共查询到20条相似文献,搜索用时 93 毫秒
1.
Sandra Wydau Guillaume van der Rest Caroline Aubard Pierre Plateau Sylvain Blanquet 《The Journal of biological chemistry》2009,284(21):14096-14104
Several l-aminoacyl-tRNA synthetases can transfer a
d-amino acid onto their cognate tRNA(s). This harmful reaction is
counteracted by the enzyme d-aminoacyl-tRNA deacylase. Two distinct
deacylases were already identified in bacteria (DTD1) and in archaea (DTD2),
respectively. Evidence was given that DTD1 homologs also exist in nearly all
eukaryotes, whereas DTD2 homologs occur in plants. On the other hand, several
bacteria, including most cyanobacteria, lack genes encoding a DTD1 homolog.
Here we show that Synechocystis sp. PCC6803 produces a third type of
deacylase (DTD3). Inactivation of the corresponding gene (dtd3)
renders the growth of Synechocystis sp. hypersensitive to the
presence of d-tyrosine. Based on the available genomes, DTD3-like
proteins are predicted to occur in all cyanobacteria. Moreover, one or several
dtd3-like genes can be recognized in all cellular types, arguing in
favor of the nearubiquity of an enzymatic function involved in the defense of
translational systems against invasion by d-amino acids.Although they are detected in various living organisms (reviewed in Ref.
1), d-amino acids
are thought not to be incorporated into proteins, because of the
stereospecificity of aminoacyl-tRNA synthetases and of the translational
machinery, including EF-Tu and the ribosome
(2). However, the
discrimination between l- and d-amino acids by
aminoacyl-tRNA synthetases is not equal to 100%. Significant
d-aminoacylation of their cognate tRNAs by Escherichia
coli tyrosyl-, tryptophanyl-, aspartyl-, lysyl-, and histidyl-tRNA
synthetases has been characterized in vitro
(3–9).
Recently, using a bacterium, transfer of d-tyrosine onto
tRNATyr was shown to occur in vivo
(10).With such misacylation reactions, the resulting
d-aminoacyl-tRNAs form a pool of metabolically inactive molecules,
at best. At worst, d-aminoacylated tRNAs infiltrate the protein
synthesis machinery. Although the latter harmful possibility has not yet been
firmly established, several cells were shown to possess a
d-tyrosyl-tRNA deacylase, or DTD, that should help them counteract
the accumulation of d-aminoacyl-tRNAs. This enzyme shows a broad
specificity, being able to remove various d-aminoacyl moieties from
the 3′-end of a tRNA
(4–6,
11). Such a function makes the
deacylase a member of the family of enzymes capable of editing in
trans mis-aminoacylated tRNAs. This family includes several homologs
of aminoacyl-tRNA synthetase editing domains
(12), as well as peptidyl-tRNA
hydrolase (13,
14).Two distinct deacylases have already been discovered. The first one, called
DTD1, is predicted to occur in most bacteria and eukaryotes (see
d-amino acids, including
d-tyrosine (6). In
fact, in an E. coli Δdtd strain grown in the presence
of 2.4 mm d-tyrosine, as much as 40% of the cellular
tRNATyr pool becomes esterified with d-tyrosine
(10).
Open in a separate windowHomologs of dtd/DTD1 are not found in the available archaeal
genomes except that of Methanosphaera stadtmanae. A search for
deacylase activity in Sulfolobus solfataricus and Pyrococcus
abyssi led to the detection of another enzyme (DTD2), completely
different from the DTD1 protein
(15). Importing dtd2
into E. coli functionally compensates for dtd deprivation.
As shown in 16).Several cells contain neither dtd nor dtd2 homologs
(d-tyrosyl-tRNA deacylase
(DTD3). This protein, encoded by dtd3, behaves as a metalloenzyme.
Sensitivity of the growth of Synechocystis to external
d-tyrosine is strongly exacerbated by the disruption of
dtd3. Moreover, expression of the Synechocystis DTD3 in a
Δdtd E. coli strain, from a plasmid, restores the resistance of
the bacterium to d-tyrosine. Finally, using the available genomes,
we examined the occurrence of DTD3 in the living world. The prevalence of
DTD3-like proteins is surprisingly high. It suggests that the defense of
protein synthesis against d-amino acids is universal. 相似文献
TABLE 1
Distribution of DTD1 and DTD2 homologs in various phylogenetic groupsHomologs of DTD1 and DTD2 were searched for using a genomic Blast analysis against complete genomes in the NCBI Database (www.ncbi.nlm.nih.gov). Values in the table are number of species. For instance, E. coli is counted only once in γ-proteobacteria despite the fact that several E. coli strains have been sequenced.DTD1 | DTD2 | DTD1 + DTD2 | None | |
---|---|---|---|---|
Bacteria | ||||
Acidobacteria | 2 | 0 | 0 | 0 |
Actinobacteria | 27 | 0 | 0 | 8 |
Aquificae | 1 | 0 | 0 | 0 |
Bacteroidetes/Chlorobi | 12 | 0 | 0 | 5 |
Chlamydiae | 1 | 0 | 0 | 6 |
Chloroflexi | 4 | 0 | 0 | 0 |
Cyanobacteria | 5 | 0 | 0 | 16 |
Deinococcus/Thermus | 4 | 0 | 0 | 0 |
Firmicutes | ||||
Bacillales | 19 | 0 | 0 | 0 |
Clostridia | 19 | 0 | 0 | 0 |
Lactobacillales | 23 | 0 | 0 | 0 |
Mollicutes | 0 | 0 | 0 | 15 |
Fusobacteria/Planctomycetes | 2 | 0 | 0 | 0 |
Proteobacteria | ||||
α | 6 | 0 | 0 | 55 |
β | 24 | 0 | 0 | 11 |
γ | 80 | 0 | 0 | 8 |
δ | 15 | 0 | 0 | 0 |
ε | 1 | 0 | 0 | 12 |
Spirochaetes | 0 | 0 | 0 | 7 |
Thermotogae | 5 | 0 | 0 | 0 |
Archaea | ||||
Crenarchaeota | 0 | 13 | 0 | 0 |
Euryarchaeota | 1 | 26 | 0 | 2 |
Nanoarchaeota | 0 | 0 | 0 | 1 |
Eukaryota | ||||
Dictyosteliida | 1 | 0 | 0 | 0 |
Fungi/Metazoa | ||||
Fungi | 13 | 0 | 0 | 1 |
Metazoa | 19 | 0 | 0 | 0 |
Kinetoplastida | 3 | 0 | 0 | 0 |
Viridiplantae | 4 | 4 | 4 | 0 |
2.
Dahrouge S Hogg WE Russell G Tuna M Geneau R Muldoon LK Kristjansson E Fletcher J 《CMAJ》2012,184(2):E135-E143
Background:
Several jurisdictions attempting to reform primary care have focused on changes in physician remuneration. The goals of this study were to compare the delivery of preventive services by practices in four primary care funding models and to identify organizational factors associated with superior preventive care.Methods:
In a cross-sectional study, we included 137 primary care practices in the province of Ontario (35 fee-for-service practices, 35 with salaried physicians [community health centres], 35 practices in the new capitation model [family health networks] and 32 practices in the established capitation model [health services organizations]). We surveyed 288 family physicians. We reviewed 4108 randomly selected patient charts and assigned prevention scores based on the proportion of eligible preventive manoeuvres delivered for each patient.Results:
A total of 3284 patients were eligible for at least one of six preventive manoeuvres. After adjusting for patient profile and contextual factors, we found that, compared with prevention scores in practices in the new capitation model, scores were significantly lower in fee-for-service practices (β estimate for effect on prevention score = −6.3, 95% confidence interval [CI] −11.9 to −0.6) and practices in the established capitation model (β = −9.1, 95% CI −14.9 to −3.3) but not for those with salaried remuneration (β = −0.8, 95% CI −6.5 to 4.8). After accounting for physician characteristics and organizational structure, the type of funding model was no longer a statistically significant factor. Compared with reference practices, those with at least one female family physician (β = 8.0, 95% CI 4.2 to 11.8), a panel size of fewer than 1600 patients per full-time equivalent family physician (β = 6.8, 95% CI 3.1 to 10.6) and an electronic reminder system (β = 4.6, 95% CI 0.4 to 8.7) had superior prevention scores. The effect of these three factors was largely but not always consistent across the funding models; it was largely consistent across the preventive manoeuvres.Interpretation:
No funding model was clearly associated with superior preventive care. Factors related to physician characteristics and practice structure were stronger predictors of performance. Practices with one or more female physicians, a smaller patient load and an electronic reminder system had superior prevention scores. Our findings raise questions about reform initiatives aimed at increasing patient numbers, but they support the adoption of information technology.Primary care providers are increasingly interested in ensuring that preventive health care be part of their work routines.1 This reorientation fits with the evidence that recommendations from family practitioners increase substantially the likelihood of patients undergoing preventive manoeuvres,2 whereas the lack of such recommendations has been linked with patient noncompliance.3,4Studies evaluating adherence to recommended preventive care suggest that the most pervasive barriers rest with the organization of the health care system and the practice itself, such as the absence of external financial incentives for the work done and the lack of a reminder system in the office.3,5–9Countries attempting to reform their delivery of primary care and improve the delivery of preventive services have often directed their efforts in finding alternatives to the traditional fee-for-service model, in which providers receive payment for each service provided. There are two predominant alternative funding models: capitation (providers receive a fixed lump-sum payment per patient per period, independent of the number of services performed) and salaried remuneration. Some health care systems blend components of fee for service with either of these models or offer additional incentives for reaching defined quality-of-care targets. Despite considerable rhetoric, there is little evidence to point to the remuneration models associated with superior delivery of primary care services.10 The complexity of health care systems makes the evaluation of models through international comparisons difficult.In Canada, the province of Ontario has four primary care funding models (11Table 1:
Characteristics of the four primary care models in the province of Ontario in 2005/06Fee for service | Capitation | ||||
---|---|---|---|---|---|
Characteristic | Salaried (community health centres)* | Traditional* | Reformed† | New (family health networks) | Established (health services organizations) |
Year introduced | 1970s | – | 2004 | 2001 | 1970s |
Group size, no. of physicians | > 1 (no specific size requirement) | 1 | ≥ 3 | ≥ 3 | ≥ 3 |
Physician remuneration | Salary | Fee for service | Fee for service and incentives | Capitation with 10% fee- for-service component, and incentives | Capitation and incentives |
Patient enrolment | Required; no limit on size of roster | Not required | Required; no limit on size of roster | Required; disincentive to enrol > 2400 | Required; disincentive to enrol > 2400 |
Incentive for enhanced preventive care‡ | |||||
Influenza immunization (age ≥ 65 yr) | None | None | None | April 2002 | July 2003 |
Colorectal cancer screening (age 50–74 yr) | None | None | April 2006 | April 2006 | April 2006 |
Breast cancer screening (age 50–70 yr) | None | None | None | April 2002 | April 2003 |
Cervical cancer screening (age 35–70 yr) | None | None | None | April 2002 | April 2003 |
3.
C. P. A. de Haan R. Kivist? M. L. H?nninen 《Applied and environmental microbiology》2010,76(20):6942-6943
Cj0859c variants fspA1 and fspA2 from 669 human, poultry, and bovine Campylobacter jejuni strains were associated with certain hosts and multilocus sequence typing (MLST) types. Among the human and poultry strains, fspA1 was significantly (P < 0.001) more common than fspA2. FspA2 amino acid sequences were the most diverse and were often truncated.Campylobacter jejuni is the leading cause of bacterial gastroenteritis worldwide and responsible for more than 90% of Campylobacter infections (7). Case-control studies have identified consumption or handling of raw and undercooked poultry meat, drinking unpasteurized milk, and swimming in natural water sources as risk factors for acquiring domestic campylobacteriosis in Finland (7, 9). Multilocus sequence typing (MLST) has been employed to study the molecular epidemiology of Campylobacter (4) and can contribute to virulotyping when combined with known virulence factors (5). FspA proteins are small, acidic, flagellum-secreted nonflagellar proteins of C. jejuni that are encoded by Cj0859c, which is expressed by a σ28 promoter (8). Both FspA1 and FspA2 were shown to be immunogenic in mice and protected against disease after challenge with a homologous strain (1). However, FspA1 also protected against illness after challenge with a heterologous strain, whereas FspA2 failed to do the same at a significant level. Neither FspA1 nor FspA2 protected against colonization (1). On the other hand, FspA2 has been shown to induce apoptosis in INT407 cells, a feature not exhibited by FspA1 (8). Therefore, our aim was to study the distributions of fspA1 and fspA2 among MLST types of Finnish human, chicken, and bovine strains.In total, 367 human isolates, 183 chicken isolates, and 119 bovine isolates (n = 669) were included in the analyses (3). PCR primers for Cj0859c were used as described previously (8). Primer pgo6.13 (5′-TTGTTGCAGTTCCAGCATCGGT-3′) was designed to sequence fspA1. Fisher''s exact test or a chi-square test was used to assess the associations between sequence types (STs) and Cj0859c. The SignalP 3.0 server was used for prediction of signal peptides (2).The fspA1 and fspA2 variants were found in 62.6% and 37.4% of the strains, respectively. In 0.3% of the strains, neither isoform was found. Among the human and chicken strains, fspA1 was significantly more common, whereas fspA2 was significantly more frequent among the bovine isolates (Table (Table1).1). Among the MLST clonal complexes (CCs), fspA1 was associated with the ST-22, ST-45, ST-283, and ST-677 CCs and fspA2 was associated with the ST-21, ST-52, ST-61, ST-206, ST-692, and ST-1332 CCs and ST-58, ST-475, and ST-4001. Although strong CC associations of fspA1 and fspA2 were found, the ST-48 complex showed a heterogeneous distribution of fspA1 and fspA2. Most isolates carried fspA2, and ST-475 was associated with fspA2. On the contrary, ST-48 commonly carried fspA1 (Table (Table1).1). In our previous studies, ST-48 was found in human isolates only (6), while ST-475 was found in both human and bovine isolates (3, 6). The strict host associations and striking difference between fspA variants in human ST-48 isolates and human/bovine ST-475 isolates suggest that fspA could be important in host adaptation.
Open in a separate windowaIn 0.3% of the strains, neither isoform was found. NF, not found.bNA, not associated.A total of 28 isolates (representing 6 CCs and 13 STs) were sequenced for fspA1 and compared to reference strains NCTC 11168 and 81-176. All isolates in the ST-22 CC showed the same one-nucleotide (nt) difference with both NCTC 11168 and 81-176 strains, resulting in a Thr→Ala substitution in the predicted protein sequence (represented by isolate FB7437, GenBank accession number ; Fig. HQ104931Fig.1).1). Eight other isolates in different CCs showed a 2-nt difference (isolate 1970, GenBank accession number ; Fig. HQ104932Fig.1)1) compared to strains NCTC 11168 and 81-176, although this did not result in amino acid substitutions. All 28 isolates were predicted to encode a full-length FspA1 protein.Open in a separate windowFIG. 1.Comparison of FspA1 and FspA2 isoforms. FspA1 is represented by 81-176, FB7437, and 1970. FspA2 is represented by C. jejuni strains 76763 to 1960 (GenBank accession numbers ). Scale bar represents amino acid divergence.In total, 62 isolates (representing 7 CCs and 35 STs) were subjected to fspA2 sequence analysis. Although a 100% sequence similarity between different STs was found for isolates in the ST-21, ST-45, ST-48, ST-61, and ST-206 CCs, fspA2 was generally more heterogeneous than fspA1 and we found 13 predicted FspA2 amino acid sequence variants in total (Fig. HQ104933 to HQ104946(Fig.1).1). In several isolates with uncommon and often unassigned (UA) STs, the proteins were truncated (Fig. (Fig.1),1), with most mutations being ST specific. For example, all ST-58 isolates showed a 13-bp deletion (isolate 3074_2; Fig. Fig.1),1), resulting in a premature stop codon. Also, all ST-1332 CC isolates were predicted to have a premature stop codon by the addition of a nucleotide between nt 112 and nt 113 (isolate 1960; Fig. Fig.1),1), a feature shared with two isolates typed as ST-4002 (UA). A T68A substitution in ST-1960 (isolate T-73494) also resulted in a premature stop codon. Interestingly, ST-1959 and ST-4003 (represented by isolate 4129) both lacked one triplet (nt 235 to 237), resulting in a shorter FspA2 protein. SignalP analysis showed the probability of a signal peptide between nt 22 and 23 (ACA-AA [between the underlined nucleotides]). An A24C substitution in two other strains, represented by isolate 76580, of ST-693 and ST-993 could possibly result in a truncated FspA2 protein as well.In conclusion, our results showed that FspA1 and FspA2 showed host and MLST associations. The immunogenic FspA1 seems to be conserved among C. jejuni strains, in contrast to the heterogeneous apoptosis-inducing FspA2, of which many isoforms were truncated. FspA proteins could serve as virulence factors for C. jejuni, although their roles herein are not clear at this time. 相似文献
TABLE 1.
Percent distributions of fspA1 and fspA2 variants among 669 human, poultry, and bovine Campylobacter jejuni strains and their associations with hosts, STs, and CCsHost or ST complex/ST (no. of isolates) | % of strains witha: | P valueb | |
---|---|---|---|
fspA1 | fspA2 | ||
Host | |||
All (669) | 64.3 | 35.4 | |
Human (367) | 69.5 | 30.0 | <0.001 |
Poultry (183) | 79.2 | 20.8 | <0.001 |
Bovine (119) | 25.2 | 74.8 | <0.0001 |
ST complex and STs | |||
ST-21 complex (151) | 2.6 | 97.4 | <0.0001 |
ST-50 (76) | NF | 100 | <0.0001 |
ST-53 (19) | NF | 100 | <0.0001 |
ST-451 (9) | NF | 100 | <0.0001 |
ST-883 (11) | NF | 100 | <0.0001 |
ST-22 complex (22) | 100 | NF | <0.0001 |
ST-22 (11) | 100 | NF | <0.01 |
ST-1947 (9) | 100 | NF | 0.03 |
ST-45 complex (268) | 99.3 | 0.7 | <0.0001 |
ST-11 (7) | 100 | NF | NA |
ST-45 (173) | 99.4 | 0.6 | <0.0001 |
ST-137 (22) | 95.5 | 4.5 | 0.001 |
ST-230 (14) | 100 | NF | <0.0001 |
ST-48 complex (18) | 44.4 | 55.6 | NA |
ST-48 (7) | 100 | NF | NA |
ST-475 (8) | NF | 100 | <0.001 |
ST-52 complex (5) | NF | 100 | <0.01 |
ST-52 (4) | NF | 100 | 0.02 |
ST-61 complex (21) | NF | 100 | <0.0001 |
ST-61 (11) | NF | 100 | <0.0001 |
ST-618 (3) | NF | 100 | 0.04 |
ST-206 complex (5) | NF | 100 | <0.01 |
ST-283 complex (24) | 100 | NF | <0.0001 |
ST-267 (23) | 100 | NF | <0.0001 |
ST-677 complex (59) | 100 | NF | <0.0001 |
ST-677 (48) | 100 | NF | <0.0001 |
ST-794 (11) | 100 | NF | <0.001 |
ST-692 complex (3) | NF | 100 | 0.04 |
ST-1034 complex (5) | NF | 80 | NA |
ST-4001 (3) | NF | 100 | 0.04 |
ST-1287 complex/ST-945 (8) | 100 | NF | NA |
ST-1332 complex/ST-1332 (4) | NF | 100 | 0.02 |
Unassigned STs | |||
ST-58 (6) | NF | 100 | <0.01 |
ST-586 (6) | 100 | NF | NA |
4.
Aurelio Cafaro Stefania Bellino Fausto Titti Maria Teresa Maggiorella Leonardo Sernicola Roger W. Wiseman David Venzon Julie A. Karl David O'Connor Paolo Monini Marjorie Robert-Guroff Barbara Ensoli 《Journal of virology》2010,84(17):8953-8958
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).
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
TABLE 1.
Summary of treatment, challenge dose, and outcome of infection in cynomolgus monkeysProtocol code | No. of monkeys | Immunogen (dose)a | Adjuvantb | Schedule of immunization (wk) | Routec | Challenged (MID50) | Virological outcomee | Reference(s) or source | ||
---|---|---|---|---|---|---|---|---|---|---|
A | C | V | ||||||||
ISS-ST | 6 | Tat (10) | Alum or RIBI | 0, 2, 6, 12, 15, 21, 28, 32, 36 | s.c., i.m. | 10 | 4 | 1 | 1 | 4, 17 |
ISS-ST | 1 | Tat (6) | None | 0, 5, 12, 17, 22, 27, 32, 38, 42, 48 | i.d. | 10 | 1 | 0 | 0 | 4, 17 |
ISS-PCV | 3 | pCV-tat (1 mg) | Bupivacaine + methylparaben | 0, 2, 6, 11, 15, 21, 28, 32, 36 | i.m. | 10 | 3 | 0 | 0 | 6 |
ISS-ID | 3 | Tat (6) | none | 0, 4, 8, 12, 16, 20, 24, 28, 39, 43, 60 | i.d. | 10 | 1 | 1 | 1 | B. Ensoli, unpublished data |
ISS-TR | 6 | Tat (10) | Alum-Iscom | 0, 2, 6, 11, 16, 21, 28, 32, 36 | s.c., i.d., i.m. | 10 | 4 | 2 | 0 | Ensoli, unpublished |
ISS-TGf | 3 | Tat (10) | Alum | 0, 4, 12, 22 | s.c. | 15 | 0 | 3 | Ensoli, unpublished | |
ISS-TG | 3 | Tatcys22 (10) | Alum | 15 | 0 | 3 | Ensoli, unpublished | |||
ISS-TG | 4 | Tatcys22 (10) + Gag (60) | Alum | 15 | 0 | 4 | Ensoli, unpublished | |||
ISS-TG | 4 | Tat (10) + Gag (60) | Alum | 15 | 0 | 4 | Ensoli, unpublished | |||
ISS-MP | 3 | Tat (10) | H1D-Alum | 0, 4, 12, 18, 21, 38 | s.c., i.m. | 15 | 0 | 2 | 1 | Ensoli, unpublished |
ISS-MP | 3 | Tat (10) | Alum | s.c. | 15 | 0 | 0 | 3 | Ensoli, unpublished | |
ISS-GS | 6 | Tat (10) | H1D-Alum | 0, 4, 12, 18, 21, 36 | s.c., i.m. | 15 | 1 | 3 | 2 | Ensoli, unpublished |
NCI-Ad-tat/Tat | 7 | Ad-tat (5 × 108 PFU), Tat (10) | Alum | 0, 12, 24, 36 | i.n., i.t., s.c. | 15 | 2 | 3 | 2 | Ensoli, unpublished |
NCI-Tat | 9 | Tat (6 and 10) | Alum/Iscom | 0, 2, 6, 11, 15, 21, 28, 32, 36 | s.c., i.d., i.m. | 15 | 2 | 4 | 3 | 12 |
ISS-NPT | 3 | pCV-tat (1 mg) | Bupivacaine + methylparaben-Iscom | 0, 2, 8, 13, 17, 22, 28, 46, 71 | i.m. | 20 | 0 | 0 | 3 | Ensoli, unpublished |
ISS-NPT | 3 | pCV-tatcys22 (1 mg) | Bupivacaine + methylparaben-Iscom | 0, 2, 8, 13, 17, 22, 28, 46, 71 | i.m. | 20 | 1 | 1 | 1 | |
Total vaccinated | 67 | 19 | 17 | 31 | ||||||
Naive | 11 | None | None | NAg | NA | 10 or 15 | 1 | 3 | 7 | |
Control | 34 | None, Ad, or pCV-0 | Alum, RIBI, H1D, Iscom or bupivacaine + methylparaben-Iscom | s.c., i.d., i.n., i.t., i.m. | 10, 15, or 20 | 5 | 13 | 16 | ||
Total controls | 45 | 6 | 16 | 23 | ||||||
Total | 112 | 25 | 33 | 54 |
5.
6.
7.
8.
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).
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 g−1 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 g−1 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 g−1, 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 ml−1) 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 ml−1. 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.
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 ml−1) and W4 (3.4 log10 copies 100 ml−1 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
TABLE 1.
Specificities of the CGOF1-Bac, CGOF2-Bac, and CG-Prev f5 PCR assays for different species present in Saskatchewan, CanadaHost group or sample type | No. of samples | No. positive for Bacteroidales marker: | |||
---|---|---|---|---|---|
CGOF1-Bac | CGOF2-Bac | CG-Prev f5 | All-Bac | ||
Individual human feces | 25 | 0 | 0 | 1 | 25 |
Raw human sewage | 6 | 0 | 0 | 0 | 6 |
Cows | 41 | 0 | 0 | 0 | 41 |
Pigs | 48 | 0 | 0 | 1 | 48 |
Chickens | 34 | 0 | 0 | 8 | 34 |
Geese | 101 | 58 | 51 | 59 | 95a |
Gulls | 16 | 0 | 0 | 6 | 14 |
Pigeons | 25 | 1 | 0 | 2 | 22 |
Ducks | 10 | 0 | 0 | 0 | 10 |
Swans | 1 | 0 | 0 | 0 | 1 |
Moose | 10 | 0 | 0 | 0 | 10 |
Deer | |||||
White tailed | 10 | 0 | 0 | 0 | 10 |
Mule | 10 | 0 | 0 | 0 | 10 |
Fallow | 10 | 0 | 0 | 0 | 10 |
Caribou | 10 | 0 | 0 | 0 | 10 |
Bison | 10 | 0 | 0 | 0 | 10 |
Goats | 10 | 0 | 0 | 0 | 10 |
Horses | 15 | 0 | 0 | 0 | 15 |
Total | 392 | 59 | 51 | 77 | 381 |
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 weeklyaSite | E. 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 analyzed | Min level-max level (log copies 100 ml−1) | Mean level (log copies 100 ml−1) | |
W1 | 8/8 (100) | 6-196 | 71.1 | 8/8 (100) | 6.2-8.1 | 6.9 | 6/8 (75) | 0-4.7 | 2.4 | 4/8 (50) | 0-4 | 1.7 | 2/8 | 0-3.7 | 1.7 |
W2 | 9/10 (90) | 0-1,120 | 194 | 10/10 (100) | 5.8-6.8 | 6.4 | 9/10 (90) | 0-3.7 | 2.6 | 8/10 (80) | 0-3.3 | 2.2 | 0/10 | 0 | 0 |
W3 | 10/10 (100) | 6-1,550 | 534 | 10/10 (100) | 6-7.8 | 7 | 10/10 (100) | 2.9-4.8 | 3.8 | 10/10 (100) | 2-4.5 | 3.4 | 0/10 | 0 | 0 |
W4 | 10/10 (100) | 16-1,732 | 529 | 10/10 (100) | 6.4-7.6 | 7 | 10/10 (100) | 3.2-4.6 | 3.9 | 10/10 (100) | 2.8-4.3 | 3.4 | 0/10 | 0 | 0 |
W5 | 10/10 (100) | 2-2,420 | 687 | 10/10 (100) | 5.5-6.9 | 6.3 | 7/10 (70) | 0-3.2 | 1.7 | 5/10 (50) | 0-3.1 | 1.2 | 0/10 | 0 | 0 |
W6 | 10/10 (100) | 3-1,990 | 389 | 10/10 (100) | 5.5-7 | 6.3 | 9/10 (90) | 0-4.3 | 2.8 | 6/10 (60) | 0-5.1 | 2 | 1/10 | 0-3.4 | 1.3 |
W7 | 7/7 (100) | 5-2,420 | 445 | 7/7 (100) | 5.7-7.8 | 7 | 6/7 (86) | 0-3.8 | 2.6 | 5/7 (71) | 0-4.4 | 2.4 | 2/7 | 0-5.1 | 2.8 |
W8 | 10/10 (100) | 17-980 | 160 | 10/10 (100) | 6.3-8.6 | 7.1 | 8/10 (80) | 0-4.6 | 2.8 | 7/10 (70) | 0-4.4 | 2.3 | 0/10 | 0 | 0 |
9.
Evolutionary Strata in a Small Mating-Type-Specific Region of the Smut Fungus Microbotryum violaceum
下载免费PDF全文
![点击此处可从《Genetics》网站下载免费的PDF全文](/ch/ext_images/free.gif)
DNA sequence analysis and genetic mapping of loci from mating-type-specific chromosomes of the smut fungus Microbotryum violaceum demonstrated that the nonrecombining mating-type-specific region in this species comprises ∼25% (∼1 Mb) of the chromosome length. Divergence between homologous mating-type-linked genes in this region varies between 0 and 8.6%, resembling the evolutionary strata of vertebrate and plant sex chromosomes.EVOLUTION of mating types or sex-determining systems often involves the suppression of recombination around the primary sex-determining or mating-type-determining locus. In animals and plants, it is often an entire or almost entire chromosome (Y or W in male or female heterogametic species, respectively) that ceases to recombine with its homologous (X or Z) chromosome (Charlesworth and Charlesworth 2000; Charlesworth 2008). Self-incompatibility loci in plants are also thought to be located in regions of suppressed recombination (Charlesworth et al. 2005; Kamau and Charlesworth 2005; Kamau et al. 2007; Li et al. 2007; Yang et al. 2007). Regardless of the phylogenetic position of a species, such nonrecombining regions are known to follow similar evolutionary trajectories. The nonrecombining region on the sex-specific chromosome expands in several steps, forming evolutionary strata—regions of different X/Y (or Z/W) divergence (Lahn and Page 1999; Handley et al. 2004; Sandstedt and Tucker 2004; Nicolas et al. 2005)—and genes in the nonrecombining regions gradually accumulate deleterious mutations that eventually render them dysfunctional (Charlesworth and Charlesworth 2005; Charlesworth 2008).Fungal mating-type systems are very diverse, with the number of mating types varying from two to several hundred (Casselton 2002). Like sex chromosomes in several animals and plants, suppressed recombination has evolved in regions near fungal mating-type loci, including in Ustilago hordei (Lee et al. 1999), Cryptococcus neoformans (Lengeler et al. 2002), and Neurospora tetrasperma (Menkis et al. 2008). These species have two mating types, but no morphologically distinct sexes. The mating-type locus (the region of suppressed recombination) of C. neoformans is small (∼100 kb) compared with known sex chromosomes and contains only ∼20 genes that, unlike many sex chromosomes (Y or W chromosomes), show no obvious signs of genetic degeneration (Lengeler et al. 2002; Fraser et al. 2004). Judging from the divergence between the homologous genes on the two mating-type-specific chromosomes, C. neoformans started to evolve sex chromosomes a long time ago because silent divergence between the two mating types in the most ancient region exceeds 100% (Fraser et al. 2004). Genes in the younger mating-type-specific region are much less diverged between the two sex chromosomes, suggesting that the evolution of the sex locus in C. neoformans might have proceeded through several steps. The nonrecombining region around the mating-type locus of N. tetrasperma is much larger than in C. neoformans (at least 6.6 Mb), and silent divergence between homologous genes on the mating-type-specific chromosomes ranges from zero to 9%, demonstrating that these mating-type-specific chromosomes evolved recently (Menkis et al. 2008).M. violaceum, which causes anther smut disease in Silene latifolia and other species in the family Caryophyllaceae, has two mating types, A1 and A2 (reviewed by Giraud et al. 2008), which are determined by the presence of mating-type-specific chromosomes (hereafter A1 and A2 chromosomes, or sex chromosomes) in the haploid stage of the life cycle (Hood 2002; Hood et al. 2004). The A1 and A2 chromosomes are distinguishable by size in pulsed-field electrophoresis, and it is possible to isolate individual chromosomes electrophoretically (Hood et al. 2004). Random fragments of A1 and A2 chromosomes have previously been isolated from mating-type-specific bands of pulsed-field separated chromosomes of M. violaceum (Hood et al. 2004). These fragments were assumed to be linked to mating type. The same method was used to isolate fragments of non-mating-type-specific chromosomes. On the basis of the analysis of their sequences, (Hood et al. 2004) proposed that mating-type-specific chromosomes in M. violaceum might be degenerate because they contained a lower proportion of protein-coding genes than other chromosomes. However, it was not determined whether the sequences isolated from the mating-type chromosomes originated from the mating-type-specific or from the recombining regions (Hood et al. 2004), and the relative sizes of these regions are not known for these M. violaceum chromosomes. We tested the mating-type specificity of 86 of these fragments and demonstrate that fewer than a quarter of these loci are located in the mating-type-specific region, suggesting that the nonrecombining region on the A1 and A2 chromosomes is quite small, while the rest of the chromosome probably recombines (like pseudoautosomal regions of sex chromosomes) and is therefore not expected to undergo genetic degeneration. Genetic mapping confirms the presence of two pseudoautosomal regions in the M. violaceum mating-type-specific chromosomes.As these chromosomes are mating type specific in the haploid stage of M. violaceum, mating-type-specific loci (or DNA fragments) can be identified by testing whether they are present exclusively in A1 or A2 haploid strains. We therefore prepared haploid A1 and A2 M. violaceum cultures from S. latifolia plants from two geographically remote locations (accessions Sl405 from Sweden and Sl127 from the French Pyrenees). Haploid sporidial cultures were isolated by a standard dilution method (Kaltz and Shykoff 1997; Oudemans and Alexander 1998). Mating types were determined by PCR amplification of each culture with primers designed for A1 and A2 pheromone receptor genes linked to A1 and A2 mating types (Yockteng et al. 2007). The primers were as follows: 5′-TGGCATCCCTCAATGTTTCC-3′ and 5′-CACCTTTTGATGAGAGGCCG-3′ for the A1 pheromone receptor (GenBank accession no. ) and 5′-TGACGAGAGCATTCCTACCG-3′ and 5′-GAAGCGGAACTTGCCTTTCT-3′ for the A2 pheromone receptor (GenBank accession no. EF584742). Cultures with PCR product amplified only from an A1 or A2 pheromone receptor gene were selected for further use. The mating types of the cultures were verified by conjugating them in all combinations.The GenBank nucleotide database was searched using BLAST for sequences similar to those isolated by EF584741Hood et al. (2004). Sequences with similarity to transposable elements (TE) and other repeats were excluded. The resulting set of nonredundant sequences was used to design PCR primers for 98 fragments. Half of these were originally isolated from the A1 and half from the A2 chromosomes and are hereafter called A1-NNN or A2-NNN (where NNN is the locus number; supporting information, Table S1), which does not imply that these loci are A1 or A2 specific, but merely indicates that they were originally isolated from the A1 or A2 chromosomes. Amplification of these regions from new A1 and A2 M. violaceum cultures, independently isolated by ourselves, revealed that only 5 of the 49 loci isolated from the A1 chromosome are indeed A1 specific and only 6 of 49 isolated from the A2 chromosome are A2 specific. All other loci amplified from both A1 and A2 cultures. Figure 1 illustrates some of these results from the Swedish sample (Sl405).Open in a separate windowFigure 1.—Testing of mating-type specificity for loci isolated from A1 and A2 chromosomes. (a) PCR amplifications from haploid cultures from Sl405 using primers designed from six A1-originated loci. Loci in which a PCR product could be amplified only from A1 cultures (boxed) were classified as specific to mating type A1. (b) PCR tests of six A2-originated loci on the same set of haploids as in a. Loci in which a PCR product amplified only from A2 cultures (boxed) were classified as specific to mating type A2. Loci amplified from both A1 and A2 cultures are not mating type specific.The fragments that amplified from both A1 and A2 mating types may be in recombining regions, or they could be present in mating-type-specific regions on both A1 and A2 chromosomes. If they are in recombining regions, the A1- and A2-linked homologs should not be diverged from each other, but if they are in nonrecombining, mating-type-specific regions, the divergence of the A1- and A2-linked homologs should be roughly proportional to the time since recombination stopped in the region. We therefore sequenced and compared PCR fragments amplified from the two mating types of Sl405 or Sl127 cultures (GenBank accession nos. – FI855822). Sequencing of PCR products showed that 12 (4 A1 and 8 A2) loci have more than one copy, and they were excluded from further analysis. Sequences of 61 loci were identical between the A1 and A2 strains, and four loci demonstrated low total divergence (0.24–0.61%) between the two mating types ( FI856001otintseva and D. Filatov, unpublished results). Thus, these loci might be located in the recombining part of the mating-type-specific chromosomes. Ten of 75 loci that amplified in both mating types demonstrated multiple polymorphisms fixed between the mating types rather than between the locations. Given that the strains that we used in the analysis originated from two geographically distant locations, it is highly unlikely that multiple polymorphisms distinguishing the A1 and A2 sequences arose purely by chance; thus, these loci are probably located in the nonrecombining mating-type-specific region of the M. violaceum A1 and A2 chromosomes.
Open in a separate windowaA1, loci originated from the A1 sex chromosome; A2, loci originated from the A2 sex chromosome.bThe number of loci used for genetic map construction is in parentheses.To confirm the mating-type-specific or pseudoautosomal locations of the loci with and without A1/A2 divergence, we conducted genetic mapping in a family of 99 individuals, 50 of which were of mating type A1 and 49 of mating type A2. The family was generated by a cross between A1 and A2 M. violaceum strains from S. latifolia accessions Sl405 (Sweden) and Sl127 (France), respectively. The choice of strains from geographically distant locations was motivated by the hope of maximizing the number of DNA sequence differences between them that can be used as molecular genetic markers in segregation analysis. We inoculated S. latifolia seedlings with sporidial cultures of both mating types. For inoculation, petri dishes with 12-day-old seedlings of S. latifolia were flooded with 2.5 ml of inoculum suspension. Inoculum suspension consisted of equal volumes of the A1 and A2 sporidial cultures that were mixed and conjugated overnight at 14° under rotation (Biere and Honders 1996; Van Putten et al. 2003). Seedlings were potted 3 days after inoculation. Two months later, teliospores were collected from the flowers of the infected plant and grown in petri dishes on 3.6% potato dextrose agar medium. Haploid sporidia formed after meiosis were isolated and grown as separate cultures for DNA extraction. The mating types of single sporidia cultures were identified as described above. The loci analyzed in the segregation analysis were sequenced in the two parental haploid strains and in 99 (50 A1 and 49 A2) haploid strains that were generated in the cross. Single nucleotide differences between the parental strains were used as molecular genetic markers for segregation analysis in the progeny. The genetic map was constructed using MAPMAKER/EXP v3.0 (Lincoln et al. 1992) and MapDisto v1.7 (http://mapdisto.free.fr/).The resulting genetic map is shown in Figure 2. As expected, no recombination was observed between the 10 loci with diverged A1- and A2-linked copies. In addition, one marker with no A1/A2 divergence, A2-397, was also completely linked to the loci with significant A1/A2 divergence. This locus either may be very tightly linked to the nonrecombining mating-type-specific region or may have been added to that region more recently than the loci that had already accumulated some divergence between the alleles in the two mating types. The mating-type-specific pheromone receptor locus (Devier et al. 2009) and 11 mating-type-specific loci are also located in this nonrecombining region (Figure 2). Interestingly, the cluster of nonrecombining markers is flanked on both sides with markers that recombine in meiosis, demonstrating that there are pseudoautosomal regions on both ends of the mating-type-specific chromosomes.Open in a separate windowFigure 2.—Genetic map of the mating-type-determining chromosome in M. violaceum. Genetic distance (in centimorgans) and the relative positions of the markers are shown to the left and the right of the chromosome, respectively. The position of the nonrecombining region corresponds to the cluster of linked markers shown on the right of the figure. Total A1/A2 divergence is shown in parentheses. Eleven mating-type-specific markers (for which sequences are available from only one mating type), located in the nonrecombining mating-type-specific region, are not shown.Our results demonstrate that although the loci reported by Hood et al. (2004) were isolated from the A1 and A2 chromosomes, most of these loci are not located in the nonrecombining mating-type-specific regions. In fact, the nonrecombining region might be relatively small: of 86 tested fragments, only 21 appeared to be either mating type specific or linked to the mating-type locus. Assuming that these loci represent a random set of DNA fragments isolated from the A1 and A2 chromosomes, it is possible to estimate the size of the nonrecombining region using the binomial distribution: the nonrecombining region is expected to be 24.4% (95% CI: 16.7–33.6%) of the chromosome length. As the sizes of the A1 and A2 chromosomes are ∼3.4 and 4.2 Mb long (Hood 2002; Hood et al. 2004), the nonrecombining region might be ∼1 Mb long.Interestingly, total A1/A2 divergence for the 11 loci with A1- and A2-linked copies mapped to the nonrecombining region varied from 0% to 8.6% (Figure 2). In addition, 11 loci amplified from only one mating type. These genes could represent degenerated genes, some of which degenerated in A1 strains, and some in A2 strains. Alternatively, they might be highly diverged genes, such that the PCR primers amplify only one allele, and not the other. Variation in divergence may be the result of the stepwise cessation of recombination between the A1 and A2 chromosomes in M. violaceum, resembling the evolutionary strata reported for human, chicken, and white campion sex chromosomes (Lahn and Page 1999; Handley et al. 2004; Bergero et al. 2007). However, only the differences between the most and the least diverged loci are statistically significant (Devier et al. 2009), the M. violaceum mating-type region has at least three strata: one oldest stratum, including the pheromone receptor locus; a younger stratum with ∼5–9% A1/A2 divergence; and the youngest stratum with 1–4% divergence between the two mating types. There may also be an additional very recently evolved stratum containing the locus named A2-397, which is also present in all A1 strains tested, with no fixed differences between the A1 and A2 strains (No. of sites analyzed Within A1
Within A2
Fixed differences between A1 and A2 A1/A2 divergence (%) Locia Sb total S π (%)c S π (%)c A1/A2 divergence <1% A1-236 456 3 0 0 2 0.44 1 0.44 A1-045 654 4 0 0 0 0 4 0.61 A2-568 413 2 2 0.48 2 0.48 0 0.24 A2-411 480 2 1 0.21 0 0 1 0.31 A1/A2 divergence >1% A1-217 667 9 0 0 0 0 9 1.35 A1-128 569 9 0 0 1 0.18 8 1.49 A1-199 618 13 0 0 1 0.16 12 2.02 A2-422 344 9 0 0 0 0 9 2.62 A2-516 470 14 0 0 0 0 14 2.98 A2-404 508 20 0 0 3 0.59 17 3.64 A2-435 506 22 2 0.39 2 0.39 18 3.95 A2-473 457 23 1 0.22 1 0.22 21 4.81 A2-457 303 17 1 0.33 0 0 16 5.54 A2-575 503 47 5 0.99 3 0.59 39 8.55
TABLE 1
Loci from mating-type-specific chromosomes of M. violaceum used for PCR analysis and genetic map constructionWith nonzero A1/A2 divergenceb
| |||||
---|---|---|---|---|---|
Loci | Mating type specific | <1% | >1% | With zero A1/A2 divergenceb | Total |
A1a | 5 | 2 (1) | 3 (3) | 35 (3) | 45 (7) |
A2a | 6 | 2 (0) | 7 (7) | 26 (3) | 41 (10) |
Subtotal | 4 (1) | 10 (10) | |||
Total | 11 | 14 (11) | 61 (6) | 86 (17) |