Literature DB >> 23826280

Global Distribution of Campylobacter jejuni Penner Serotypes: A Systematic Review.

Brian L Pike1, Patricia Guerry, Frédéric Poly.   

Abstract

Penner serotyping has been the principal method for differentiating Campylobacter isolates since its inception. Campylobacter capsule polysaccharide (CPS), the principal serodeterminant on which Penner serotyping is based, is presently of interest as a vaccine component. To determine the required valency of an effective CPS-based vaccine, a comprehensive understanding of CPS distribution is needed. Because of the association between Penner serotype and CPS, we conducted a systematic review to estimate the frequency and distribution of Penner serotypes associated with cases of Campylobacteriosis. In total, more than 21,000 sporadic cases of C. jejuni cases were identified for inclusion. While regional variation exists, distribution estimates indicate that eight serotypes accounted for more than half of all sporadic diarrheal cases globally and three serotypes (HS4 complex, HS2, and HS1/44) were dominant inter-regionally as well as globally. Furthermore, a total of 17 different serotypes reached a representation of 2% or greater in at least one of the five regions sampled. While this review is an important first step in defining CPS distribution, these results make it clear that significant gaps remain in our knowledge. Eliminating these gaps will be critical to future vaccine development efforts.

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Year:  2013        PMID: 23826280      PMCID: PMC3694973          DOI: 10.1371/journal.pone.0067375

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Campylobacter is a gram negative organism that belongs to the class epsilonproteobacteria, and is recognized as a major foodborne pathogen in developed and developing countries alike. Campylobacteriosis, the disease caused by Campylobacter spp., is often a self-limiting disease commonly associated with diarrhea, cramping, headache, and fever. However, severe cases, including those resulting in dysentery, may require medical attention. Furthermore, long-term sequelae, including Guillain-Barré Syndrome (GBS), reactive arthritis, and irritable bowel syndrome (IBS) have been linked to infection [1]. The two major Campylobacter spp. involved in human diarrheal disease are C. jejuni and C. coli. However, for the purpose of this systematic review, analysis will be limited to C. jejuni. For the past 30 years, epidemiologic studies of C. jejuni have used the Penner serotyping scheme, a passive slide hemaglutination assay developed by Penner and Hennessy [2], to classify differing Campylobacter isolates. This system, which is also called the heat stable or HS serotyping system, was originally thought to be based on lipopolysaccharides (LPS), also referred to as the “O” antigen, hence the frequent designation of “O” serotypes in earlier publications. However, more recent data show that C. jejuni does not express LPS, but instead expresses lipooligosaccharides (LOS) and a capsule polysaccharide (CPS) [3], [4]. The CPS has since been shown to be the primary serodeterminant of the Penner scheme [4], [5]. Today, there are 47 recognized HS serotypes of C. jejuni, which mirror CPS variation within the species [1]. These 47 serotypes, because of similarities in CPS structure, may further be refined into 35 serotypes, serotype cross-reactive pairs or complexes (See Methods). Because CPS is one of the few identified virulence factors of C. jejuni [6] and [7], the potential use of CPS-based vaccines to protect against infection has gained some interest and early evidence appears to support such a strategy. Vaccines based on the CPS of C. jejuni strain 81–176 (HS23/36) and CG8486 (HS4 complex) conjugated to CRM197 (a diptheria toxin mutant) reduced disease in the intranasal mouse model following challenge with the homologous strain. And, vaccines made with CPS of 81–176 also provided 100% protection against diarrheal disease in Aotus nancymaae, a new world monkey, when challenged with 81–176 [8] and 86% protection when challenged with CG8421, another HS23/36 strain which has been used in development of a human challenge model [9] and [Gregory et al. (in preparation)]. These data suggest that CPS based vaccines are a viable strategy to protect against diarrheal disease. However, continued pursuit of such a strategy will require answering questions about the required valency of a broadly effective CPS conjugate vaccine against C. jejuni. A first step in that direction will be determining the prevalence of CPS types circulating globally. Due to the correlation between CPS and Penner types, this review aims to summarize Penner serotyping data of clinical isolates, and by extension C. jejuni CPS type distribution, as reported in the published literature since the advent of Penner’s method.

Methods

Relevant published data were identified from searches of PubMed for research articles containing the keyword “Campylobacter” and the term “Penner” or “serotype”. At the same time, non-English publications, and review articles were excluded. The titles and abstracts of the identified articles were screened for relevance and evaluated independently by two of the study authors for inclusion on the basis of the availability of the article, and whether or not the article had previously unpublished, extractable data. Inclusion was limited to studies of natural sporadic C. jejuni infections in which human isolates were typed by the Penner-serotyping method. Research articles that reported data on fewer than ten isolates, data from outbreaks, or data from collections of isolates with evidence of selection bias (i.e. studies examining isolates from Guillain-Barré Syndrome patients only) were excluded. No further exclusionary restrictions were applied, such as the makeup of the study population, the length of the observation period, or the publication date. Disagreements between reviewers concerning inclusion were resolved by consensus. Data from studies selected for inclusion were extracted by two authors independently. The data were extracted according to a fixed protocol to include, the author, year, and location of the study, the demographics of the study population, the serotyping methodology used, the length of the study period, and the number of serotypes screened, and a count of the serotypes identified. Extracted data were entered independently into a Microsoft Access (Redmond, WA) database. Reported isolates were assigned to 1 of 35 commonly observed serotypes or cross-reactive serotype groups (HS1/44, HS2, HS3, HS4 complex (includes HS4/13/16/43/50/63/64/65), HS5/31, HS6/7, HS8/17, HS9, HS10, HS11, HS12, HS15, HS18, HS19, HS21, HS22, HS23/36, HS27, HS29, HS32, HS33, HS35, HS37, HS38, HS40, HS41, HS42, HS45, HS52, HS53, HS55, HS57, HS58, HS60, HS62, or Non-Typable). Some Penner serotypes were reported as belonging to more than one of the HS types indicated above, and such isolates were distributed across each serotype indicated. For example, an isolate reported as belonging to serotype HS24/55/60 would be distributed equally as HS24 = 0.33, HS55 = 0.33, and HS60 = 0.33. Several research articles also grouped a fraction of isolates into the non-descript category “Other”, when the relative proportion of a given serotype was below a reporting threshold determined by study authors. In these instances, the serotypes of the “Other” isolates were imputed across each study and distributed in the relative global proportions calculated for the 35 C. jejuni serotypes outlined above. C. coli serotypes, when reported, were not included in this analysis. Discrepancies concerning serotype assignment were resolved through discussion amongst all study authors. Serotypes were tallied within each study, and their respective proportions were calculated. Pooled proportional estimates were computed across all studies and within studies grouped by region. The proportional estimates were computed using the DerSimonian & Laird random effects model [10]. Strong evidence of heterogeneity existed across the studies for most of the serotypes examined, the exception being those rarely reported in the literature (HS22, HS29, HS32, HS33, HS35, HS38, HS40, HS41, HS42, HS45, HS52, HS55, HS57, HS60, HS62, and HS66). All statistical analyses were performed using Stata Version 12 (College Station, TX).

Results

A search of the PubMed database identified 596 research articles for possible inclusion. After removing the duplicates, 488 research articles remained for consideration. A review of the titles and abstracts excluded another 410 articles from consideration based on relevance to the topic of interest, leaving 78 studies to be assessed for eligibility for inclusion. The full text of each of the 78 articles was examined in more detail, and data from 54 studies were included for the purpose of this review. Five publications reported stratified data that are included as separate studies for the purpose of this review, bringing the total number of studies to 59 (See Table 1 and Supplementary Figure S1).
Table 1

Included Studies.

First AuthorCountrya Totalb Yearc Duratione Agef CatchmentArea g, h Serotypes Tested i
Karmali [13] Canada285197836Children 0 to >10Point55
Taylor [14] USA4619806MixedRegionalNS
Skirrow [15] England34001981132MixedCountry43
McMyne [16] Canada1531982d NSNSRegional55
Lastovica [17] South Africa25819826Children <10Point60
Georges-Courbot [18] CAR94198217Children <15Point56
Neogi [19] Bangladesh102198312MixedPoint42
Patton [20] USA1491985d NSNSCountry56
Jones [21] Britain4061985d NSNSUnknown32
Sjogren [22] Sweden29198512Adults >15Point23
Sjogren [22] Mexico130198512Infants 0–5Point23
Nishimura [23] Japan691985NSNSUnknownNS
Chatzipanagiotou [24] Greece31198712Children <14Point25
Albert [25] Australia108198812MixedRegional66
Albert [26] Australia1219886MixedRegional66
Sjogren [27] Kuwait471989 d NSMixedPointNS
Zaman [28] Saudi Arabia46198912MixedPointNS
Prasad [29] India221989132MixedRegional72
Wareing [30] England75419907NSCountry42
Takahashi [31] Japan4551990156NSCountry25
Owen [32] UK27199212NSCountry45
Asrat [33] Ethiopia35199212MixedPoint33
Owen [34] England398199312NSCountry47
Marshall [35] England701994 d NSNSPointNS
Gibson [36] UK2719942NSCountry45
Nishimura [23] China851994NSNSRegionalNS
Fang [37] Taiwan271994120MixedUnknown25
Nielsen [38] Denmark136199512NSCountry49
Nielsen [39] Denmark42199511NSCountry47
Poly [5] Egypt142199543Infants 0–5Point47
Frost [40] Wales2310199612NSCountry66
Hudson [41] New Zealand6919967NSPointNS
Strid [42] Denmark1731996NSMixedCountry47
Petersen [43] Denmark42199624NSCountry47
Smith [44] Nigeria171997 d NSNSPoint64
Sopwith [45] England2277199724MixedRegionalNS
McKay [46] Scotland3155199812NSCountry66
Moser [47] Germany201199812NSRegional9
Chatzipanagiotou [24] Greece98199824Children <14Point25
Poly [5] Thailand103199872Adults >15Country47
Vierikko [48] Finland51819993NSCountry25
Saito [49] Japan158200036NSRegional25
Eyles [50] New Zealand54200012MixedRegionalNS
Ioannidis [51] Greece207200036NSRegional25
Gilpin [52] New Zealand6620006NSRegionalNS
Nielsen [53] Denmark973200112NSRegional47
Fussing [54] Denmark926200113MixedRegional47
Wierzba [55] Egypt20200130MixedPointNS
Oza [56] England4142002 d NSNSUnknown66
Cornelius [57] New Zealand10620022NSPointNS
Gilpin [58] New Zealand16820026NSRegional43
Schonberg-Norio [59] Finland11420023NSCountry25
Sonnevend [60] UAE41200224NSPoint25
Nakari [61] Finland622200248MixedCountry25
Nakari [61] Finland785200248MixedCountry25
Miljkovic-Selimovic [62] Serbia29200321NSRegionalNS
McTavish [63] New Zealand1122006NSMixedCountry43
Islam [64] Bangladesh312006NSNSPointNS
Grozdanova [65] Macedonia20200811NSRegional25

Country = Country from which sporadic diarrhea cases were identified;

Total = Total number of isolates analyzed;

Year = Year specimen collection initiated.

When the year in which specimen collection began was not specified, publication year used;

Duration = Length of specimen collection period in months;

Age in years, “Mixed” indicates specimens collected from both children and adults;

Catchment indicates the size of the collection area,

Point = a single collection point (e.g. single hospital or clinic);

Serotypes Tested = number of serotypes included in the panel of screening sera used in each study. A number of studies screened for C. coli serotypes in addition to those for C. jejuni. Therefore, the number of serotypes screened for may exceed the 35 C. jejuni serotypes enumerated in this review. Abbreviations: CAR = Central African Republic, UAE = United Arab Emirates, UK = United Kingdom, USA = United States of America; NS = Not Specified.

Country = Country from which sporadic diarrhea cases were identified; Total = Total number of isolates analyzed; Year = Year specimen collection initiated. When the year in which specimen collection began was not specified, publication year used; Duration = Length of specimen collection period in months; Age in years, “Mixed” indicates specimens collected from both children and adults; Catchment indicates the size of the collection area, Point = a single collection point (e.g. single hospital or clinic); Serotypes Tested = number of serotypes included in the panel of screening sera used in each study. A number of studies screened for C. coli serotypes in addition to those for C. jejuni. Therefore, the number of serotypes screened for may exceed the 35 C. jejuni serotypes enumerated in this review. Abbreviations: CAR = Central African Republic, UAE = United Arab Emirates, UK = United Kingdom, USA = United States of America; NS = Not Specified. In total, the studies were published between 1982 and 2011, reported data on 21,394 individual C. jejuni isolates from sporadic cases of enteric infection collected between 1978 to 2008 from 29 different countries (Table 1). Study size and duration varied considerably. The largest and smallest studies comprised 3,400 and 12 isolates, respectively (mean = 363), while the duration of the studies analyzed ranged from 13 years to 2 months. The included studies also varied in design (i.e. sampling methodology and the size of the catchment area) as well as in their target populations (i.e. age, traveler vs. resident populations). The number of serotypes screened for in each study also differed, ranging from nine to 72 serotypes (including serotypes for C. coli) (See Table 1). Overall, the studies predominately sampled European populations. Nearly 85% (n = 18,184) of the isolates included in this analysis were from Europe, while 1,186 were from Asia, 763 were from North America, 695 were from the Oceanic Region, and 566 were from Africa (Figure 1). No studies examining South America were identified in the literature search.
Figure 1

Proportional representation of the three most dominant HS serotypes (HS4c, HS2, and HS1/44) by region.

Lightly shaded areas represent the 33 (of 35) HS serotypes not indicated in color on the graph. Darkly shaded areas indicating those isolates not accounted for in the 35 HS serotypes examined were empirically derived by subtracting the sum of the percentages of the 35 serotypes from 100%. The darkly shaded area also includes non-typable isolates.

Proportional representation of the three most dominant HS serotypes (HS4c, HS2, and HS1/44) by region.

Lightly shaded areas represent the 33 (of 35) HS serotypes not indicated in color on the graph. Darkly shaded areas indicating those isolates not accounted for in the 35 HS serotypes examined were empirically derived by subtracting the sum of the percentages of the 35 serotypes from 100%. The darkly shaded area also includes non-typable isolates. Globally, eight serotypes (HS4 complex, HS2, HS1/44, HS11, HS5/31, HS8/17, HS6/7, and HS3) accounted for 50.4% of all isolates. The dominant serotypes were those of the HS4 complex (15.3%, CI: 12.9, 17.6), HS2 (13.5%, CI: 11.3, 15.8), and HS1/44 (8.2%, CI: 7.1, 9.3) (See Table 2). Combined, these three serotype categories accounted for nearly 40% of all isolates reported worldwide. HS4 complex, HS2, and HS1/44 were also the three serotypes with the greatest proportional representation across each of the five regions examined (Table 3 and Figure 1). Moreover, these three serotypes remained the most prevalent serotypes when the data were stratified by the economic status of the country in which the study was conducted (Tables 4).
Table 2

Global HS Serotypes with Proportional Estimates of 2% or Greater.

%lciuci
Global (n = 21,394)
HS4c15.312.917.6
HS213.511.315.8
HS1/448.27.19.3
HS113.12.24.0
HS5/312.92.23.5
HS8/172.82.23.4
HS6/72.41.83.1
HS32.21.72.7
Table 3

HS Serotypes with Proportional Estimates of 2% or Greater by Region.

%lciuci
Africa (n = 566)
HS4c7.02.811.2
HS1/446.82.810.8
HS36.31.111.6
HS26.22.110.3
HS5/316.22.310
HS23/364.22.36.1
HS8/174.10.18.1
HS533.30.26.4
HS192.00.63.4
Asia (n = 1,186)
HS211.56.117
HS4c8.94.313.5
HS1/444.21.96.5
HS153.41.15.7
HS193.10.95.4
HS23/363.00.95.0
HS8/172.91.04.8
HS32.61.14.2
HS372.40.64.1
Europe (n = 18,184)
HS4c17.314.620
HS215.312.118.5
HS1/449.17.710.4
HS114.02.85.2
HS6/73.62.74.5
HS5/312.61.93.4
HS8/172.21.52.9
HS122.11.42.8
HS582.01.03.0
N. America (n = 763)
HS4c23.515.331.7
HS210.74.317.1
HS1/449.37.111.5
HS5/316.83.010.5
HS8/175.33.47.2
HS34.91.88.1
HS113.61.25.9
HS212.50.84.2
HS6/72.30.73.9
HS182.10.83.4
HS372.10.73.4
Oceania (n = 695)
HS218.27.928.5
HS4c17.410.724.0
HS1/4410.56.314.8
HS8/178.83.514.1
HS23/364.22.45.9
Table 4

HS Serotypes with Proportional Estimates of 2% or Greater by Economic Development Status.

%lciuci
Developed (n = 1,222)
HS4c17.515.219.8
HS216.513.819.1
HS1/449.07.810.1
HS113.52.44.5
HS6/72.92.13.6
HS8/172.82.13.4
HS5/312.62.03.3
HS32.11.62.6
Developing (n = 20,172)
HS4c8.24.811.5
HS1/445.02.97.1
HS25.02.87.3
HS5/314.32.36.3
HS33.71.75.7
HS8/173.51.55.5
HS23/363.31.55.1
HS152.91.14.6
HS532.91.04.8

Tables 2–4: HS serotypes with a proportional representation of 2% or greater, Globally (Table 2), by Region (Table 3), and by Economic Status (Table 4). Proportional estimates (%) were computed using the DerSimonian & Laird random effects model and include the upper (uci) and lower (lci) 95% confidence intervals. Note: Isolates categorized as a cross-reactive pair HS serotype (e.g. HS1/44, HS5/31, HS6/7, HS8/17, and HS23/36) were originally reported as one of the two serotypes or as the paired serotype itself. Isolates categorized as HS4 complex (or HS4c) represent isolates reported as any combination of the following serotypes HS 4/13/16/43/50/63/64/65.

Tables 2–4: HS serotypes with a proportional representation of 2% or greater, Globally (Table 2), by Region (Table 3), and by Economic Status (Table 4). Proportional estimates (%) were computed using the DerSimonian & Laird random effects model and include the upper (uci) and lower (lci) 95% confidence intervals. Note: Isolates categorized as a cross-reactive pair HS serotype (e.g. HS1/44, HS5/31, HS6/7, HS8/17, and HS23/36) were originally reported as one of the two serotypes or as the paired serotype itself. Isolates categorized as HS4 complex (or HS4c) represent isolates reported as any combination of the following serotypes HS 4/13/16/43/50/63/64/65. Beyond the three most dominant serotypes, in all, 17 different serotypes reached a proportional representation of 2% or more in at least one of the five geographic regions considered (Table 5). Nine serotypes reached the 2% threshold in Africa, Asia, and Europe, accounting for 46.1%, 42%, and 58.2% of the total number of isolates in each region, respectively. Combined, the studies from North America had 11 serotypes with a representation of 2% or greater, totaling 73.1% of isolates, while five serotypes met the 2% threshold in Oceania, accounting for 59.1% of isolates in this geographic region. Notably, nearly 14% of isolates were non-typable by the Penner scheme globally (data not shown), a likely consequence of the fact that CPS expression in C. jejuni is known to be phase variable [6] and successful typing in the Penner scheme requires CPS expression. As discussed below, methodological differences amongst the studies may also contribute to an artificially inflated number of non-typable isolates.
Table 5

Comparison of HS Serotypes with Proportional Estimates by Region: Proportions that met or exceeded the 2% threshold are bolded and those that did not are indicated in italics.

Global %Africa %Asia %Europe %N. America %Oceania %
(n = 21,394)(n = 566)(n = 1,186)(n = 18,184)(n = 763)(n = 695)
HS4c 15.3 7.0 8.9 17.3 23.5 17.4
HS2 13.5 6.2 11.5 15.3 10.7 18.2
HS1/44 8.2 6.8 4.2 9.1 9.3 10.5
HS11 3.1 1.6 0.2 4.0 3.6 1.7
HS5/31 2.9 6.2 1.8 2.6 6.8 1.5
HS8/17 2.8 4.1 2.9 2.2 5.3 8.8
HS6/7 2.4 1.2 0.7 3.6 2.3 0.6
HS3 2.2 6.3 2.6 1.9 4.9 0.7
HS37 1.8 0.9 2.4 1.8 2.1 1.8
HS23/36 1.7 4.2 3.0 1.4 1.8 4.2
HS21 1.6 0.5 0.6 1.8 2.5 1.1
HS19 1.5 2.0 3.1 1.5 0.9 0.5
HS12 1.3 1.0 0.0 2.1 0.5 0.7
HS58 1.3 0.8 0.0 2.0 1.0 0.1
HS15 1.1 1.4 3.4 1.2 0.9 0.4
HS18 0.9 0.4 0.1 1.1 2.1 0.2
HS53 0.7 3.3 1.2 0.7 0.6 0.1

Discussion

Since Penner first introduced the method [2], serotyping has been an important means of characterizing Campylobacter isolates. Here, using existing data, we estimate the distribution of C. jejuni serotypes both globally and by geographic region. Estimates were derived from 59 published studies on more than 21,000 cases of sporadic diarrhea. Based on these estimates, eight serotypes account for half of all isolates globally and three serotypes in particular (HS4 complex, HS2, and HS1/44), were consistently represented across all regions. Although this study is the first of its kind and a significant step forward in understanding the serotype distribution of C. jejuni infections, it is not without limitations. In fact, the estimates presented here are almost certainly imprecise. Data are sparse in every region of the world. No studies reporting extractable data were identified in South America and relatively few studies reported data from Africa and Asia, regions in which enteric infections contribute significantly to morbidity and mortality. The fact that some geographic regions are underrepresented may be partially due to the exclusion of non-English publications. However, the lack of data most probably reflects an absence of surveillance in these regions. With limited data from every region of the world, save Europe, the global estimates presented are biased towards those calculated in Europe. Even in Europe, from which 85% of the isolates in this study originated, there are insufficient data to draw conclusions regarding temporal changes in serotype distribution, geographic variation, and differences across demographic groups (e.g. travelers vs. non-travelers, or children vs. adults, etc.). The estimates presented here are also based on reports of sporadic cases of diarrhea. If an association between serotype and disease severity exists, selection bias has the potential to overestimate serotypes that result in manifest symptoms. Additionally, although a modest number of publications included in this review used a commercially available kit consisting of 25 antisera (Denka Seiken, Co), most studies relied upon custom reagents generated in-house or from another laboratory. The lack of standardized reagents calls into question the comparability of results across individual studies. Similarly, studies varied from one to the next with regards to which and how many serotypes were tested. These methodological differences undoubtedly influenced the estimates calculated here. Studies that did not screen a complete panel of antisera capable of detecting every serotype risked under-reporting certain serotypes, classifying them instead as non-typable. Finally, because C. jejuni is known to be subject to phase variation, assays such as Penner serotyping that depend upon the expression of CPS have the potential to underestimate the prevalence of any given Campylobacter serotype. If current efforts to develop a CPS-based vaccine are to succeed, robust surveillance systems are needed to address substantial gaps in knowledge surrounding the geographic distribution and temporal stability of serotypes. Future surveillance methods should also aim to reveal demographic differences in serotype distribution (e.g. age, traveler vs. resident populations) and disease/serotype associations (e.g. severity of disease, risk of developing chronic long-term health outcomes such as reactive arthritis, Guillain-Barré syndrome, or gastrointestinal disorders). Combined with investigations into the immunogenic properties of the differing CPS types, addressing these fundamental surveillance-related questions will be important in determining the composition of a future vaccine with regards to valency. Furthermore, the need for surveillance is greatest in developing regions, where diarrheal disease is most prevalent and available data are lacking. Diarrheal episodes amongst children in the developing world are believed to cause millions of deaths annually [11] and, although the estimates are derived from a relatively small number of studies, the proportion of diarrheal cases attributable to Campylobacter infection is believed to be high, ranging between 5–20% of cases [12]. Given this high incidence rate, the potential benefit of a future vaccine is greatest in the developing world. However, realizing this potential will require a significant surveillance effort to inform the development of a multi-valent vaccine that is well-matched to CPS types circulating in these regions. Implementation of such a surveillance program will require a commitment of time and resources that has not been seen to date. Although Penner typing was once considered the gold standard in C. jejuni serotyping, its use has been declining in recent years and, today, the technique is routinely performed by only a small number of reference laboratories in North American and Europe. The limited and declining use of Penner typing is due in part to the complexity and cost of generating polyclonal rabbit sera to the 47 C. jejuni type strains, as well as to the emergence and value of other typing schemes such as Multi Locus Sequence Typing (MLST) and the ever-decreasing cost of direct sequencing. For a surveillance system to be implemented that is sufficiently large enough to address the outstanding questions of CPS distribution and disease association, alternative methodologies for determining the CPS type of C. jejuni isolates will almost certainly need to be employed. Such alternative methodologies will need to be cost-effective, efficient with respect to time, readily transferred to most any laboratory, and have high throughput capacity. Recently, our group offered a method that meets these criteria. Sequencing has revealed that each Penner serotype is unique with regards to the genomic structure of the cassette of genes involved in the biosynthesis of the serodeterminant CPS [5]. We have designed specific PCR primers that exploit these genomic differences and reproduce the original Penner serotypes. The published system covered 14 serotypes, and has recently been extended to 47 serotypes, (Poly et al. in preparation). Standardization and distribution of this CPS typing system offers one potential alternative method for large-scale surveillance. In addition to the already noted benefits this molecular typing system might offer, such a system may also reduce or eliminate the substantial number of non-typable isolates found in previous studies, as the described PCR-based typing system it is not sensitive to CPS expression. Regardless of which method is ultimately used, informed design of a CPS-based vaccine will require a substantial investment of resources to sustain the intensive surveillance needed to move beyond the incomplete and static picture that this review is able to offer. Flow diagram of articles search, reviewed, and included in the systematic review. (DOCX) Click here for additional data file.
  65 in total

1.  Distribution of serotypes of Campylobacter jejuni and C. coli from Danish patients, poultry, cattle and swine.

Authors:  E M Nielsen; J Engberg; M Madsen
Journal:  FEMS Immunol Med Microbiol       Date:  1997-09

2.  Campylobacter jejuni isolated from retail poultry meat, bovine feces and bile, and human diarrheal samples in Japan: comparison of serotypes and genotypes.

Authors:  Shioko Saito; Jun Yatsuyanagi; Seizaburo Harata; Yuko Ito; Kunihiro Shinagawa; Noriyuki Suzuki; Ken-Ichi Amano; Katsuhiko Enomoto
Journal:  FEMS Immunol Med Microbiol       Date:  2005-08-01

3.  Detection of heat-stable antigens of Campylobacter jejuni and C. coli by direct agglutination and passive hemagglutination.

Authors:  A N Oza; R T Thwaites; D R A Wareing; F J Bolton; J A Frost
Journal:  J Clin Microbiol       Date:  2002-03       Impact factor: 5.948

4.  Evaluation of phenotypic and genotypic methods for subtyping Campylobacter jejuni isolates from humans, poultry, and cattle.

Authors:  E M Nielsen; J Engberg; V Fussing; L Petersen; C H Brogren; S L On
Journal:  J Clin Microbiol       Date:  2000-10       Impact factor: 5.948

5.  Most Campylobacter subtypes from sporadic infections can be found in retail poultry products and food animals.

Authors:  E M Nielsen; V Fussing; J Engberg; N L Nielsen; J Neimann
Journal:  Epidemiol Infect       Date:  2005-11-29       Impact factor: 2.451

6.  The serotype distribution of Campylobacter in patients with diarrhoea in Kuwait.

Authors:  E Sjögren; M Johny; B Kaijser
Journal:  FEMS Microbiol Lett       Date:  1989-01-15       Impact factor: 2.742

7.  Comparison of a blood-free medium and a filtration technique for the isolation of Campylobacter spp. from diarrhoeal stools of hospitalised patients in central Australia.

Authors:  M J Albert; W Tee; A Leach; V Asche; J L Penner
Journal:  J Med Microbiol       Date:  1992-09       Impact factor: 2.472

8.  Distribution of sero-biotypes of Campylobacter jejuni and C. coli isolated from paediatric patients.

Authors:  A J Lastovica; E Le Roux; R V Congi; J L Penner
Journal:  J Med Microbiol       Date:  1986-02       Impact factor: 2.472

9.  Comparison of Campylobacter jejuni genotypes from dairy cattle and human sources from the Matamata-Piako District of New Zealand.

Authors:  B J Gilpin; B Thorrold; P Scholes; R D Longhurst; M Devane; C Nicol; S Walker; B Robson; M Savill
Journal:  J Appl Microbiol       Date:  2008-08-18       Impact factor: 3.772

10.  Comparative genotyping of Campylobacter jejuni strains from patients with Guillain-Barré syndrome in Bangladesh.

Authors:  Zhahirul Islam; Alex van Belkum; Jaap A Wagenaar; Alison J Cody; Albert G de Boer; Helen Tabor; Bart C Jacobs; Kaisar A Talukder; Hubert P Endtz
Journal:  PLoS One       Date:  2009-09-30       Impact factor: 3.240

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  19 in total

Review 1.  Update on the burden of Campylobacter in developing countries.

Authors:  James A Platts-Mills; Margaret Kosek
Journal:  Curr Opin Infect Dis       Date:  2014-10       Impact factor: 4.915

Review 2.  A capsule conjugate vaccine approach to prevent diarrheal disease caused by Campylobacter jejuni.

Authors:  Alexander C Maue; Frédéric Poly; Patricia Guerry
Journal:  Hum Vaccin Immunother       Date:  2014-03-14       Impact factor: 3.452

3.  Capsular genotype and lipooligosaccharide locus class distribution in Campylobacter jejuni from young children with diarrhea and asymptomatic carriers in Bangladesh.

Authors:  Z Islam; S K Sarker; I Jahan; K S Farzana; D Ahmed; A S G Faruque; P Guerry; F Poly; A P Heikema; H P Endtz
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2017-12-21       Impact factor: 3.267

4.  Key Role of Capsular Polysaccharide in the Induction of Systemic Infection and Abortion by Hypervirulent Campylobacter jejuni.

Authors:  Orhan Sahin; Samantha A Terhorst; Eric R Burrough; Zhangqi Shen; Zuowei Wu; Lei Dai; Yizhi Tang; Paul J Plummer; Ju Ji; Michael J Yaeger; Qijing Zhang
Journal:  Infect Immun       Date:  2017-05-23       Impact factor: 3.441

Review 5.  Controlled Human Infection Models To Accelerate Vaccine Development.

Authors:  Robert K M Choy; A Louis Bourgeois; Christian F Ockenhouse; Richard I Walker; Rebecca L Sheets; Jorge Flores
Journal:  Clin Microbiol Rev       Date:  2022-07-06       Impact factor: 50.129

6.  Epidemiology of Campylobacter Infections among Children in Egypt.

Authors:  Rebecca Sainato; Atef ElGendy; Frédéric Poly; Janelle Kuroiwa; Patricia Guerry; Mark S Riddle; Chad K Porter
Journal:  Am J Trop Med Hyg       Date:  2017-12-14       Impact factor: 2.345

Review 7.  Association between Ras association domain family 1A promoter methylation and hepatocellular carcinoma: a meta-analysis.

Authors:  Ze-Hua Zhao; Yu-Chen Fan; Yang Yang; Kai Wang
Journal:  World J Gastroenterol       Date:  2013-11-07       Impact factor: 5.742

8.  Detection of Campylobacter jejuni in Lizard Faeces from Central Australia Using Quantitative PCR.

Authors:  Harriet Whiley; Ryan McLean; Kirstin Ross
Journal:  Pathogens       Date:  2016-12-23

9.  Updated Campylobacter jejuni Capsule PCR Multiplex Typing System and Its Application to Clinical Isolates from South and Southeast Asia.

Authors:  Frédéric Poly; Oralak Serichantalergs; Janelle Kuroiwa; Piyarat Pootong; Carl Mason; Patricia Guerry; Craig T Parker
Journal:  PLoS One       Date:  2015-12-02       Impact factor: 3.240

10.  Antibiotic resistance, molecular characterizations, and clinical manifestations of Campylobacteriosis at a military medical center in Hawaii from 2012-2016: a retrospective analysis.

Authors:  Evan C Ewers; Sarah K Anisowicz; Tomas M Ferguson; Scott E Seronello; Jason C Barnhill; Michael B Lustik; Willie Agee; Michael A Washington; Md A Nahid; Mark W Burnett; Ladaporn Bodhidatta; Apichai Srijan; Supaporn Rukasiri; Patcharawalai Wassanarungroj; Sirigade Ruekit; Panida Nobthai; Brett E Swierczewski; Woradee Lurchachaiwong; Oralak Serichantalergs; Viseth Ngauy
Journal:  Sci Rep       Date:  2018-08-06       Impact factor: 4.379

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