-01/02/003-1O26:H11H11++stx1ββββ+/++++110, 126
        WH-01/02/003-2O26:H11H11++stx1ββββ+/++++110, 126
        WH-01/02/003-5O26:H11H11++stx1ββββ+/++++110, 126
        WH-01/02/003-6O26:H11H11++stx1ββββ+/+++110, 126
        WH-01/02/003-7O26:H11H11++stx1ββββ+/++++110, 126
        WH-01/02/003-8O26:H11H11++stx1ββββ−/++++110, 126
        WH-01/02/003-9O26:H11H11++stx1ββββ+/++++1106
        WH-01/02/003-10O26:H11H11++stx1ββββ+/++++1106
    Animal 26 (farm A)
        WH-01/26/002-2O26:H11H11++stx1ββββ+/++++130, 125
        WH-01/26/002-5O26:H11H11++stx1ββββ+/++++130, 125
        WH-01/26/002-8O26:H11H11++stx1ββββ+/++++130, 125
        WH-01/26/002-9O26:H11H11++stx1ββββ+/++110, 125
        WH-01/26/002-10O26:H11H11++stx1ββββ+/++++130, 125
Day 64
    Animal 20 (farm A)
        WH-01/20/005-3O26:H11H11++stx1ββββ+/+130, 2.52
Day 78
    Animal 29 (farm A)
        WH-01/29/002-1O26:H11H11++stx1ββββ+/−+130, 12, 2.54
        WH-01/29/002-2O26:H11H11++stx1ββββ+/++++130, 12, 2.54
        WH-01/29/002-3O26:H11H11++stx1ββββ+/++++130, 12, 2.54
        WH-01/29/002-4O26:H11H11++stx1ββββ+/++++130, 12, 2.54
        WH-01/29/002-5O26:H11H11++stx1ββββ+/++130, 12, 2.54
Day 106
    Animal 27 (farm A)
        WH-01/27/005-2O26:H11H11++stx1ββββ+/−+++145, 110, 123
        WH-01/27/005-5O26:H11H11++stx1ββββ+/++++130, 12, 2.55
        WH-01/27/005-6O26:H11H11++stx1ββββ+/+130, 12, 2.55
Day 113
    Animal 7 (farm C)
        WH-04/07/001-2O26:H11H11++++stx1/stx2ββββ+/+++55, 35, 2.511
        WH-04/07/001-4O26:H11H11++++stx1/stx2ββββ+/++++5512
        WH-04/07/001-6O26:H11H11++++stx1/stx2ββββ+/++++5512
Day 170
    Animal 22 (farm C)
        WH-04/22/001-1O26:H11H11++stx1ββββ+/++++110, 12, 6.312
        WH-04/22/001-4O26:H11H11++stx1ββββ+/++++110, 12, 6.312
        WH-04/22/001-5O26:H11H11++stx1ββββ+/++++110, 12, 6.312
Day 176
    Animal 14 (farm D)
        WH-03/14/004-8O26:H11H11++stx1ββββ+/+++11010
Day 218
    Animal 27 (farm A)
        WH-01/27/009-1O26:H11H11++++stx1/stx2ββββ+/++++110, 129
        WH-01/27/009-2O26:H11H11++++stx1/stx2ββββ+/++++110, 129
        WH-01/27/009-3O26:H11H11++++stx1/stx2ββββ+/++++110, 128
        WH-01/27/009-8O26:H11H11++++stx1/stx2ββββ+/++110, 128
        WH-01/27/009-9O26:H11H11++++stx1/stx2ββββ+/++++110, 129
Day 309
    Animal 29 (farm A)
        WH-01/29/010-1O26:H11H11++stx1ββββ+/++++110, 35, 124
        WH-01/29/010-2O26:H11H11++stx1ββββ+/++130, 55, 358
        WH-01/29/010-3O26:H11H11++stx1ββββ+/++++130, 35, 128
Day 365
    Animal 8 (farm C)
        WH-04/08/008-6O26:H11H11++stx1ββββ+/++++110, 5512
Day 379
    Animal 9 (farm A)
        WH-01/09/016-2O26:H32H32++stx1/stx2−/−145, 130, 1.81
    Animal 27 (farm A)
        WH-01/27/014-3O26:H11H11++stx1ββββ+/++++110, 129
        WH-01/27/014-4O26:H11H11++stx1ββββ+/++++110, 129
        WH-01/27/014-5O26:H11H11++stx1ββββ+/++++110, 128
Day 407
    Animal 29 (farm A)
        WH-01/29/013-4O26:H11H11++stx1ββββ+/++++110, 12, 2.58
        WH-01/29/013-7O26:H11H11++stx1ββββ+/++++110, 12, 2.58
Day 478
    Animal 27 (farm A)
        WH-01/27/017-1O26:H11H11++++stx1/stx2ββββ+/++++110, 128
        WH-01/27/017-5O26:H11H11++++stx1/stx2ββββ+/++++110, 128
        WH-01/27/017-6O26:H11H11++++stx1/stx2ββββ+/++++1108
        WH-01/27/017-7O26:H11H11++++stx1/stx2ββββ+/++++1108
        WH-01/27/017-10O26:H11H11+++stx1ββββ+/++++130, 12, 2.58
Open in a separate windowastx1/stx2, gene stx1 or stx2.befa1 was detected by two hybridizations (with lifA1-lifA2 and lifA3-lifA4 probes). +/+, complete gene; +/− or −/+, incomplete gene; −/−, efa1 negative.The serotyping of the O26 isolates was confirmed by the results of the fliC PCR-restriction fragment length polymorphism (RFLP) analysis performed according to Fields et al. (25), with slight modifications described by Zhang et al. (62). All O26:H11 isolates showed the H11 pattern described by Zhang et al. (62). In contrast, the O26:H32 isolate demonstrated a different fliC RFLP pattern that was identical to the H32 pattern described by the same authors. It has been demonstrated that EHEC O26:H11 strains belong to at least four different sequence types (STs) in the common clone complex 29 (39). In the multilocus sequence typing analysis for E. coli (61), the tested five EHEC O26:H11 isolates (WH-01/02/003-1, WH-01/20/005-3, WH-01/27/009-9, WH-03/14/004-8, and WH-04/22/001-1) of different farms and clusters were characterized as two sequence types (ST 21 and ST 396). The isolates from farms A and C belong to ST 21, the most frequent ST of EHEC O26:H11 isolates found in humans and animals (39), but the single isolate from farm D was characterized as ST 396.Typing and subtyping of genes (stx1 and/or stx2, eae, tir, espA, espB, EHEC-hlyA, katP, and espP) associated with EHEC were performed with LightCycler fluorescence PCR (48) and different block-cycler PCRs. To identify the subtypes of the stx2 genes and of the locus of enterocyte effacement-encoding genes eae, tir, espA, and espB, the PCR products were digested by different restriction endonucleases (19, 26, 46). The complete pattern of virulence markers was detected in most bovine isolates examined in our study. An stx1 gene was present in all O26 isolates. In addition, an stx2 gene was found in nine O26:H11 isolates in farm A and in three isolates of the same type in farm C, as well as in the O26:H32 isolate. Both Stx1 and Stx2 were closely related to families of Stx1 and Stx2 variants or alleles. EHEC isolates with stx2 genes are significantly more often associated with HUS and other severe disease manifestations than isolates with an stx1 gene, which are more frequently associated with uncomplicated diarrhea and healthy individuals (13). In contrast to STEC strains harboring stx2 gene variants, however, STEC strains of the stx2 genotype were statistically significantly associated with HUS (26). The stx2 genotype was found in all O26 isolates with an stx2 gene, while the GK3/GK4 amplification products after digestion with HaeIII and FokI restriction enzymes showed the typical pattern for this genotype described by Friedrich et al. (26). The nucleotide sequences of the A and B subunits of the stx2 gene of the selected bovine O26:H11 isolate WH-01/27/017-1 (GenBank accession no. EU700491) were identical to the stx2 genes of different sorbitol-fermenting EHEC O157:H− strains associated with human HUS cases and other EHEC infections in Germany (10) and 99.3% identical in their DNA sequences to the stx2 gene of the EHEC type strain EDL933, a typical O157:H7 isolate from an HUS patient. A characteristic stx1 genotype was present in all O26 isolates. The nucleotide sequences of the A and B subunits of the stx1 gene of the tested bovine O26:H11 isolate WH-01/27/017-1 (GenBank accession no. EU700490) were nearly identical to those of the stx1 genes of the EHEC O26:H11 reference type strains H19 and DEC10B, which had been associated with human disease outbreaks in Canada and Australia. Nucleotide exchanges typical for stx1c and stx1d subtypes as described by Kuczius et al. (38) were not found. All bovine O26:H11 strains produced an Stx1 with high cytotoxicity for Vero cells tested by Stx enzyme-linked immunosorbent assay and Vero cell neutralization assay (53). The Stx2 cytotoxicity for Vero cells was also very high in the O26:H11 isolates.Not only factors influencing the basic and inducible Stx production are important in STEC pathogenesis. It has been suggested that the eae and EHEC-hlyA genes are likely contributors to STEC pathogenicity (2, 3, 13, 50). Ritchie et al. (50) found both genes in all analyzed HUS-associated STEC isolates. In all O26:H11 isolates we obtained, stx genes were present in combination with eae genes. Only the O26:H32 isolate lacked an eae gene. To date, 10 distinct variants of eae have been described (1, 19, 36, 45, 47). Some serotypes were closely associated with a particular intimin variant: the O157 serogroup was linked to γ-eae, the O26 serogroup to β-eae, and the O103 serogroup to ɛ-eae (4, 19, 20, 58). Our study confirms these associations. All bovine O26:H11 isolates were also typed as members of the β-eae subgroup. A translocated intimin receptor gene (tir gene) and the type III secreted proteins encoded by the espA and espB genes were found in all 56 O26:H11 isolates but not in the O26:H32 isolate. These other tested locus of enterocyte effacement-associated genes belonged to the β-subgroups. These results are in accord with the results of China et al. (19), who detected the pathotypes β-eae, β-tir, β-espA, and β-espB in all investigated human O26 strains. Like the eae gene, the EHEC-hlyA gene was found in association with severe clinical disease in humans (52). Aldick et al. (2) showed that EHEC hemolysin is toxic (cytolytic) to human microvascular endothelial cells and may thus contribute to the pathogenesis of HUS. In our study, the EHEC-hlyA gene was detected in 50 of the 56 bovine E. coli O26:H11 isolates which harbored virulence-associated plasmids of different sizes (Table (Table1).1). The presence of virulence-associated plasmids corresponded to the occurrence of additional virulence markers such as the espP and katP genes (17). The katP gene and the espP gene were detected in 49 and 50 of the 56 O26:H11 isolates, respectively. The espP gene was missing in six of the seven bovine O26:H11 isolates in which the katP genes were also absent. Both genes were not found in the O26:H32 isolate (Table (Table1).1). Although we found large plasmids of the same size in O26:H11 isolates, they lacked one or more of the plasmid-associated virulence factors (Table (Table1).1). Two DNA probes were used to detect the efa1 genes by colony hybridization. (DNA probes were labeled with digoxigenin [DIG] with lifA1-lifA2 and lifA3-lifA4 primers [14] using the PCR DIG probe synthesis kit [Roche Diagnostics, Mannheim, Germany]; DIG Easy Hyb solution [Roche] was used for prehybridization and hybridization.) Positive results with both DNA probes were obtained for 52 of 56 E. coli O26:H11 isolates. A positive signal was only found in three isolates with the lifA1-lifA2 DNA probe and in one isolate with the lifA3-lifA4 probe. An efa1 gene was not detected in the O26:H32 isolate (Table (Table11).We also analyzed the spatial and temporal behavior of the O26:H11/H32 isolates in the beef herds by cluster analysis (conducted in PAUP* for Windows version 4.0, 2008 [http://paup.csit.fsu.edu/about.html]). This was performed with distance matrices using the neighbor-joining algorithm, an agglomerative cluster method which generates a phylogenetic tree. The distance matrices were calculated by pairwise comparisons of the fragmentation patterns produced by genomic typing through pulsed-field gel electrophoresis analysis with four restriction endonucleases (XbaI, NotI, BlnI, and SpeI) and the presence or absence of potential virulence markers (Fig. (Fig.11 and Table Table1).1). To this end, the total character difference was used, which counts the pairwise differences between two given patterns. During a monitoring program of 3 years in four cattle farms (29), different O26:H11 cluster groups and one O26:H32 isolate were detected in three different farms. The genetic distance of the O26:H32 isolate was very high relative to the O26:H11 isolates. Therefore, the O26:H32 isolate was outgrouped. The O26:H11 isolates of each farm represented independent cluster groups. The single isolate from farm D fitted better to the isolates from farm C than to those from farm A. This finding is in accord with the geographical distance between the farms. The fact that the farms were located in neighboring villages may suggest that direct or indirect connections between the farms were possible (e.g., by person contacts or animal trade). However, the isolates from farm C and farm D belonged to different sequence types (ST 21 and ST 396), which may argue against a direct connection. Interestingly, O26:H11 isolates with and without stx2 genes were detected in the same clusters. This phenomenon was observed in both farm A and farm C. In farm A, the isolates with additional stx2 genes were found in animal 27 and were grouped in clusters 8 and 9 (day 218). An stx2 gene was repeatedly found (four isolates) in the same animal (animal 27). The isolates grouped in cluster 8 on a later day of sampling (day 478). All other O26:H11 isolates grouped in the same clusters and obtained from the same animals (27 and 29) on different sampling days lacked an stx2 gene. Also, the isolates obtained from animal 27 on previous sampling days, which grouped in clusters 3 and 5, exhibited no stx2 genes. In farm C, the three isolates with additional stx2 genes obtained from animal 7 grouped in clusters 11 and 12. An stx2 gene was absent from all other O26:H11 isolates grouped in the same cluster 12 on later sampling days, and no other isolates of cluster 11 were found later on. However, we detected members of many clusters over relatively long periods (clusters 5, 8, and 9 in farm A and cluster 12 in farm C), but members of other clusters were only found on single occasions. This patchy temporal pattern is apparently not a unique property of O26:H11, as we found similar results for cluster groups of other EHEC serotypes of bovine origin (28). The isolates grouped in the dominant cluster 8 were found on 5 of 9 sampling days over a period of 10 months. In contrast, we found the members of clusters 4, 5, 9, and 12 only on two nonconsecutive sampling days. The period during which isolates of these groups were not detected was particularly long for cluster 4 (231 days). We also observed the coexistence of different clusters over long periods in the same farm and in the same cattle (clusters 8 and 9), while one of the clusters dominated. Transmission of clusters between cattle was also observed. These results suggest that some of the EHEC O26:H11 strains had the potential for a longer persistence in the host population, while others had not. The reasons for this difference are not yet clear. Perhaps the incomplete efa1 gene found in isolates of clusters which were only detected once might explain why some strains disappeared rapidly. Efa1 has been discussed as a potential E. coli colonization factor for the bovine intestine used by non-O157 STEC, including O26 (54, 56). The O165:H25 cluster detected during a longer period in farm B may have disappeared after it had lost its efa1 gene (28). The precise biological activity of Efa1 in EHEC O26 is not yet known, but it has been demonstrated that the molecule is a non-Stx virulence determinant which can increase the virulence of EHEC O26 in humans (8).Open in a separate windowFIG. 1.Neighbor-joining tree of bovine E. coli O26:H11/H32 strains based on the restriction pattern obtained after digestion with XbaI, NotI, BlnI, and SpeI.We distinguished 12 different clusters, but complete genetic identity was only found in two isolates. The variations in the O26:H11 clusters may be due to increasing competition between the bacterial populations of the various subtypes in the bovine intestine or to potential interactions between EHEC O26:H11 and the host.The ephemeral occurrence of additional stx2 genes in different clusters and farms may be the result of recombination events due to horizontal gene transfer (16). The loss of stx genes may occur rapidly in the course of an infection, but the reincorporation by induction of an stx-carrying bacteriophage into the O26:H11 strains is possible at any time (9, 40). Nevertheless, an additional stx2 gene may increase the dangerousness of the respective EHEC O26:H11 strains. While all patients involved in an outbreak caused by an EHEC O26:H11 strain harboring the gene encoding Stx2 developed HUS (41), the persons affected by another outbreak caused by an EHEC O26:H11 strain that produced exclusively Stx1 had only uncomplicated diarrhea (60).In conclusion, our results showed that bovine O26:H11 isolates can carry virulence factors of EHEC that are strongly associated with EHEC-related disease in humans, particularly with severe clinical manifestations such as hemorrhagic colitis and HUS. Therefore, strains of bovine origin may represent a considerable risk for human infection. Moreover, some clusters of EHEC O26:H11 persisted in cattle and farms over longer periods, which may increase the risk of transmission to other animals and humans even further.  相似文献   

20.
Vertebrate genomic assemblies were analyzed for endogenous sequences related to any known viruses with single-stranded DNA genomes. Numerous high-confidence examples related to the Circoviridae and two genera in the family Parvoviridae, the parvoviruses and dependoviruses, were found and were broadly distributed among 31 of the 49 vertebrate species tested. Our analyses indicate that the ages of both virus families may exceed 40 to 50 million years. Shared features of the replication strategies of these viruses may explain the high incidence of the integrations.It has long been appreciated that retroviruses can contribute significantly to the genetic makeup of host organisms. Genes related to certain other viruses with single-stranded RNA genomes, formerly considered to be most unlikely candidates for such contribution, have recently been detected throughout the vertebrate phylogenetic tree (1, 6, 13). Here, we report that viruses with single-stranded DNA (ssDNA) genomes have also contributed to the genetic makeup of many organisms, stretching back as far as the Paleocene period and possibly the late Cretaceous period of evolution.Determining the evolutionary ages of viruses can be problematic, as their mutation rates may be high and their replication may be rapid but also sporadic. To establish a lower age limit for currently circulating ssDNA viruses, we analyzed 49 published vertebrate genomic assemblies for the presence of sequences derived from the NCBI RefSeq database of 2,382 proteins from known viruses in this category, representing a total of 23 classified genera from 7 virus families. Our survey uncovered numerous high-confidence examples of endogenous sequences related to the Circoviridae and to two genera in the family Parvoviridae: the parvoviruses and dependoviruses (Fig. (Fig.11).Open in a separate windowFIG. 1.Phylogenetic tree of vertebrate organisms and history of ssDNA virus integrations. Times of integration of ancestral dependoviruses (yellow icosahedrons), parvoviruses (blue icosahedrons), and circoviruses (triangles) are approximate.The Dependovirus and Parvovirus genomes are typically 4 to 6 kb in length, include 2 major open reading frames (encoding replicase proteins [Rep and NS1, respectively] and capsid proteins [Cap and VP1, respectively]), and have characteristic hairpin structures at both ends (Fig. (Fig.2).2). For replication, these viruses depend on host enzymes that are recruited by the viral replicase proteins to the hairpin regions, where self-primed viral DNA synthesis is initiated (2). Circovirus genomes are typically ∼2-kb circles. DNA of the type species, porcine circovirus 1 (PCV-1), contains a stem-loop structure within the origin of replication (Fig. (Fig.2),2), and the largest open reading frame includes sequences that are homologous to the Parvovirus replicase open reading frame (9, 11). The circoviruses also depend on host enzymes for replication, and DNA synthesis is self-primed from a 3′-OH end formed by endonucleolytic cleavage of the stem-loop structure (4). The frequency of Dependovirus infection is estimated to be as high as 90% within an individual''s lifetime. None of the dependoviruses have been associated with human disease, but related viruses in the family Parvoviridae (e.g., erythrovirus B19 and possibly human bocavirus) are pathogenic for humans, and members of both the Parvoviridae and the Circoviridae can cause a variety of animal diseases (2, 4).Open in a separate windowFIG. 2.Schematics illustrating the structure and organization of Parvoviridae and Circoviridae genomes and origins of several of the longest-integrated ancestral viral sequences found in vertebrates. Integrations were aligned to the Dependovirus adeno-associated virus 2 (AAV2), the Parvovirus minute virus of mice (MVM), and the Circovirus porcine circovirus 1 (PCV-1). The inverted terminal repeat (ITR) sequences in the Dependovirus and Parvovirus genomes are depicted on an expanded scale. A linear representation of the circular genome of PCV-1 is shown with the 10-bp stem-loop structure on an expanded scale. Horizontal lines beneath the maps indicate the lengths of similar sequences that could be identified by BLAST. The numbers indicate the locations of amino acids in the viral proteins where the sequence similarities in the endogenous insertions start and end. The actual ancestral virus-derived integrated sequences may extend beyond the indicated regions.With some ancestral endogenous sequences that we identified, phylogenetic comparisons can be used to estimate age. For example, as a Dependovirus-like sequence is present at the same location in the genomes of mice and rats, the ancestral virus must have existed before their divergence, more than 20 million years ago. Some Circovirus- and Dependovirus-related integrations also predate the split between dog and panda, about 42 million years ago. However, in most other cases, we rely on an indirect method for estimating age (1). As genomic sequences evolve, they accumulate new stop codons and insertion/deletion-induced frameshifts. The rates of these events can be tied directly to the rates of neutral sequence drift and, therefore, the time of evolution. To apply this method, we first performed a BLAST search of vertebrate genomes for all known ssDNA virus proteins (BLAST options, -p tblastn -M BLOSUM62 -e 1e−4). Candidate sequences were then recorded, along with 5 kb of flanking regions, and then again aligned against the database of ssDNA viruses to find the most complete alignment (BLAST options, -t blastx -F F -w 15 -t 1500 -Z 150 -G 13 -E 1 -e 1e−2). Detected alignments were then compared with a neutral model of genome evolution, as described in the supplemental material, and the numbers of stop codons and frameshifts were converted into the expected genomic drift undergone by the sequences. The age of integration was then estimated from the known phylogeny of vertebrates (7, 10). Using these methods, we discovered that as many as 110 ssDNA virus-related sequences have been integrated into the 49 vertebrate genomes considered, during a time period ranging from the present to over 40 to 60 million years ago (Table (Table1;1; see also Tables S1 to S3 in the supplemental material).

TABLE 1.

Selected endogenous sequences in vertebrate genomes related to single-stranded DNA viruses
Virus group and vertebrate speciesInitial genomic search using TBLASTN
Best sequence homology identified using BLASTX
Predicted nucleotide drift (%)Integration labelAge (million yr) or timing of integration based on sequence aging
Chromosomal or scaffold locationProteinBLAST E value/% sequence identityMost similar virusaProteinCoordinatesNo. of stop codons/frameshifts
Circoviruses
    CatScaffold_62068Rep6E−05/37Canary circovirusRep4-2833/7 in 268 aab14.2fcECLG-182
Scaffold_24038Rep6E−06/51Columbid circovirusRep44-3174/5 in 231 aac15.2fcECLG-287
    DogChr5dRep7E−16/46Raven circovirusRep16-2636/5 in 250 aa17.6cfECLG-198
Chr22Rep1E−14/43Beak and feather disease virusRep7-2642/1 in 261 aac4.5cfECLG-254
    OpossumChr3Rep4E−46/44Finch circovirusRep2-2910/2 in 282 aa2.3mdECLG12
Cap6-360/0 in 30 aa
Dependoviruses
    DogChrXRep6E−05/55AAV5Rep239-4453/4 in 200 aa14.0cfEDLG-178
    DolphinGeneScaffold1475Rep8E−39/39Avian AAV DA1Rep79-4863/4 in 379 aac6.6ttEDLG-255
Cap4E−61/47Cap1-7384/7 in 678 aac
    ElephantScaffold_4Rep0/55AAV5Rep3-5890/0 in 579 aa0.0laEDLGRecent
    HyraxGeneScaffold5020Cap3E−34/53AAV3Cap485-7350/5 in 256 aa7.0pcEDLG-129
Scaffold_19252Rep9E−72/47Bovine AAVRep2-3488/4 in 348 aa14.3pcEDLG-260
    MegabatScaffold_5601Rep2E−13/31AAV2Rep315-4791/5 in 175 aa13.1pvEDLG-376
    MicrobatGeneScaffold2026Rep1E−117/50AAV2Rep1-6172/5 in 612 aa5.8mlEDLG-127
Cap9E−33/51Cap1-7312/9 in 509 aac
Scaffold_146492Cap6E−32/42AAV2Cap479-7320/3 in 252 aa4.2mlEDLG-219
    MouseChr1Rep2E−06/34AAV2Rep4-2063/5 in 191 aa17.1mmEDLG-139
Chr3Rep2E−24/31AAV5Rep71-47812/7 in 389 aa16.5mmEDLG-237
Cap2E−22/45Cap22-72412/10 in 649aac
Chr8Rep1E−08/46AAV2Rep314-4733/3 in 147 aa13.8mmEDLG-331
Cap1-1371/2 in 114 aa
    PandaScaffold2359Rep2E−06/37Bovine AAVRep238-4262/3 in 186 aa10.4amEDLG-159
    PikaScaffold_9941Rep4E−14/28AAV5Rep126-4152/2 in 282 aa5.4opEDLG14
    PlatypusChr2Rep9E−10/35Bovine AAVRep297-4374/3 in 138 aa17.1oaEDLG-179
Cap272-4191/2 in 150 aac
Contig12430Rep2E−09/47Bovine AAVRep353-4503/1 in 123 aa12.0oaEDLG-255
Cap2E−05/32Cap253-3672/1 in 116 aa
    RabbitChr10Rep3E−97/39AAV2Rep1-6193/9 in 613 aa9.3ocEDLG43
Cap5E−50/45Cap1-72310/9 in 675 aa
    RatChr13Rep2E−09/33AAV2Rep4-1752/4 in 177 aa13.3rnEDLG-128
Chr2Rep4E−18/40AAV5Rep1-46112/12 in 454 aa22.7rnEDLG-251
Chr19Rep2E−07/33AAV5Rep329-4642/4 in 136 aa16.1rnEDLG-335
Cap31-1332/1 in 93 aa
    TarsierScaffold_178326Rep4E−14/23AAV5Rep96-4652/3 in 356 aa5.3tsEDLG23
Parvoviruses
    Guinea pigScaffold_188Rep3E−24/46Porcine parvovirusRep313-5675/3 in 250 aa12.3cpEPLG-140
Cap1E−16/36Cap10-68911/12 in 672 aa
Scaffold_27Rep1E−50/39Canine parvovirusRep11-6401/4 in 616 aa5.3cpEPLG-217
Cap1E−38/39Porcine parvovirusCap3-7192/14 in 700 aa
    TenrecScaffold_260946Rep2E−20/38LuIII virusRep406-5984/4 in 190 aa19.0etEPLG-260
Cap11-63916/15 in 595 aa
    RatChr5Rep6E−10/56Canine parvovirusRep1-2820/0 in 312 aa0.6rnEPLGRecent
Cap0/62Cap637-6670/2 in 760 aa
Rep0/631-751
    OpossumChr3Rep2E−39/33LuIII virusRep7-57011/3 in 502 aa10.9mdEPLG-256
Cap7E−8/33Cap11-72914/7 in 704 aa
Chr6Rep6E−58/44Porcine parvovirusRep16-5633/7 in 534 aac4.6mdEPLG-324
Cap6E−60/38Cap10-7152/5 in 707 aac
    WallabyScaffold_108040Rep4E−74/62Canine parvovirusRep341-6450/0 in 287 aa1.3meEPLG-37
Cap8E−37/32Cap35-7380/4 in 687 aa
Scaffold_72496Rep2E−61/42Porcine parvovirusRep23-5674/3 in 531 aa5.7meEPLG-630
Cap2E−31/38Cap10-5326/4 in 514 aa
Scaffold_88340Rep7E−37/55Mouse parvovirus 1Rep344-5660/3 in 223 aa6.7meEPLG-1636
Cap7E−22/33Cap11-7136/9 in 700 aa
Open in a separate windowaSome ambiguity in choosing the most similar virus is possible. We generally used the alignment with the lowest E value in the BLAST results. However, one or two points in the exponent of an E value were sometimes sacrificed to achieve a longer sequence alignment.baa, amino acids.cThese sequences have long insertions compared to the present-day viruses. In all cases tested, these insertions originated from short interspersed elements (SINEs). These insertions were excluded from the counts of stop codons and frameshifts and the estimation of integration age.dChr, chromosome.It is important to recognize that there is an intrinsic limit on how far back in time we can reach to identify ancient endogenous viral sequences. First, the sequences must be identified with confidence by BLAST or similar programs. This requirement places a lower limit on sequence identity at about 20 to 30% of amino acids, or about 75% of nucleotides (nucleotides evolve nearly 2.5 times slower than the amino acid sequence they encode). Second, the related, present-day virus must have evolved at a rate that is not much higher than that of the endogenous sequences. The viruses for which ancestral endogenous sequences were identified in this study exhibit sequence drift similar to that associated with mammalian genomes. Setting this rate at 0.14% per million years of evolution (8), we arrive at 90 million years as the theoretical limit for the oldest sequences that can be identified using our methods. This limit drops to less than 35 million years for endogenous viral sequences in rodents and even lower for sequences related to viruses that evolve faster than mammalian genomes.The most widespread integrations found in our survey are derived from the dependoviruses. These include nearly complete genomes related to adeno-associated virus (AAV) in microbat, wallaby, dolphin, rabbit, mouse, and baboon (Fig. (Fig.2).2). We did not detect inverted terminal repeats in several integrations tested, even though repeats are common in the present-day dependoviruses. This result could be explained by sequence decay or the absence of such structures in the ancestral viruses. However, we do see sequences that resemble degraded hairpin structures to which Dependovirus Rep proteins bind, with an example from microbat integration mlEDLG-1 shown in Fig. Fig.3.3. The second most widespread endogenous sequences are related to the parvoviruses. They are found in 6 of 49 vertebrate species considered, with nearly complete genomes in rat, opossum, wallaby, and guinea pig (Fig. (Fig.22).Open in a separate windowFIG. 3.Hairpin structure of the inverted terminal repeat of adeno-associated virus 2 (left) and a candidate degraded hairpin structure located close to the 5′ end of the mlEDLG-1 integration in microbats (right). Structures and mountain plots were generated using default parameters of the RNAfold program (5), with nucleotide coloring representing base-pairing probabilities: blue is below average, green is average, and red is above average. Mountain plots represent hairpin structures based on minimum free energy (mfe) calculations and partition function (pf) calculations, as well as the centroid structure (5). Height is expressed in numbers of nucleotides; position represents nucleotide.The Dependovirus AAV2 has strong bias for integration into human chromosome 19 during infection, driven by a host sequence that is recognized by the viral Rep protein(s). Rep mediates the formation of a synapse between viral and cellular sequences, and the cellular sequences are nicked to serve as an origin of viral replication (14). The related integrations in mice and rats, located in the same chromosomal locations, might be explained by such a mechanism. However, the extent of endogenous sequence decay and the frequency of stop codons indicate that these integrations occurred some 30 to 35 million years ago, implying that they are derived from a single event in a rodent ancestor rather than two independent integration events at the same location. Similarly, integrations EDLG-1 in dog and panda lie in chromosomal regions that can be readily aligned (based on University of California—Santa Cruz [UCSC] genome assemblies) and show sequence decay consistent with the age of the common ancestor, about 42 million years. Endogenous sequences related to the family Parvoviridae can thus be traced to over 40 million years back in time, and viral proteins related to this family have remained over 40% conserved.Sequences related to circoviruses were detected in five vertebrate species (Table (Table11 and Table S1 in the supplemental material). At least one of these sequences, the endogenous sequence in opossum, likely represents a recent integration. Several integrations in dog, cat, and panda, on the other hand, appear to date from at least 42 million years ago, which is the last time when pandas and dogs shared a common ancestor. We see evidence for this age in data from sequence degradation (Table (Table1),1), phylogenetic analyses of endogenous Circovirus-like genomes (see Fig. S2 in the supplemental material), and genomic synteny where integration ECLG-3 is surrounded by genes MTA3 and ARID5A in both dog and panda and integration ECLG-2 lies 35 to 43 kb downstream of gene UPF3A. In fact, Circovirus integrations may even precede the split between dogs and cats, about 55 million years ago, although the preliminary assembly and short genomic contigs for cats make synteny analysis impossible.The most common Circovirus-related sequences detected in vertebrate genomes are derived from the rep gene. We speculate that, like those of the Parvoviridae, the ancestral Circoviridae sequences might have been copied using a primer sequence in the host DNA that resembled the viral origin and was therefore recognized by the virus Rep protein. Higher incidence of rep gene identifications may represent higher conservation of this gene with time, or alternatively, possession of these sequences may impart some selective advantage to the host species. The largest Circovirus-related integration detected, in the opossum, comprises a short fragment of what may have been the cap gene immediately adjacent to and in the opposite orientation from the rep gene. This organization is similar to that of the present day Circovirus genome in which these genes share a promoter in the hairpin regions but are translated in opposite directions (Fig. (Fig.22).In summary, our results indicate that sequences derived from ancestral members of the families Parvoviridae and Circoviridae were integrated into their host''s genomes over the past 50 million years of evolution. Features of their replication strategies suggest mechanisms by which such integrations may have occurred. It is possible that some of the endogenous viral sequences could offer a selective advantage to the virus or the host. We note that rep open reading frame-derived proteins from some members of these families kill tumor cells selectively (3, 12). The genomic “fossils” we have discovered provide a unique glimpse into virus evolution but can give us only a lower estimate of the actual ages of these families. However, numerous recent integrations suggest that their germ line transfer has been continuing into present times.   相似文献   

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