*Wellcome Trust Centre for the Epidemiology of Infectious Disease, Department of Zoology, University of Oxford, Oxford, England;
Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, Texas;
Max-Planck-Institut fuer Chemische Oekologie, Jena, Germany;
§Center for Agricultural Biotechnology and Department of Entomology, University of Maryland College Park;
||National Malaria Program, Ministry of Health, La Paz, Bolivia;
¶Papua New Guinea Institute for Medical Research, Madang, Papua New Guinea;
**HIV Research Program, Henry M. Jackson Foundation, Rockville, Maryland;
Liverpool School of Tropical Medicine, Liverpool, England;
Medical Research Council Research Programme on AIDS in Uganda Uganda Virus Research Institute, Entebbe, Uganda;
§§Programa de Estudio y Control de Enfermedades Tropicales, Universidad de Antioquia, Medellin, Colombia;
||||Shoklo Malaria Research Unit, Mae Sot Tak, Thailand;
¶¶Departamento de Parasitologia, Instituto de Ciências Biomédicas, Universidade de São Paulo, São Paulo, Brazil
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Abstract |
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Introduction |
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Plasmodium falciparum is a hermaphroditic protozoan, with haploid asexual replication in the human host and a brief diploid sexual phase in the mosquito vector. Haploid parasites divide mitotically in the human host, and some cells differentiate into male and female stages. Male and female gametes fuse in the mosquito host to form a short-lived diploid zygote. Meiotic division then gives rise to haploid cells that develop into infective sporozoites, which migrate to the mosquito salivary glands and infect humans during mosquito blood-feeding. Fusion of male and female gametes from the same clone (selfing) results in no effective recombination, while fusion of gametes from different clones (outcrossing) may result in recombination. While Plasmodium has a well-established sexual phase in its life cycle and genetic crosses have been performed (Walker-Jonah et al. 1992
; Su et al. 1999
), there is ongoing discussion about the level of effective recombination in natural malaria populations (Rich et al. 1998
; Conway et al. 1999
). Rich et al. (1998)
used substitution patterns in the circumsporozoite antigen to argue that P. falciparum populations are predominantly clonal (Rich, Hudson, and Ayala 1997
). This conclusion was based on the absence of any decay in linkage disequilibrium (LD) with distance across the locus studied. This claim was clearly refuted by Conway et al. (1999)
, who showed a rapid decay in LD with physical distance along a chromosome and argued for high levels of recombination, at least in African locations. However, the situation is by no means clear: while some authors have observed no evidence for LD between physically unlinked antigen loci (Babiker et al. 1994
; Paul et al. 1995
), others have reported strong LD (Abderrazak et al. 1999
). Other aspects of population structure are also debated. Data on levels of geographical genetic differentiation among parasite populations are conflicting, with two antigen loci (MSP-1 and MSP-2) indicating low levels of global genetic structure (FST < 0.2) (Conway 1997
) and a third locus, the gametocyte surface antigen pfs48/45, suggesting strong subdivision (FST > 0.7) (Drakeley et al. 1996
). Once again, interpretation of these data is hampered by the use of small numbers of strongly selected loci.
To clarify our understanding of P. falciparum population genetics, we employed microsatellite genotyping. Recently, microsatellite markers have been shown to be extremely widespread in P. falciparum, occurring every 23 kb throughout the genome (Su and Wellems 1996
; Su et al. 1999
). We adapted 12 loci bearing trinucleotide repeats for use with the minimal amounts of template present in P. falciparuminfected blood samples (Anderson et al. 1999
) and used these loci to measure allelic variation in 465 P. falciparuminfected blood samples collected from nine different locations worldwide. The samples were collected from regions with high levels of transmission in Africa and Papua New Guinea, and also from areas with low levels of transmission in Thailand and in three countries in South America. For all samples, we constructed infection "haplotypes" using the predominant allele present in the PCR products from each locus, while we also documented the frequency of infections containing multiple clones. These data clearly reveal a spectrum of population structures in a single parasite species. Strong LD, low diversity, and extensive population differentiation are seen in regions with low levels of transmission, while linkage equilibrium, high diversity, and low levels of differentiation are observed in regions with high levels of transmission.
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Materials And Methods |
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In Uganda, P. falciparuminfected blood samples were collected (April 1996June 1997) from HIV-infected individuals living in a 15-km radius of a clinic near Entebbe. This area is hyperendemic for malaria, with 10% of adults being blood-slide-positive (one or more parasites observed in fields containing 200 white blood cells). In the Democratic Republic of Congo, blood samples were obtained from asymptomatic pregnant women visiting a clinic in Kimpese in 1993. This area is holoendemic for malaria: 70% of women in their first pregnancy were slide-positive for P. falciparum, while 13% of multigravidae were slide-positive (Jackson et al. 1991
). In Zimbabwe, blood samples were collected in April and May 1998 from symptomatic patients visiting health clinics in the Mutare and Mutasa districts near the border with Mozambique. In this region, transmission is seasonal with a prevalence of 2%4.6%. In Papua New Guinea, blood samples were collected during cross-sectional surveys in Mebat, Madang Province (November 17 and December 16, 1997) and in Buksak, 80 km away (September 22 and December 8, 1997). In Mebat 38% of samples were slide-positive, while in Buksak, 51% were positive. In Thailand, samples were collected between December 15, 1997, and January 11, 1998, from symptomatic patients in Shoklo, Tak Province. A survey in January 1998 showed a prevalence of 0.6%. In Colombia, samples were collected from symptomatic individuals visiting the clinic in El Bagre (Province of Antioquia). In Bolivia, blood samples were collected from symptomatic individuals during an outbreak in MayJune 1994 in Guayaramerín (Department of Beni). In Brazil, 22 infected blood samples were obtained from symptomatic individuals visiting the clinic in Porto Velho, Rondônia, in JulySeptember 1998, while a further 10 samples were obtained in July 1997. The sites in Bolivia and Brazil are approximately 350 km apart. For South American locations, we used Pan American Health Organization incidence data for P. falciparum to estimate cross-sectional prevalence. This was done by dividing the yearly number of reported cases by the population size and dividing the resulting figure by 12 (duration of infection was estimated at 1 month). For Porto Velho, Brazil, in 1997, 4,426 cases were observed in a population of 294,327, giving an estimated prevalence of 0.125%. In Guayanamerín, Bolivia, in 1997, 1,644 cases were observed in a population of 44,950, giving an estimated prevalence of 0.305%. In El Bagre, Colombia, in 1998, 3,391 cases were observed in a population of 50,204, giving an estimated prevalence of 0.563%.
Scoring of Microsatellite Length Variation
In eight locations, parasite DNA was prepared from finger-prick blood samples (50 µl) absorbed onto Whatman filter paper using a chelex extraction protocol (Wooden, Kyes, and Sibley 1993
), and re-eluted in 100 µl TE. Brazilian DNA samples were prepared from 200 µl of whole blood. Levels of parasite infection vary by two or three orders of magnitude between infected individuals and are frequently very low. As a result, levels of parasite DNA template available for PCR are also variable and may be as low as 1 pg. We used a two-round hemi-nested PCR strategy to amplify microsatellite loci from P. falciparum, and fluorescently labeled PCR products were sized on polyacrylamide gels by comparison with internal size standards. For samples from Buksak (PNG), primers were end- labeled with
-P32, and products were sized by reference to M13 sequence ladders. Primers, PCR conditions, primer specificity, and reproducibility of the techniques used have previously been described (Anderson et al. 1999
). The 12 loci used are distributed throughout the P. falciparum genome. The loci are Poly
(Chr4), TA42 (Chr5), TA81 (Chr5), TA1 (Chr6), TA109 (Chr6), TA87 (6), TA40 (Chr10), 2490 (Chr10), ARAII (Chr11), pfG377 (Chr12), PfPk2 (12), and TA60 (Chr13). Four loci (Poly
, ARAII, pfG377, and PfPk2) are in coding sequences from GenBank. The other eight loci were drawn from a genomic library (Su and Wellems 1996
), and their function is unknown. We used GENESCAN and GENOTYPER software (Applied Biosystems) to automate measurement of allele length and to quantify peak heights. We discarded data from samples that amplified poorly for particular loci (maximum peak height < 200 fluorescent units).
Measurement of Diversity, Effective Population Size, and Geographical Structure
We measured allele frequencies using only the predominant allele present at each locus within each infection. The predominant allele at each locus was defined as the highest peak in electropherogram traces. This procedure results in unbiased estimation of allele frequencies within a population, if we assume the composition of PCR products is representative of the composition of templates. We measured expected heterozygosity (H) at each locus in each location as H = [n/(n - 1)][1 - ni=1 p2i], where n is the number of infections sampled and pi is the frequency of the ith allele. We also measured the variance in allele size (VSZ) and counted the number of alleles (A) at each locus in the nine populations. We compared levels of diversity in different populations using ANOVA or nonparametric tests.
We estimated effective population size using observed H and mutation rate estimates. We used a microsatellite mutation rate (µ) for P. falciparum of 1.59 x 10-4 (95% confidence interval: 6.98 x 10-5, 3.7 x 10-4). This was estimated from the observation of five unique nonparental alleles in 35 progeny of a genetic cross that were genotyped for 901 microsatellite loci (Su et al. 1999
). Confidence intervals were estimated from chi-square tables using standard methods for distribution of Poisson-distributed variables (Johnson, Kotz, and Kemp 1992
). Since 5 of the 12 loci (Poly
, TA42, TA1, TA109, and TA40) used in the present study show patterns of variation which are inconsistent with a pure stepwise mutation model (Anderson et al. 2000b
), we used estimates based on both the infinite-alleles model (IAM) and the stepwise mutation model (SMM). For IAM, we used the relationship Neµ = H/4(1 - H), while for SMM we used the relationship Neµ =
{[1/(1 - H)]2 - 1} (Schug, Mackay, and Aquadro 1997
).
We measured population subdivision using Weir and Cockerham's (1984)
unbiased estimator of Wright's F statistics, while confidence intervals were estimated by bootstrapping over loci 104 times using the program GDA (Lewis and Zaykin 2000
). We examined correlations between pairwise values of genetic divergence (
) and geographical distance between locations using the Mantel test. The significance of the observed correlation was estimated by permuting the order of taxa in the data matrices 105 times and computing the frequency with which the correlation observed between the permuted data sets was greater than or equal to that observed between the original data sets. We measured Nei's (1978)
genetic distance between parasite populations while we examined the genetic relationships among individual parasite haplotypes by counting the proportion of alleles shared between 12-locus haplotypes (Ps) and using the measure (1 - Ps) as a simple distance measure (Bowcock et al. 1994
). All trees were constructed using PHYLIP (Felsenstein 1993
).
Assessment of Multiple Infections
Blood samples are frequently infected with two or more haploid clones of P. falciparum, resulting in the detection of two or more alleles at polymorphic loci. This may result from superinfection and therefore provides a surrogate indicator of the level of transmission within populations, as well the opportunity for recombination between unlike malaria clones (Hill and Babiker 1995
). We scored multiple alleles per locus if minor peaks were >33% the height of the predominant allele present for each locus. Multiple infections were defined as those in which at least one of the 12 loci contained more than one allele. This method has the advantage of being very simple. However, when populations differ in levels of heterozygosity, this method may be biased, since multiple infections are easy to detect in populations with high levels of heterozygosity and more difficult to detect in populations with low heterozygosity. We therefore also used a maximum-likelihood procedure (Hill and Babiker 1995
) to estimate the mean number of multiple infections using data from each of the 12 loci. For this analysis, we assumed a positive Poisson distribution of parasite clones among hosts (Hill and Babiker 1995
).
Multilocus Linkage Disequilibrium
We used the predominant allele detected at each locus to construct "infection haplotypes." Where blood samples contain a single parasite clone this, results in recovery of true parasite haplotypes. Where two or more clones are present, the infection haplotypes may be a composite of alleles from two or more clones. This may impose additional recombination on the data and bias the data against detection of LD. We conducted analyses of both the complete data set and a curtailed data set in which multiple infections (see above) were removed. We used a permutation procedure to test the null hypothesis of random association among loci for each parasite population (Souza et al. 1992
; Haubold et al. 1998
). The program LIAN, version 3 (Haubold and Hudson 2000
), was used to compute the number of alleles shared (D) between all pairwise comparisons of complete 12-locus haplotypes and to measure the variance of this distance measure (VD). To investigate if the observed data differed from random expectations, we compared the observed VD with the distribution of VD values in 10,000 simulated data sets in which alleles at each locus were randomly reshuffled among genotypes. Significant LD was detected if the observed VD was >95% of the values generated in the reshuffled data sets. We used the index of association (IA) to measure the strength of LD. The "classical" IA was defined as IA = (VD/Ve - 1), where Ve is the mean variance of the reshuffled data sets (Maynard-Smith et al. 1993
). However, since this statistic scales with r - 1, where r is the number of loci analyzed (Hudson 1994
), we used a "standardized" IA statistic (ISA), calculated as ISA = (VD/Ve - 1)/(r - 1).
Inferring Population History
We used Goldstein's (µ)2 (Goldstein et al. 1995
) distance, which is related linearly to time, to estimate divergence times between parasite populations. For this purpose, the five "complex" loci (Anderson et al. 2000b
) that show deviations from SMM were excluded (see above). The divergence time between populations was estimated using the relationship (
µ)2 = 2µt, where µ is the mutation rate and t is the number of generations elapsed since divergence (Goldstein et al. 1995
). The mutation rate estimation used in this calculation is described above.
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Results |
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Genetic Diversity
Levels of genetic diversity showed dramatic heterogeneity among locations (table 1
). All three measures of diversity showed the highest diversity in African locations, intermediate levels of diversity in samples from Papua New Guinea and Thailand, and the lowest diversity at the three South American sites. Up to 18 alleles per locus were found within African locations (in Poly in Zimbabwe and Uganda), while a maximum of five alleles per locus were observed within South American locations (also in Poly
). Similarly, H ranged from 0.8 in Zimbabwe and Congo to a minimum of 0.3 in Colombia. Variance in allele size was also greater in African locations, and the heterogeneity among populations was highly significant.
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Discussion |
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Linkage Disequilibrium
Significant deviations from random association among loci were observed in six of nine parasite populations using both the complete data set and the reduced data set from which multiple infections were removed. Maynard-Smith et al. (1993)
have described a simple framework for evaluating the population structure of microbial pathogens. They distinguish between "clonal" organisms, such as Salmonella and E. coli, in which levels of recombination are insufficient to break down clonal lineages, and "epidemic" population structures of organisms such as Neisseria meningitidis, in which LD results from temporal expansion of particular clones in an otherwise sexual population. Epidemic population structures can be identified by treating multiply represented genotypes as single individuals and remeasuring LD. This procedure restores linkage equilibrium to four of the six malaria populations investigated; LD remained in populations from Zimbabwe and Bolivia. Hence, the P. falciparum populations studied here range from epidemic in low-transmission areas to panmixia in high-transmission areas.
In Bolivia, LD remains even when only unique genotypes are included in the data set. Two explanations are conceivable. The rate of recombination may be sufficiently low relative to mutation, such that LD is maintained. Alternatively, the populations may result from admixture with a genetically divergent parasite population, and insufficient time has passed for recombination to homogenize these two populations. We note that parasite populations in South America show strong differentiation over relatively small geographical distances, so admixture of populations may occur frequently. LD also remains in Zimbabwe, even when unique genotypes are analyzed. This is surprising, given that we observe very high levels of multiclone infection in this region, suggesting relatively high levels of transmission. The Zimbabwe sample was collected from people visiting two different clinics in Mutare and Mutasa. These samples showed no significant genetic differentiation and were therefore analyzed together. Moreover, significant LD was observed in both populations, even when only unique haplotypes were analyzed (Mutare: n = 32, ISA = 0.0167, P = 0.0058; Mutasa: n = 24, ISA = 0.0158, P = 0.0461), suggesting that combining different populations did not generate the observed LD.
The simplest explanation for the observed association between transmission intensity and LD is that P. falciparum utilizes a mixed mating system in which inbreeding predominates in low-transmission areas, while higher levels of outbreeding occur in regions with higher transmission. This may occur, since people are rarely superinfected with more than one parasite clone in low-transmission regions. As a result, unrelated parasites rarely co-occur in the same mosquito blood meal. Conversely, multiple-clone infections are frequent where transmission is intense. Consequently, mosquitoes frequently ingest unrelated parasites, leading to higher levels of outbreeding (Babiker et al. 1994
; Paul et al. 1995
). To further investigate the relationship between LD and transmission, we compared two indicators of transmission intensity (prevalence and proportion of infections containing multiple clones) with ISA, which measures the strength of LD (fig. 5
). In general, parasites from regions with low prevalence or low levels of multiple infection show higher levels of ISA than those from regions with high prevalence or with high levels of multiple infections. This relationship should be viewed with some caution. Hudson (1994)
has shown that ISA is not directly comparable between populations when Ne varies. A theoretical framework to allow interpretation of microsatellite-derived ISA values in terms of levels of recombination would be extremely useful. Such a model does exist for markers evolving by IAM (Hudson 1994
). However, for most microsatellite data, this mutation model is likely to be inappropriate.
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Levels of LD may have important consequences for a number of aspects of P. falciparum biology. In particular, the rate at which recombination breaks down association between genes may influence the persistence of clonal genotypes (Paul et al. 1995
; Hastings and Wedgewood-Oppenheim 1997
), the maintenance of antigenically distinct "strains" (Gupta et al. 1996
; Hastings and Wedgewood-Oppenheim 1997
), sex ratio (Read et al. 1992
; Dye and Godfray 1993
), and the spread of drug resistance (Dye and Williams 1997
; Hastings 1997
; Hastings and Mackinnon 1998
). The extensive LD observed has important practical consequences for malaria research, a major goal of which is to locate parasite genes underlying important phenotypes such as pathogenicity and resistance to drugs. Two resourcesthe sequence data emerging from the malaria genome project (Gardner et al. 1998
) and a dense microsatellite map, with markers every 3050 kb (Su and Wellems 1996
; Su et al. 1999
)should simplify the location of important genes in P. falciparum. However, the high recombination rate (1 cM = 1530 kb) observed in a genetic cross (Walker-Jonah et al. 1992
) and the recent demonstration that LD is rarely detected between markers separated by >1 kb in African populations (Conway et al. 1999
) may discourage researchers from using LD in natural populations as a mapping tool. In populations with high levels of inbreeding, the "effective" recombination rate will be considerably reduced. In such populations, it should be possible to locate genes encoding important parasite traits using relatively low densities of marker loci (Noorberg 2000
). This approach is likely to be particularly effective for genes involved in drug resistance, since the mutations involved have occurred recently (White 1992
), allowing little time for LD between marker and trait loci to have been broken down (fig. 6 ). For example, with 1% recombination, LD may be maintained between markers spaced 5 cM apart for 2,750 generations, which is equivalent to >400 years if we assume a 2-month generation time for P. falciparum. Thus, for recently evolved traits (<50 years ago) genome screens using 200400 markers spaced at 75150-kb intervals are likely to be successful. In comparison, in regions with 50% outcrossing, all traces of LD between loci will be lost in <60 generations (
10 years), and marker densities one or two orders of magnitude higher would be necessary. Empirical data provide encouraging support for this mapping approach: LD is observed for >60 kb on either side of the putative chloroquine resistance locus (Su et al. 1997
).
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The differences in diversity may result from differences in effective population size and levels of inbreeding in low- and high-transmission regions. The intraspecific patterns of diversity, genetic differentiation, and LD observed in P. falciparum show a striking similarity to interspecific patterns of variation observed in plants (Schoen and Brown 1991
; Awadalla and Ritland 1997
) and animals (Jarne 1995
) with differing levels of inbreeding. Outbred species typically show higher levels of genetic variation and lower levels of genetic differentiation than inbred species. The interplay between mating system, diversity, and differentiation is complex. Three factors are likely to result in the reduced levels of genetic variation observed in inbred populations of P. falciparum. First, Ne is halved in situations of complete inbreeding relative to complete outbreeding (Pollak 1987
). This alone cannot account for the variation in diversity observed in P. falciparum, since Ne is reduced 923-fold in South American populations relative to African populations (table 2 ). Second, LD generated by selfing will increase the size of genomic regions involved in selective events, since "hitchhiking" either with deleterious sites (background selection) (Charlesworth, Morgan, and Charlesworth 1993
) or with sites under positive selection (selective sweeps) (Hedrick 1980
) will remove variation in the vicinity of the sites under selection. The size of genomic regions affected will be greatest in geographical regions in which strong LD is observed. Third, the effect of LD and inbreeding on diversity are likely to be compounded by the fact that both numbers of infected hosts and numbers of clones per individual are generally higher in areas of high transmission than in areas of low transmission. The reduced effective size of parasite populations in low-transmission areas may also explain the increased levels of genetic differentiation in regions such as South America, since allele frequencies may change rapidly in small populations owing to increased levels of genetic drift. If this explanation is correct, then we might expect to see similar numbers of alleles in both South America and Africa if sufficient populations are sampled. The fact that variation is distributed among populations in South America, while variation is distributed within populations in African locations, may give an illusion of reduced variation in parasites from the New World when the number of populations sampled is limited.
There is some supporting evidence for explanations involving disease ecology from two recent studies in which malaria parasites from isolated epidemics were genotyped for antigen-encoding loci. Arez et al. (1999) observed no genetic variation at loci in a malaria epidemic on Cabo Verde, while Laserson et al. (1999) observed no genetic variation at two antigen loci in an epidemic among Yanomani Indians in the Venezuelan Amazon. These papers suggest the importance of recent founder events associated with epidemic malaria in generating low-diversity parasite populations. Patterns of allelic distribution also provide some support for this explanation. In South American locations, the distribution of allele frequencies is flat, while in African countries the distributions are L-shaped (fig. 7
). Furthermore, in two locations, Bolivia and Brazil, the modal allele frequency range is in one of the intermediate allele frequency classes (40%50% for Bolivia and 10%20% for Colombia). Such "mode shifts," indicating a loss of rare alleles, are commonly observed in recently bottlenecked populations and appear to be indicative of populations that are not at mutation drift equilibrium (Maruyama and Fuerst 1985
; Luikart et al. 1998
).
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Regardless of the causes, the dramatic differences in genetic diversity, population differentiation, and LD in different locations have important consequences for our understanding of P. falciparum biology. In parasite populations with low microsatellite diversity, we would also expect to see reduced diversity in antigen-encoding loci (Ferreira et al. 1998
) and a smaller repertoire of variant surface antigens. Hence, under a model of genotype-specific immunity (Gupta et al. 1994
), we might expect effective immunity to malaria to be generated following a relatively small number of infective mosquito bites in low-transmission regions. Second, in regions with low levels of recombination, multilocus genotypes may be maintained through multiple generations. In this situation, it should be possible to track the spread of multilocus genotypes within communities, as is done for bacterial haplotypes. Furthermore, comparison of infection characteristics of multiply represented haplotypes can be used to investigate which aspects of P. falciparum virulence (or other traits) are a product of parasite genetics rather than host factors.
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Acknowledgements |
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Footnotes |
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1 Keywords: Plasmodium falciparum,
linkage disequilibrium
heterozygosity
population structure
infinite-alleles model
stepwise mutation model
2 Address for correspondence and reprints: Timothy J. C. Anderson, Department of Genetics, Southwest Foundation for Biomedical Research, 7620 NW Loop 410, P.O. Box 760549, San Antonio, Texas 78245-0549. E-mail: tanderso{at}darwin.sfbr.org
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