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Giardia duodenalis: Number and Fluorescence Reduction Caused by the Advanced Oxidation Process (H 2O 2/UV)
research-article
Author(s):
José Roberto Guimarães
1 ,
Regina Maura Bueno Franco
2 ,
Regiane Aparecida Guadagnini
1 ,
Luciana Urbano dos Santos
1
,
3
,
*
Publication date (Electronic):
4 December 2014
Publisher:
Hindawi Publishing Corporation
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Abstract
This study evaluated the effect of peroxidation assisted by ultraviolet radiation (H 2O 2/UV), which is an advanced oxidation process (AOP), on Giardia duodenalis cysts. The cysts were inoculated in synthetic and surface water using a concentration of 12 g H 2O 2 L −1 and a UV dose ( λ = 254 nm) of 5,480 mJcm −2. The aqueous solutions were concentrated using membrane filtration, and the organisms were observed using a direct immunofluorescence assay (IFA). The AOP was effective in reducing the number of G. duodenalis cysts in synthetic and surface water and was most effective in reducing the fluorescence of the cyst walls that were present in the surface water. The AOP showed a higher deleterious potential for G. duodenalis cysts than either peroxidation (H 2O 2) or photolysis (UV) processes alone.
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Most cited references45
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Inactivation credit of UV radiation for viruses, bacteria and protozoan (oo)cysts in water: a review.
W Hijnen, E Beerendonk, G. Medema (2006)
UV disinfection technology is of growing interest in the water industry since it was demonstrated that UV radiation is very effective against (oo)cysts of Cryptosporidium and Giardia, two pathogenic micro-organisms of major importance for the safety of drinking water. Quantitative Microbial Risk Assessment, the new concept for microbial safety of drinking water and wastewater, requires quantitative data of the inactivation or removal of pathogenic micro-organisms by water treatment processes. The objective of this study was to review the literature on UV disinfection and extract quantitative information about the relation between the inactivation of micro-organisms and the applied UV fluence. The quality of the available studies was evaluated and only high-quality studies were incorporated in the analysis of the inactivation kinetics. The results show that UV is effective against all waterborne pathogens. The inactivation of micro-organisms by UV could be described with first-order kinetics using fluence-inactivation data from laboratory studies in collimated beam tests. No inactivation at low fluences (offset) and/or no further increase of inactivation at higher fluences (tailing) was observed for some micro-organisms. Where observed, these were included in the description of the inactivation kinetics, even though the cause of tailing is still a matter of debate. The parameters that were used to describe inactivation are the inactivation rate constant k (cm(2)/mJ), the maximum inactivation demonstrated and (only for bacterial spores and Acanthamoeba) the offset value. These parameters were the basis for the calculation of the microbial inactivation credit (MIC="log-credits") that can be assigned to a certain UV fluence. The most UV-resistant organisms are viruses, specifically Adenoviruses, and bacterial spores. The protozoon Acanthamoeba is also highly UV resistant. Bacteria and (oo)cysts of Cryptosporidium and Giardia are more susceptible with a fluence requirement of <20 mJ/cm(2) for an MIC of 3 log. Several studies have reported an increased UV resistance of environmental bacteria and bacterial spores, compared to lab-grown strains. This means that higher UV fluences are required to obtain the same level of inactivation. Hence, for bacteria and spores, a correction factor of 2 and 4 was included in the MIC calculation, respectively, whereas some wastewater studies suggest that a correction of a factor of 7 is needed under these conditions. For phages and viruses this phenomenon appears to be of little significance and for protozoan (oo)cysts this aspect needs further investigation. Correction of the required fluence for DNA repair is considered unnecessary under the conditions of drinking water practice (no photo-repair, dark repair insignificant, esp. at higher (60 mJ/cm(2)) fluences) and probably also wastewater practice (photo-repair limited by light absorption). To enable accurate assessment of the effective fluence in continuous flow UV systems in water treatment practice, biodosimetry is still essential, although the use of computational fluid dynamics (CFD) improves the description of reactor hydraulics and fluence distribution. For UV systems that are primarily dedicated to inactivate the more sensitive pathogens (Cryptosporidium, Giardia, pathogenic bacteria), additional model organisms are needed to serve as biodosimeter.
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Waterborne transmission of protozoan parasites: review of worldwide outbreaks - an update 2004-2010.
Selma Baldursson, Panagiotis Karanis (2011)
The present update gives a comprehensive review of worldwide waterborne parasitic protozoan outbreaks that occurred and were published globally between January 2004 and December 2010. At least one hundred and ninety-nine outbreaks of human diseases due to the waterborne transmission of parasitic protozoa occurred and were reported during the time period from 2004 to 2010. 46.7% of the documented outbreaks occurred on the Australian continent, 30.6% in North America and 16.5% in Europe. Cryptosporidium spp. was the etiological agent in 60.3% (120) of the outbreaks, Giardia lamblia in 35.2% (70) and other protozoa in 4.5% (9). Four outbreaks (2%) were caused by Toxoplasma gondii, three (1.5%) by Cyclospora cayetanensis. In two outbreaks (1%) Acanthamoeba spp. was identified as the causative agent. In one outbreak, G. lamblia (in 17.6% of stool samples) and Cryptosporidium parvum (in 2.7% of stool samples) as well as Entamoeba histolytica (in 9.4% of stool samples) and Blastocystis hominis (in 8.1% of stool samples) were detected. In those countries that are likely affected most a lack of surveillance systems is noticeable. However, countries that established surveillance systems did not establish an international standardization of reporting systems. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Identification of Zoonotic Genotypes of Giardia duodenalis
Introduction Giardia is a genus of intestinal flagellates that infect a wide range of vertebrate hosts. The genus consists of six species, which are distinguished on the basis of the morphology and ultra-structure of their trophozoites [1]. Giardia duodenalis (syn. G. intestinalis, G. lamblia) is the only species found in humans, although it exhibits a wide host range being found in many other mammals. G. duodenalis is the etiological agent of giardiasis, a gastrointestinal infection in humans ranging from asymptomatic to severe diarrhea as well as chronic disease [2]. Giardiasis represents a major public health concern in both developing and developed countries [3],[4]. The economic losses, both direct and indirect, caused by this widespread parasitic infection are considerable. Children are at most risk from the clinical consequences of G. duodenalis infection, particularly those in developing countries and living in disadvantaged community settings [5]. In population- and general practitioner-based studies in The Netherlands, G. duodenalis was identified as the most important gastrointestinal parasitic pathogen [6],[7]. Paradoxically, the diagnosis of giardiasis is not routinely carried out, due to lack of awareness and the similarity of symptoms with other gastro-enteritis diseases. G. duodenalis is also of significant clinical and economic importance in livestock and pet animals [8]–[10]. Giardia has a simple life cycle comprising rapidly multiplying, non-invasive trophozoites on the mucosal surface of the small intestine, and the production of environmentally resistant cysts that are passed with the host faeces. Infectious cysts are transmitted by the faecal-oral route, either by direct contact or by ingestion of contaminated food or water [11]. Illness from this parasite arises through infection in two broad settings: outbreaks and (sporadic) endemic transmissions. Outbreaks are most frequently waterborne and caused by contamination of drinking water, although other transmission routes have been implicated as well [1],[12],[13]. One complicating factor is that the number of asymptomatic carriers, and their role in the spread of the infections, are not clear [6],[7],[12],[14]. G. duodenalis can be considered as a species complex, whose members show little variation in their morphology, yet can be assigned to seven distinct assemblages (A to G) based on genetic analysis [15]. Assemblages A and B are responsible for human infection, and are also found in a wide range of mammals. The remaining assemblages show more restricted host ranges: C and D are found in canids, E in livestock, F in cats, and G in rodents [16]. Genetic characterization has been extensively used to assess the role of animals in the epidemiology of human infection and to develop tools for tracing sources of infection. However, the zoonotic potential of G. duodenalis is still under debate, particularly the role of domestic animals. Transmission may occur from animals to humans or from humans to animals. Alternatively, humans and animals may be infected with host-adapted genotypes only. For example, transmission of Giardia from beavers to humans via drinking water was postulated [17],[18]. In endemic areas where humans and animals live closely together, transmission from human to animals or vice versa may occur [19],[20]. Also, the existence of host-adapted Giardia genotypes has been reported [21],[22]. Until now, the majority of molecular epidemiological studies have been based on the analysis of a single marker from a limited number of isolates. Furthermore, the genetic variability and the usefulness of the different loci in identifying genotypes have not been systematically evaluated. Finally, it remains unclear to what extent allelic sequence heterozygosity (ASH) and genetic exchanges contribute to the genetic variation found in Giardia [23]. In this study the zoonotic potential of G. duodenalis is investigated at different levels of resolution (single and multiple loci on the same dataset). Zoonotic potential is defined here as a G. duodenalis genotype, which has been isolated from both human and animal, sources, and doesn't take into account other epidemiological parameters (such as time and geographical origin). A European network of public and veterinary health Institutions from 9 European countries that focuses on zoonotic protozoan parasites (the ZOOnotic Protozoa NETwork, ZOOPNET) has been established (Sprong et al. submitted) as part of MedVetNet, a European network of excellence working for the prevention and control of zoonoses and food borne diseases. The aims of ZOOPNET were (i) to harmonize the methodology for the detection and control of Giardia and Cryptosporidium, (ii) to investigate the molecular epidemiology of these infections, and (iii) to study the role of animal sources in human disease. A molecular epidemiological database was built in the course of the project, currently containing information on 2476 Giardia isolates, which encompass 3886 sequences, and on 1024 Cryptosporidium isolates, for a total of 1664 sequences. The ZOOPNET-database differs from a representative (e.g. Genbank) or a genomic (e.g. GiardaDB) database [24], as it aims to collect epidemiological data linked to a few molecular markers from as many field isolates as possible. A field isolate can be described best as a DNA sample isolated from a human, animal or environmental source. This implies that an isolate may contain more than one G. duodenalis species or genotypes. A part of the database is already publicly available (https://hypocrates.rivm.nl/bnwww/MedVetNet/). Currently, a more user-friendly web-based database which not only contains all the molecular epidemiological data used in this study, but also allows public and veterinary health researchers to BLAST their sequences in the database, to perform basis phylogenetic analysis and to submit their own data into the database. In the present study, the genetic diversity and geographic distribution of G. duodenalis of human and animal origin, and the potential for zoonotic transmission, were assessed by different molecular genotyping methods. Methods Origin of the isolates Giardia isolates of human and animal origin were collected by Public and Veterinary Health Institutions from the European countries represented in the network, as well as and from external research groups on a voluntary basis. Epidemiologic and molecular data were submitted using an Excel-based file, and form the basis of the information present in the database (Sequences and data used for this study are available on request). Furthermore, Giardia sequences were retrieved from the Genbank database. A selection of these sequences was made using the same strategy as previously described [25]. For example, sequences that were too short to cover regions of variation within any given assemblage were used only for analysis at the level of that assemblage, but not at the level of sub-assemblage. In addition, when multiple, identical sequences from any given isolate were deposited in Genbank, only the longest available sequence was retrieved. Although Genbank sequences constitute ∼45% of the database, limited epidemiological data (mainly country and source of isolation) are available for those isolates. All molecular epidemiological data were stored and analysed in Bionumerics (Version 5.10; Applied Math, Belgium). The contents of the database (February 2009) are described in the supporting information (Text S1). Sequence analysis All of the G. duodenalis sequences were derived from genomic DNA. Most of the sequences were obtained from direct sequencing (occasionally cloned) of PCR products amplified from faecal samples. The sequences of reference isolates originated from laboratory strains, which were grown previously in culture or passaged through suckling mice. Each isolate was characterized using one to four of the most commonly employed genetic markers, which corresponds to portions of the small subunit ribosomal DNA (SSU-rDNA), beta-giardin (BG), glutamate dehydrogenase (GDH), and triose phosphate isomerase (TPI) genes [25]. All sequences were sorted into their different genes, assemblages, and sub-assemblages as well as alignments along the gene using previously defined references (Text S1). All of these markers, with the exception of the SSU-rDNA, have a high, though variable degree of genetic polymorphism [25], and were used to define sub-assemblages and subtypes. Sequences that were too short, or that contain ambiguous nucleotides which prevent their assignment to specific assemblage were excluded from further analysis [25]. Subtyping at the GDH locus was complicated by the use of different primers that amplify different portions of the gene, with only a partial overlap. In order to minimize these transitivity dilemmas, cluster analysis for each locus was performed using Unweigthed Pair Group Method with Arithmetic mean (UPGMA) and “most identical matches” as first and secondary criterion, respectively. A secondary criterion will be applied if two equivalent solutions will emerge from the first criterion. The four markers used in this study are unlinked in the G. duodenalis genome, at least in the genome of assemblage A [22], which is a prerequisite for a multi-locus sequence typing scheme. The following G. duodenalis isolates were used as references for multi-locus sequence typing: for assemblage A, sub-assemblage AI, the axenic strains WB, Portland 1 and Ad-1 [26],[27]; for assemblage A, sub-assemblage AII, the axenic strains Bris-162, Bris-136 and KC8 [28]; for assemblage A, sub-assemblage AIII the isolate ISSGdA614 [22]; for assemblage B, sub-assemblage BIII, the strains BAH12 and Ld18 [26],[29]; and for assemblage B, sub-assemblage BIV, the strains Ad28 and Nij5 [26],[29]. Results The zoonotic potential of G. duodenalis can be inferred by comparing the genotypes of human and animal isolates. Here, genotyping was performed at different levels of resolution. First, for each marker all sequences were assigned to specific G. duodenalis assemblages (A to G) by comparison with previously defined sequences of reference strains [15]. Second, sequences of assemblages A and B were assigned to sub-assemblages AI, AII, AIII, BIII, and BIV using single-nucleotide polymorphisms (SNPs) from reference strains which were identified previously [22]. Third, since considerable sequence heterogeneity was also found within each sub-assemblage, subtypes (AS001, AS002, AS003, etc) were assigned to groups of sequences, on the basis of their similarity [22],[30],[31]. Fourth, genotyping data from different loci were combined to perform a multi-locus analysis. Typing at the assemblage level The sequences from each of the four markers obtained from 2476 Giardia isolates were assigned to G. duodenalis assemblages A to G by comparison with previously defined reference strains (Text S1). The distribution of the assemblages within each source (corresponds to host or host group) was determined (Table 1). In humans (n = 1658), assemblage A (43%), B (56%) and to a much lesser extent C (0,1%), D (0,2%), E(0,2%), and F (0,2%) were found [32],[33]. All of these assemblages were also found in animals. Thus, at this very low level of resolution assemblages A to F can be considered zoonotic. The relative host range of a specific assemblage is calculated as the distribution of the sources within each assemblage (Table 2). The presented calculation does not take the absolute numbers of the sources in a population (e.g. number of cats compared to the number of humans in Europe) and the prevalence of giardiasis of each source into account. Still, assemblages C and D were mainly found in dogs (Table 2), assemblage E in livestock, F in cats and G in rodents (beavers and rats). These results are in agreement with previous findings [11],[16]. Remarkably, the host distribution of assemblage B is predominantly human and to a much lesser extent wildlife and dog (Table 2). 10.1371/journal.pntd.0000558.t001 Table 1 Distribution of assemblages as percentage within each source. Source Cat Cattle Dog Goat & Sheep Human Pig Water Wildlife Other A 43 23 23 17 43 21 70 54 32 B 2 2 9 1 56 0,7 30 20 62 C 3 0 32 0 0,1 0 0 2 0 D 2 0 36 0 0,2 0,7 0 2 0 E 1 75 1 82 0,2 78 0 6 5 F 49 0 0 0 0,2 0 0 0 0 G 0 0 0 0 0 0 0 16 0 Total (n) 158 562 600 207 1658 140 55 172 260 Bold numbers indicate the two highest percentages per column. n is: number of sequences used for the analysis. 10.1371/journal.pntd.0000558.t002 Table 2 Relative distributions of sources in percentage within each assemblage. Source Cat Cattle Dog Goat & Sheep Human Pig Wildlife Total (n) A 19 10 10 8 19 9 24 1206 B 2 2 10 1 62 1 22 1037 C 8 0 86 0 0,3 0 5 200 D 5 0 88 0 0,5 2 5 224 E 0,4 31 0,4 34 0,1 32 3 722 F 100 0 0 0 0,4 0 0 80 G 0 0 0 0 0 0 100 28 The relative distributions are corrected the different numbers of isolates within each source. Calculations are based on the percentages of Table 1, omitting “Other” as source. For example, The relative percentage of assemblage A found in cats is: 43/(43+23+23+17+43+21+70+54)*100. In non-human primates (Source: “Other”), assemblage B is the most prevalent G. duodenalis found. Bold numbers indicate the two highest percentages per column. n is: number of sequences used for the analysis. The host distribution of assemblage A is less restricted than B, where companion animals (29%) livestock (27%) and wildlife (22%) have a comparable prevalence of assemblage A as in humans (19%). This result suggests that humans are the major source of assemblage B, but that domestic animals play a major role in the host range of assemblage A. For those isolates which were characterized at two or more loci (n = 908), the assignment to a specific assemblage obtained at one locus was inconsistent with that obtained at another locus in 13% of them (Table 3). Similar results have been reported in previous studies, using the same markers as those in the present study [20],[25],[34]. This finding was particularly frequent in isolates from dogs (∼34%) where, depending on the markers used, isolates are typed as either host-adapted assemblages C and D, or as assemblage A and B (Table 4). Also in ∼12% of the human isolates (n = 392) mixing of assemblages was observed between A and B. As sexual recombination between different assemblages has not been unequivocally demonstrated [23],[35], these cases are more likely to represent mixed infections. 10.1371/journal.pntd.0000558.t003 Table 3 Mixtures of assemblages in individual isolates with more than two markers. Source Cat Cattle Dog Goat & Sheep Human Pig Water Wildlife Other TYptal Mixed (n) 2 6 45 1 46 4 0 3 14 121 2+ Markers (n) 35 144 134 49 392 56 0 52 53 908 Mixed (%) 6% 4% 34% 2% 12% 7% ND 6% 26% 100% 121 of the 908 isolates with two or more markers (13,3%) contain a mixture of two assemblages. In 3 isolates from dogs, mixtures of three assemblages were present in (ABC and BCD). 10.1371/journal.pntd.0000558.t004 Table 4 Combination of mixed assemblages found in individual isolates. B C D E F A 66 7 7 12 0 B - 4 4 1 0 C - - 15 0 0 D - - - 2 1 Only isolates with more than two markers and with inconsistent assemblage typing at different markers are used. Typing at the sub-assemblage level Sub-groups within assemblages A and B were originally defined by isoenzyme analysis of laboratory-adapted strains, and classified into AI and AII, BIII and BIV [28]. Importantly, other subgroups were observed in a more recent study also based on isoenzyme analysis, and some appear to be host specific [15]. DNA sequence analysis of a smaller number of these isolates confirmed the existence of these subgroups in assemblage A and B at different loci [15]. More recently, a third sub-assemblage within assemblage A (referred to as AIII) was identified, and appears to be specifically associated with wild hoofed animals [22],[36],[37]. The SSU-rDNA locus showed too little variability among assemblage A and B isolates to perform analysis at the sub-assemblage level, whereas sufficient genetic variation was observed at the other three loci [22]. In companion animals and in livestock infected with assemblage A, approximately three quarter of the sequences corresponded to sub-assemblage AI, and the remaining quarter to sub-assemblage AII (Table 5). The opposite was found in human isolates: approximately one quarter of the sequences was identified as sub-assemblage AI and three quarter as sub-assemblage AII. The AIII sub-assemblage was mostly found in wildlife, a few cows and in a single cat isolate, but never in humans. In human isolates with assemblage B, sub-assemblage BIII and BIV were found with a very similar frequency (Table 6). In some wild animals (beaver, muskrat), sub-assemblage BIV was predominantly found. Monkeys and marine animals [22],[38],[39],[40],[41], which together represent the majority of the category “others”, were both infected with sub-assemblage BIII and BIV. Thus, at this level of resolution, G. duodenalis sub-assemblage AI, AII, BIII and BIV are potentially zoonotic, whereas sub-assemblage AIII is found exclusively in animals. 10.1371/journal.pntd.0000558.t005 Table 5 Distribution of sub-assemblages AI, AII, and AIII in different sources. Source Cat Cattle Dog Goat, Sheep Human Pig Wildlife Other AI 69% 62% 73% 78% 25% 86% 44% 55% AII 25% 35% 27% 22% 75% 14% 3% 45% AIII 5% 4% 0% 0% 0% 0% 52% 0% Total (n) 59 113 120 36 594 14 86 80 Sequences of BG (n = 493), GDH (n = 322) and TPI (n = 308), belonging to assemblage A, were subdivided into sub-assemblages AI, AII, and AIII based on SNPs [22]. Distribution of sub-assemblages within a source is calculated as their percentage of occurrence in the three cumulative markers. Bold numbers indicate the (two) highest percentage(s) per column. 10.1371/journal.pntd.0000558.t006 Table 6 Distribution of sub-assemblages BIII and BIV in different sources. Source Dog Human Wildlife Other BIII 27% 56% 6% 43% BIV 73% 44% 94% 57% Total (n) 51 787 31 151 Sequences of BG (n = 254), GDH (n = 366) and TPI (n = 412), belonging to assemblage B, were subdivided into sub-assemblages BIII and BIV based on SNPs [22]. Distribution of sub-assemblages within a source is calculated as their percentage of occurrence in the three cumulative markers. Bold numbers indicate the highest percentage per column. The geographic distribution of sub-assemblages AI and AII in humans and companion animals/livestock was compared. In companion animals/livestock infected with assemblage A, the majority was sub-assemblage AI, and the minority was sub-assemblage AII (Table 7). This distribution was found globally, suggesting that sub-assemblage AI has a preference for companion animals/livestock. Except for Asia and Australia, the opposite was found in humans: the majority was sub-assemblage AII, and the minority was sub-assemblage AI. These data show that the three G. duodenalis sub-assemblages A predominantly/preferentially cycle within defined hosts (AI in livestock, AII in humans, AIII in wildlife), and that these cycles do not interact significantly. The geographic distribution of sub-assemblages BIII and BIV in humans showed marked differences between continents. In Africa, infection with G. duodenalis assemblage B, sub-assemblage BIII is more prevalent (81%) than infection with sub-assemblage BIV (19%), whereas the opposite is found in North-America where 86% of infections are associated with sub-assemblage BIV, and only 14% with sub-assemblage BIII (Table 8). A more balanced distribution is found in Europe and Australia. 10.1371/journal.pntd.0000558.t007 Table 7 Geographic distribution of AI and AII in humans and domestic animals. Human Africa Asia Australia Europe Middle east C/S-America N-America AI 12% 60% 69% 14% 13% 42% 44% AII 88% 40% 31% 86% 88% 58% 56% Total (n) 73 5 26 295 16 160 16 Domestic animals Africa Asia Australia Europe Middle east C/S-America N-America AI 67% 100% 92% 67% 0 77% 65% AII 33% 0% 8% 33% 0 23% 35% Total (n) 3 9 12 334 0 30 84 Data from Table 5 were grouped in “humans” and “domestic animals”, the latter represents cats, cattle, dogs, goats and sheep, and pigs. Distribution of sub-assemblages within a geographic region is calculated as their percentage of occurrence in the three cumulative markers. Bold numbers indicate the (two) highest percentage(s) per column. 10.1371/journal.pntd.0000558.t008 Table 8 Geographic distribution of BIII and BIV in humans. Human Africa Asia Australia Europe Middle east C/S-America N-America BIII 81% 68% 52% 49% 63% 79% 14% BIV 19% 32% 48% 51% 37% 21% 86% Total (n) 54 47 31 508 8 124 14 Distribution of sub-assemblages in humans within a geographic region is calculated as their percentage of occurrence in the three cumulative markers. Bold numbers indicate the (two) highest percentage(s) per column. The finding of a mixture of assemblages in a significant fraction of individual isolates prompted us to investigate whether this occurred at the level of sub-assemblages. In isolates analysed at two or more loci, sub-assemblage results obtained at the different loci were compared. Mixtures were found between AI and AII, and between AI and AIII. No mixtures were detected between AII and AIII. Within assemblage A, 5.4% of mixtures were observed between sub-assemblages AI and AII. Remarkably, mixtures between BIII and BIV characterized 30.3% of the isolates. Analysis of human isolates showed that an infection with AI alone occurs as often as an infection with a mixture of AI and AII (Table 9). A similar situation occurred with sub-assemblage BIII and BIV: an infection with BIV occurs as often as an infection with a mixture of BIII and BIV. 10.1371/journal.pntd.0000558.t009 Table 9 Mixing of A and B sub-assemblages within isolates. All isolates Assemblage A AI AII AIII AI 102 19 3 AII 231 0 AIII 38 Assemblage B BIII BIV BIII 199 144 BIV 132 Human only AI AII BIII BIV AI 12 12 5 2 AII 226 29 8 BIII 193 107 BIV 105 Mixing within individual isolates typed at two or more markers was investigated by comparison of the sub-assemblage assignment of individual markers within one isolate. Mixing between markers is shown in bold. In total 5.4% of mixing was observed between sub-assemblage AI and AII (n = 352 sequences). Mixing was detected between AI-AII, and AI and AIII, but not between AII and AIII. Mixing between sub-assemblage BIII and BIV was found in 30.3% of isolates (n = 475 sequences). In human isolates the mixing between all sub-assemblages within isolates was determined. Single versus multi-locus typing at the isolate level Sequence heterogeneity was also observed within each sub-assemblage, and those genetic variants are referred here as subtypes. In order to determine the zoonotic potential at this level, subtypes were assigned to groups of sequences, on the basis of similarity [22],[30],[31]. Thus, sequences that differ for a single nucleotide difference defined two subtypes. For example, at the SSU-rDNA locus, 15 subtypes were found among assemblage A isolates (Table 10). Of these, 3 and 7 subtypes were exclusively found in humans or in animals, respectively, whereas 5 subtypes contained both human and animal isolates. Notably, these 5 subtypes correspond to 92% of the isolates (humans and animals). Genetic variability at each of the other three loci defined several subtypes (between 3 and 18) in both assemblages A and B, and, as subtypes comprises both human and animal isolates, it is possible to infer a zoonotic potential. Subtypes were also determined for assemblages C to F. The subtypes of assemblage C, D and E found in a few human isolates did not match any of the subtypes found in animals. However, several subtypes of assemblage F found in humans at the BG locus were identical to subtypes found in cats [32]. 10.1371/journal.pntd.0000558.t010 Table 10 Potential zoonotic subtypes using one, two or three markers. Subtype (isolates) Assemblage Human Animal H & A Total SSU-rDNA A 3 (2%) 7 (5%) 5 (92%) 15 (n = 133) B 9 (17%) 3 (2%) 3 (80%) 15 (n = 133) BG A 29 (16%) 39 (15%) 12 (69%) 80 (n = 488) B 45 (40%) 8 (5%) 10 (55%) 63 (n = 211) GDH A 9 (15%) 24 (23%) 7 (62%) 40 (n = 331) B 68 (58%) 18 (13%) 14 (29%) 100 (n = 252) TPI A 12 (11%) 25 (19%) 5 (70%) 42 (n = 266) B 66 (29%) 34 (14%) 18 (57%) 118 (n = 344) rDNA-BG A 6 (76%) 4 (15%) 1 (9%) 11 (n = 33) B 15 (83%) 4 (11%) 1 (7%) 20 (n = 46) rDNA-GDH A 17 (58%) 7 (32%) 2 (11%) 26 (n = 57) B 30 (92%) 3 (5%) 1 (3%) 34 (n = 63) rDNA-TPI A 6 (73%) 5 (15%) 1 (12%) 12 (n = 33) B 16 (38%) 6 (13%) 2 (50%) 24 (n = 48) BG-GDH A 22 (51%) 18 (34%) 2 (15%) 42 (n = 137) B 48 (84%) 10 (16%) 0 58 (n = 95) BG-TPI A 17 (49%) 10 (25%) 3 (26%) 30 (n = 124) B 40 (75%) 10 (23%) 1 (2%) 51 (n = 83) GDH-TPI A 16 (49%) 12 (29%) 2 (22%) 30 (n = 113) B 38 (82%) 12 (18%) 0 50 (n = 88) rDNA-BG-GDH A 15 (78%) 5 (22%) 0 20 (n = 27) B 21 (94%) 2 (6%) 0 23 (n = 34) rDNA-BG-TPI A 10 (81%) 3 (19%) 0 13 (n = 21) B 13 (77%) 6 (23%) 0 19 (n = 27) rDNA-GDH-TPI A 12 (83%) 4 (17%) 0 16 (n = 25) B 16 (94%) 2 (6%) 0 18 (n = 32) BG-GDH-TPI A 23 (62%) 10 (38%) 2 (15%) 35 (n = 101) B 31 (78%) 8 (22%) 0 39 (n = 56) A subtype is a group of sequences (isolates) which are similar. Subtypes of assemblages A and B were identified using a similarity matrix of individual loci. The similarity matrix was calculated using UPGMA as a first criterion, and “most identical matches” as secondary criterion (see Methods). Subtypes with two or three loci were identified by combining the subtyping results of the individual markers. The column Human contains the number of subtypes which members were only human isolates. The column Animal contains the number subtypes, which members were only of animal origin. The column H & A contains the number of subtypes, which consist of both human and animal isolates. Total displays the total number of isolates per (combination of) markers. Between brackets is the percentage (%) or the total number (n) of isolates, which correspond to the number of subtypes. Subtypes of isolates with more than one marker were subsequently assigned by combining the subtypes of each marker. rDNA stands for SSU-rDNA. In order to increase the accuracy of genotyping of isolates at this level, subtypes from two or three loci were combined to define multi-locus genotypes (MLGs). 41 sequences, which could not be unequivocally assigned at the level of assemblage, were excluded from the analysis. Combining SSU-rDNA and BG was possible for 33 isolates of assemblage A, and defined 11 MLGs (Table 10). With this combination only one MLG of assemblage A was potentially zoonotic. The combination of SSU-rDNA and BG for assemblage B also generated a single potentially zoonotic MLG out of 20 MLGs. This MLG was found in 3 out of 46 isolates of assemblage B. The same approach was used for all possible combinations of the 4 markers (Table 10). When using two markers, the number of potentially zoonotic subtypes and the percentage of corresponding isolates decreased significantly. Still, potential zoonotic subtypes of both assemblage A and B were found when using two markers. When subtypes from three loci are combined, two MLGs of assemblage A are potentially zoonotic, and none of assemblage B. These cases have been described before. In Italy, an isolate from a cat (ISSGdA107) has a MLG belonging to sub-assemblage AII [22]. Human isolates from Belgium, Germany, The Netherlands, Italy, France, Nicaragua, and Australia, have the same MLG. The other case is based on two axenic strains that have a MLG belonging to sub-assemblage AI These two isolates, Portland and Ad-1, were originally isolated from human patients in the USA and Australia, respectively [15]. Remarkably, the animal (mostly cattle) isolates having this MLG are from Canada, Italy and Sweden. There are several technical explanations for the relatively low number of zoonotic MLGs as defined using three loci. Most importantly, the number of isolates typed at this level is still relatively small compared to the number of subtypes defined. Furthermore, most MLGs are from human isolates, particularly for assemblage B. Indeed, for many animal isolates of assemblage A or B, only one or two markers were sequenced, and, in some cases, the mixture of zoonotic and non-zoonotic assemblages prevents an unambiguous identification of the MLGs. An alternative, but less accurate, approach for the identification of potential zoonotic MLGs is to combine the zoonotic information of subtypes of individual markers (Table 10, row 1–4). Isolates with 3 markers (BG, GDH and TPI) were considered as potentially zoonotic when all three markers were found to be zoonotic individually. For assemblage A, 36% (n = 101) of isolates with 3 markers was found to be zoonotic. For assemblage B, 4% (n = 56) was potentially zoonotic (Table 11). 10.1371/journal.pntd.0000558.t011 Table 11 Number of potential zoonotic isolates with 3 markers. Assemblage A Human Animal H & A Unassigned Human 0 0 26 39 Cat 0 2 1 4 Cattle 0 0 4 0 Goat &sheep 0 0 2 5 Wildlife 0 11 2 1 Other 0 1 1 2 Total (Isolates) 0 14 36 51 Assemblage B Human Animal H & A Unassigned Human 3 0 1 39 Wildlife 0 0 0 1 Other 0 1 1 10 Total (Isolates) 3 1 2 50 (n = 101) for assemblage A, and 4% (n = 56) for assemblage B, were potentially zoonotic. The zoonotic information of subtypes from each marker (see Table 10) was used to determine the zoonotic potential of isolates with 3 markers (BG, GDH and TPI). Isolates were considered zoonotic (H & A) when the subtypes of all the 3 markers were designated individually as potentially zoonotic. The column Human and Animal contains the number of isolates which subtypes were exclusively found in humans or animals, respectively. The column Unassigned contains the number of isolates from which the subtypes of one or two markers was zoonotic and the other(s) specifically for humans or animals. Thus, 36%. Sequences containing ambiguous nucleotides The presence of heterogeneous sequencing profiles (characterized by two overlapping nucleotide peaks at specific positions) has been reported in several papers from different research groups [19],[22],[32],[42]. Besides the quality of the sequencing reaction itself, two explanations can be given for the presence of those mixed profiles: allelic sequence heterozygosity (ASH) and mixed infections. Giardia has two diploid nuclei, which may accumulate specific mutations independently, and this generates ASH [23]. The fact that G. duodenalis isolates display a very low level of ASH, initially based on the analysis of few isolates and genetic loci [35],[43], has been confirmed by the analysis of the complete WB genome, a strain belonging to assemblage A, sub-assemblage AI [43]. Albeit limited by the small number of loci, and by the difficulty in distinguishing ASH from mixed infections, the data presented in Table 12 clearly shows that heterogeneous sequencing profiles occur much more often in isolates of assemblages B, C, and D than in those from assemblage A, E and F. The number of heterogeneous positions also varied among the loci analysed and the positions involved often coincide with polymorphic sites among different subtypes. 10.1371/journal.pntd.0000558.t012 Table 12 Sequences containing ambiguous nucleotides. SSU-rDNA BG GDH TPI Total (%) A 13% (165) 6% (516) 2% (338) 4% (271) 5% (1290) B 16% (161) 16% (247) 32% (345) 16% (398) 21% (1151) C 5% (65) 24% (42) 15% (53) 47% (45) 20% (205) D 0% (39) 31% (81) 15% (89) 42% (19) 20% (228) E 0% (200) 11% (205) 29% (237) 7% (95) 10% (737) F 0% (13) 8% (24) 6% (36) 8% (13) 6% (86) Occurrence of heterogeneous positions in the sequences of beta-giardin (BG), glutamate dehydrogenase (GDH) and triose phosphate isomerase (TPI) genes as found in isolates of assemblages A to F. Data were taken from the ZoopNet database (February 2009). Between brackets is the total number of sequences used to calculate the percentage of sequences with heterogeneous positions. The occurrence of ASH complicates the assignment of isolates to specific subtypes, especially for assemblage B. Therefore, the occurrence of zoonotic subtypes within assemblage B was tested after the exclusion of ambiguous nucleotides. The BG, GDH, and TPI sequences from a total of 117 assemblage B isolates (100 from humans, and 17 from animals) were merged and clustered. No zoonotic subtypes were detected. When all isolates (n = 199) typed with 2 markers (BG-GDH, BG-TPI, or GDH-TPI) were included in the analysis, 7% were compatible with zoonotic potential. Interestingly, these isolates were from zoo animals and a rabbit. Genetic heterogeneity A measure of the genetic diversity of a locus can be estimated by the number of subtypes corrected for the number of isolates. This was achieved by dividing the number of isolates without ambiguous nucleotides (Table 13) by the number of subtypes. The lowest genetic variability was found at the SSU-rDNA locus. Although 15 subtypes were identified at SSU-rDNA for both assemblage A and B, sequence variation, no distinction could be made between sub-assemblages. Most of the sequence variation found at SSU-rDNA was caused by a minority of the isolates. The genetic variability of the other 3 markers varied only a little from each other. Remarkably, the genetic variability at each marker in assemblage A subtypes was ∼2-fold lower than that found in assemblage B subtypes. The genetic distance within assemblage A was higher than within assemblage B (Table 13). 10.1371/journal.pntd.0000558.t013 Table 13 Genetic heterogeneity of assemblage A and B. Subtypes (isolates) Assemblage Diversity Isolates/subtypes Similarity (%) SSU-rDNA A 8.9 (133/15) 98.2* B 8.9 (133/15) 98.5* BG A 6.1 (488/80) 98.1 (98.8) B 3.4 (211/63) 98.9 GDH A 8.3 (331/40) 96.2 (98.7) B 2.5 (252/100) 96.6 TPI A 6.3 (266/42) 97.0 (99.2) B 2.9 (344/118) 97.7 The genetic diversity was measured by dividing the total number of isolates by the total number of subtypes. High numbers represent low genetic diversity. Sequences with ambiguous nucleotides were not taken into account. Percentage of similarity is based on multiple alignment of UPGMA. Values in brackets are without AIII. *With SSU-rDNA no differences were observed between AI, AII and AIII, and between BIII and BIV. Phylogenetic analysis of assemblages A and B The multi-locus analysis of field isolates may not represent G. duodenalis genotypes as they could consist of a mixture of several G. duodenalis (sub)species. To identify multi-locus genotypes among isolates of assemblage A, the sequences of the BG, GDH, and TPI loci from isolates with matching assignment were merged, a multiple alignment was generated and trees were constructed using complete linkage. To increase the accuracy of the analysis, only multi-locus genotypes found in more than one isolate were selected. In total 9 MLGs were identified from 84 isolates for assemblage A (Figure 1). To evaluate the robustness of the inferred relationships within assemblage A, trees were also generated from each marker. The clustering generated from the individual markers was congruent with the clustering of multi-locus profile (Table 14). These analyses confirmed the existence of three monophyletic sub-assemblages at each marker. However, the sequence variation at each locus was too low to discriminate between the different subtypes within sub-assemblage AI and AII. For example, subtype AI-1 cannot be distinguished from AI-3 with GDH, and AI-1 is identical to AI-2 when using BG and TPI. Two genotypes were identified, AI-III, and AII-II, which contained both human and animals isolates, which is in agreement with the MLGs identified previously (Table 10). 10.1371/journal.pntd.0000558.g001 Figure 1 Phylogenetic analysis of assemblage A. Phylogenetic trees of 84 isolates with 3 markers were inferred using Unweighted Pair Group Method with Arithmetic mean, corrected by complete linkage, which uses the lowest similarities found between two clusters. Individual and merged BG, GDH and TPI nucleotide sequences were used. Bootstrap values were calculated by the analysis of 1000 replicates. Only bootstrap values >60 are shown. The phylogenetic analysis of assemblage A shows that the three sub-assemblages clustered together with high bootstrap support (i.e., they are monophyletic). The genetic diversity of the multi-locus genotypes (isolates/subtypes: 9,3) is relatively low (see Table 13), and the maximum genetic distance is 4,0%. 10.1371/journal.pntd.0000558.t014 Table 14 Congruence of phylogenetic analysis of assemblage A and B. Ass A BG GDH TPI Merge BG 100 86 96 96 GDH 100 90 97 TPI 100 97 Merge 100 Ass B BG GDH TPI Merge BG 100 12 31 62 GDH 100 6 46 TPI 100 74 Merge 100 Congruence is calculated from the cluster analysis of 3 markers (BG, GDH, TPI) and of their merge. See also Figure 1 (assemblage A) and Figure 2 (assemblage B). A similar analysis was performed for assemblage B isolates. In total 31 genotypes were identified from 65 isolates (Figure 2). The clustering generated from individual markers was able to discriminate sub-assemblage BIII from BIV, but with low bootstrap values, especially for BG. However, multi-locus genotyping of assemblage B was inconsistent with genotyping at the sub-assemblage level: significant mixing (∼30%) of BIII and BIV was observed. In contrast to assemblage A, clustering from individual loci of assemblage B was incongruent with clustering of multiple loci (Table 14). These results are consistent with the multi-locus subtyping of isolates: In assemblage A, mixing is less frequently observed than in assemblage B (Table 9). Removal of the “mixed MLGs” from the genotyping analysis did not alter the outcome of the analysis significantly: The bootstrap values as well as the congruency remained low (not shown). Compared to assemblage A, the MLG diversity (number of genotypes) of assemblage B is 4 times higher, but their genetic distance is two times lower, both at the level of individual markers and at the level of MLG (Figures 1 and 2). 10.1371/journal.pntd.0000558.g002 Figure 2 Phylogenetic analysis of assemblage B. Phylogenetic trees of 65 isolates of assemblage B with 3 markers were constructed using Unweighted Pair Group Method with Arithmetic mean, corrected by complete linkage, which uses the lowest similarities found between two clusters. Individual and merged BG, GDH and TPI nucleotide sequences were used. Bootstrap values were calculated by the analysis of 1000 replicates. Only bootstrap values >60 are shown. The phylogenetic analysis of the merged sequences shows significant mixtures of the BIII and BIV sub-assemblages. The genetic diversity of the multi-locus genotypes (isolates/subtypes: 2,1) is relatively high (see Table 13), and the maximum genetic distance is 1,7%. Discussion In the present study, the zoonotic potential, genetic diversity, and the geographic distribution of G. duodenalis genotypes from the ZOOPNET-database were assessed. Accurate molecular typing is imperative for unraveling the intricate epidemiology of giardiasis. Molecular markers should be able to discriminate between morphologically identical isolates that may differ for important properties, like virulence and host-specificity. The genes used in this study have housekeeping functions and are presumably not directly linked to virulence and host-specificity. The discriminatory properties of the commonly used diagnostic markers of G. duodenalis have not been investigated systematically. Here, different molecular typing methods were used to address the discriminatory properties of SSU-rDNA, BG, GDH and TPI. Typing at the level of assemblages is relatively straightforward, and can be achieved with all four markers. Importantly, assemblages C, D, E and F are found in rare human cases (0.8% of human cases). These findings demonstrate that G. duodenalis assemblages C to F can indeed infect humans. Since human infection with these assemblages occurs infrequently, it seems that the host-range of G. duodenalis may be determined by more factors than the host-parasite interaction alone. It is also unclear whether human infections with assemblages C to F result in disease. Typing at the level of sub-assemblages was only possible for BG, GDH and TPI, but not for SSU-rDNA, because the SSU-rDNA locus showed too little intra-assemblage variability in both assemblage A and B (see also [22]). Assemblage A Significant differences were found between the sub-assemblages AI, AII and AIII. Although sub-assemblages AI and AII are found in both humans and animals, sub-assemblage AI is preferentially found in livestock and pets whereas sub-assemblage AII is predominantly found in humans. Sub-assemblage AIII is almost exclusively found in wild hoofed animals, and is most likely a host-adapted genotype. Several potential zoonotic subtypes, which correspond to the majority of the isolates, were identified at the level of individual markers (Table 10). However, combining the subtype information of the available markers of individual isolates (MLG) resulted in only two potentially zoonotic genotypes within assemblage A. Thus, the most important conclusion is that analysis of single markers is inaccurate for molecular epidemiological studies. This finding is consistent with the phylogenetic analysis of assemblage A: the genetic variation found in individual markers is too low to allow discrimination of different genotypes (Figure 1). Conversely, many subtypes for assemblage A were identified for each marker (Table 10: 15 for SSU-rDNA, 80 for BG, 40 for GDH, and 42 for TPI). Subtyping is based on similarity, and a single point mutation has been considered sufficient to describe a new subtype. For all markers it was found that only a minority of subtypes corresponded to the majority of isolates and that the majority of subtypes were found in only one or two isolates. Whether all these subtypes correspond to new genotypes or whether some of them will turn out to be (sequence) artifacts is unclear. The significance of all these subtypes will become clearer when more molecular epidemiological data are added to the database. From the six MLGs defined within assemblage A, two are potentially zoonotic. Genotype AI-3 consisted mostly of animal isolates and of a few human (axenic) isolates, whereas AII-2 consisted predominantly of human isolates and a single cat isolate. These findings are in agreement with the preferential distribution of AI and AII found at the level of sub-assemblages. Since the number of MLG isolates is relatively small, especially for pet isolates typed with three (consistent) markers, more genotypes with zoonotic potential may exist. The assumption is that genetically identical G. duodenalis found in both humans and animals, are zoonotic. Remarkably, the isolates having zoonotic potential were not epidemiologically linked (i.e. same location, same study). These findings highlight the global distribution of these G. duodenalis genotypes, but provide little evidence for zoonotic transmission. Assemblage B The host distribution of assemblage B is predominantly human and to a much lesser extent wildlife and dog (Table 2). Assemblage B is also found regularly in (captive) non-human primates. They generally do not play significant roles in the life cycle of G. duodenalis, which involve humans. The abundance of assemblage B in (captive) non-human primates may be due exposure to human sources. Alternatively, assemblage B is well-adapted to infect primates. Genotyping of assemblage B was more problematic. The genetic diversity (number of subtypes) and the percentage of sequences with mixed templates (ambiguous nucleotides) were ∼2,5 and 4 times higher than for assemblage A, respectively. The mixing of the sub-assemblages BIII and BIV within isolates was ∼30%, which is 6 times more than the mixing observed between sub-assemblages AI and AII. Furthermore, the 119 field isolates of assemblage B with 3 markers (BG, GDH, TPI) consisted of 102 humans, 13 primates, 2 zoo animals, one guinea pig and one rabbit. Relevant animal sources, in particular dogs and marine animals [38] are present in the database, but are not typed with the 3 markers of assemblage B. Together, these factors hamper the precise assignment of isolates at the assemblage or subtype level. Typing with two but not with three markers resulted in the identification of a few potentially zoonotic MLGs. Alternative approaches, e.g. removal of ambiguous nucleotides or estimation of potential zoonotic MLGs by combining the zoonotic information from individual markers, resulted in the identification of potential zoonotic genotypes, which corresponded to only 4–7% of the isolates of assemblage B. All in all, no clear genotypes could be inferred for assemblage B, and no distinction between zoonotic and host-adapted genotypes could be made within assemblage B. Mixed infections and allelic sequence heterozygosity Two principal mechanisms can explain the occurrence of ambiguous nucleotides and the inconsistent assignment of single isolates at the level of both assemblage and sub-assemblage: (i) “true” mixed infections; and ii) allelic sequence heterozygosity (ASH). The presence of more than one G. duodenalis type during a symptomatic infection has important implications for the etiology of giardiasis: it is unclear how humans and animals become infected with two or more G. duodenalis types. Subjects may be infected simultaneously with different Giardia assemblages (or even subtypes), because of environmental mixing, for example in water. Alternatively, subjects are asymptomatically infected with one Giardia assemblage, but become ill/symptomatic from a second infection with another Giardia assemblage. The latter hypothesis is supported by the finding of asymptomatic subjects [6],[7],[12],[14]. The occurrence of mixed infections has important epidemiological implications. Using only one marker for the assignment of isolates to specific (sub)-assemblages is not always reliable, as different markers can give different results. For example, isolates can be typed as “potentially zoonotic” with one marker, but as “host-adapted” with another. More reliable results are obtained when multiple markers are used for typing. On the other hand, “true” G. duodenalis genotypes are difficult to identify in mixed infections. Allelic sequence heterozygosity (ASH) is not unusual for diplomonads, which have two diploid nuclei, and replicate asexually [1]. Indeed, in asexual eukaryotes, the two allelic gene copies at a locus are expected to become highly divergent as a result of the independent accumulation of mutations in the absence of segregation (Meselson's effect). Therefore, substantial genetic differences are expected to accumulate among the chromosome homologues in asexual organisms with a ploidy of two or higher [44]. However, the ASH found in the genome of G. duodenalis assemblage A is extremely low [43], but the mechanism(s) responsible remained undetermined. Based on the presence of ambiguous nucleotides in sequences derived from PCR products, it is to be expected that the ASH is higher in assemblages B, C, and D than in assemblages A, E and F (Table 11). Recent studies have shown that G.duodenalis may be able to undergo sexual reproduction, a phenomenon that can influence ASH levels [35],[45]. However, the frequency of recombination is not known, nor its impact on the etiology and epidemiology of giardiasis [11],[23]. Future directions The ZOOPNET-database is the largest molecular epidemiological database of G. duodenalis to date. Still, the limitations of this unique database are apparent. Currently, the database contains a heterogeneous geographic- and incomplete source distribution of a “limited” set of isolates. Furthermore, each isolate is characterized by a small set of epidemiological data and limited sequence data. Our aim is to expand and improve the ZOOPNET database: since the content of the ZOOPNET database is accessible via internet, scientists can use these data for their own epidemiological studies. The web-based ZOOPNET-database will remain accessible, and its interface will be soon improved. Both veterinary and public health researchers are welcome to submit their molecular epidemiological data on G. duodenalis and Cryptosporidium to ZOOPNET. The web-based ZOOPNET-database has a flexible content and provides a powerful tool for new (inter)national studies on giardiasis (and cryptosporidiosis). Supporting Information Text S1 Contents of the Giardia database, geographical distribution of the Giardia isolates present in the database, and GenBank accession numbers of reference sequences. (0.07 MB DOC) Click here for additional data file.
Author and article information
Journal
Journal ID (nlm-ta): Int Sch Res Notices
Journal ID (iso-abbrev): Int Sch Res Notices
Journal ID (publisher-id): ISRN
Title:
International Scholarly Research Notices
Publisher:
Hindawi Publishing Corporation
ISSN
(Electronic):
2356-7872
Publication date Collection: 2014
Publication date
(Electronic):
4
December
2014
Volume: 2014
Electronic Location Identifier: 525719
Affiliations
1Department of Sanitation and the Environment, School of Civil Engineering, Architecture
and Urbanism, University of Campinas (UNICAMP), CP 6021, 13083-852 Campinas, SP, Brazil
Author notes
Article
DOI: 10.1155/2014/525719
PMC ID: 4897353
PubMed ID: 27379301
SO-VID: a9499df6-6e69-4a31-a6c0-d42ff4970b81
Copyright © Copyright © 2014 José Roberto Guimarães et al.
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This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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received
: 1
September
2014
Date
accepted
: 4
November
2014
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