Literature DB >> 35215187

The Prevalence of Arcobacteraceae in Aquatic Environments: A Systematic Review and Meta-Analysis.

Igor Venâncio1, Ângelo Luís1,2, Fernanda Domingues1, Mónica Oleastro3, Luísa Pereira2,4,5, Susana Ferreira1.   

Abstract

Members of the family Arcobacteraceae are distributed widely in aquatic environments, and some of its species have been associated with human and animal illness. However, information about the diversity and distribution of Arcobacteraceae in different water bodies is still limited. In order to better characterize the health risk posed by members in the family Arcobacteraceae, a systematic review and meta-analysis-based method was used to investigate the prevalence of Arcobacteraceae species in aquatic environments based on available data published worldwide. The database search was performed using related keywords and considering studies up to February 2021. The pooled prevalence in aquatic environments was 69.2%, ranging from 0.6 to 99.9%. These bacteria have a wide geographical distribution, being found in diverse aquatic environments with the highest prevalence found in raw sewage and wastewater treatment plants (WWTP), followed by seawater, surface water, ground water, processing water from food processing plants and water for human consumption. Assessing the effectiveness of treatments in WWTP in eliminating this contamination, it was found that the wastewater treatment may not be efficient in the removal of Arcobacteraceae. Among the analyzed Arcobacteraceae species, Al. butzleri was the most frequently found species. These results highlight the high prevalence and distribution of Arcobacteraceae in different aquatic environments, suggesting a risk to human health. Further, it exposes the importance of identifying and managing the sources of contamination and taking preventive actions to reduce the burden of members of the Arcobacteraceae family.

Entities:  

Keywords:  Arcobacteraceae; aquatic environment; meta-analysis

Year:  2022        PMID: 35215187      PMCID: PMC8880612          DOI: 10.3390/pathogens11020244

Source DB:  PubMed          Journal:  Pathogens        ISSN: 2076-0817


1. Introduction

Proposed in 1991, the genus Arcobacter was included in the family Campylobacteracea, which comprised two more genera, Campylobacter and Sulfurospirillum [1,2]. Over the years, this genus has been expanded to include more species, currently comprising 34 species, of which 30 are validly published [3,4]. Since the proposal for the creation of the Arcobacter genus, it has been subjected to changes, and its taxonomical organization remains controversial. In 2017, after a comparative genomic analysis of the class Epsilonproteobacteria, a reclassification of the historically denominated Arcobacter genus as a new family denominated Arcobacteraceae was proposed to be included in the class Campylobacteria [5]. More recently, through phylogenetic and genomic analyses, Pérez-Cataluña et al., (2018) have suggested the reassessment of the taxonomy of genus in order to clarify the relationships among its species. The authors suggested the division of the genus Arcobacter in six genera and one candidate [6]. However, despite the reclassification in different genera having been validated [7,8], it has been refuted by considering Arcobacter as a taxon phenotypically-, phylogenetically- and genomically-coherent, while accepting the proposal of the family Arcobacteraceae as reasonable [9,10]. Arcobacteraceae is a family found in diverse habitats, environments and hosts, including animals, humans, foods and food-processing facilities, environmental and water sources such as underground water, surface water, sewage and sea water [11,12,13]. In fact, most of the species from this family have been first isolated from aquatic environments [14]. Few species from this family have been associated with animal and human disease, among which Aliarcobacter butzleri and Aliarcobacter cryaerophilus have been classified by the International Commission on Microbiological Specification for Food as a serious hazard to human [15]. Despite these two species being the most predominantly associated with human disease, infections with Aliarcobacter skirrowii, Aliarcobacter thereius, Malacobacter mytili and Aliarcobacter lanthieri have also been reported [16,17,18,19]. These species can cause intestinal diseases, with symptoms of diarrhea, abdominal pain, nausea, vomiting and fever, but also extraintestinal diseases, such as bacteraemia and peritonitis [20]. Arcobacters are described as water and food-borne bacteria, for which contaminated food or water are considered the probable route of transmission to human and animals [11]. Considering the wide distribution of Arcobacteraceae in environmental samples and water sources, the consumption or the direct contact of humans and animals with these bacteria may be seen as a relevant threat to public health. Thus, studies on Arcobacteraceae species in water sources can be useful to determine their role as a vehicle for the transmission of infectious agents, ecological characteristics and the potential zoonotic risk of these samples. Although studies on the prevalence of bacteria from this family in different aquatic environments can be found, there is no comprehensive data available on its prevalence to estimate the load. Therefore, the main aim of this work was to perform a systematic review followed by meta-analysis in order to investigate the prevalence of Arcobacteraceae in different water bodies based on data available worldwide.

2. Results and Discussion

2.1. Selection and Characteristics of Studies

After removing duplicate articles from the searches of the three selected databases, 613 articles were available for title and abstract screening. Of these, 117 were identified as potentially relevant, and 70 were eligible for inclusion after full-text review (Figure 1). The prevalence data was gathered from the articles considering the employment of molecular or cultural methods; when both methodologies were used, the overall value of prevalence was collected and applied for meta-analysis. When it was not possible to recover the full data required for the analysis, the work was not considered, and in the situation of examination of samples from different countries, the study was divided by country.
Figure 1

Flow diagram of database search, study selection and articles included in the meta-analysis.

2.2. Meta-Analysis Results on Overall Prevalence

The global prevalence of Arcobacteraceae in aquatic environments was investigated considering 70 studies (Figure 2), from which the pooled prevalence was 69.2% (0.692; 95% CI: 0.609–0.765), ranging from 0.6 to 99.9%. The heterogeneity among the studies was found significant, as demonstrated by the values of statistics of the studies included in this meta-analysis (I2 = 91.927%; tau2 = 1.693; p-value < 0.001). The publication bias was assessed by applying a funnel plot generated for the outcome, considering the Trim and Fill adjustment. The adjustment of the funnel plot to the absence of publication bias can be achieved with the inclusion of 8 additional studies (Supplementary Figure S1). The presence of publication bias was further assessed by using Egger’s regression test (Supplementary Table S2). The results of this test showed that there is evidence to reject the null hypothesis (p-value < 0.001), indicating that there is asymmetry in the funnel plot. Consequently, apparent publication bias exists in the studies included in this meta-analysis, which can be justified by the relevance of the publication of articles with positive results regarding the presence of Arcobacteraceae in aquatic environment samples.
Figure 2

Forest plot of the meta-analysis of prevalence of Arcobacteraceae in aquatic environments (in the references, 1 and 2 concern a division of the study by country).

2.3. Subgroup Analysis by Geographical Distribution

A subgroup analysis based on the country and continent of origin was taken (Table 1). Arcobacteraceae in aquatic environments have been reported in 26 countries among the 70 included papers. However, a small number of surveys in water were conducted in each of the 26 different countries considered, usually with a low number of samples (from three to 780, with a median number of 24 samples). Country-level estimates showed that the highest pooled prevalence of Arcobacteraceae can be found in Denmark, followed by Brazil, Australia and Korea, while the lowest prevalence was observed for the Netherlands and Cameroon.
Table 1

Meta-analysis of the prevalence of Arcobacteraceae according to countries, continents and income level.

Countries/Continent/Income Level n Pooled Prevalence95% CIQ-ValueI2tau2p-Value
Lower LimitUpper Limit
Countries
Australia20.9460.6070.9950.2000.655
Belgium20.6470.150.9511.21591.0846.0690.001
Brazil10.9620.2980.9990001
Cameroon10.00600.2480001
Canada40.9190.6860.983157.86698.16.5330
China60.880.5820.97522.11277.3887.142<0.001
Czech Republic50.4950.1640.838.13750.8390.8860.087
Denmark10.9640.5710.9980001
Ethiopia10.90.1250.9980001
Germany20.4580.0660.914.99379.9724.8890.025
India20.1940.0210.7283.52371.6112.7170.061
Iran10.6330.080.9720001
Italy60.4960.1840.81128.09582.2033.702<0.001
Japan10.2350.0910.4860001
Korea10.9440.2210.9990001
Malaysia20.1110.0120.560001
Nepal40.780.4080.94829.84389.9472.843<0.001
Netherlands10.10.0020.8750001
Portugal10.1250.0020.9030001
South Africa10.3330.0230.9140001
Spain100.8940.7420.96163.89785.9151.383<0.001
Thailand10.9380.4610.9960001
Turkey40.1240.0280.41331.32890.4241.365<0.001
UK20.9350.4430.9960.07000.792
USA90.8570.6690.94798.42491.8721.3610
Zambia10.1140.0060.7360001
Continent
Africa40.1920.0470.53617.35182.712.322<0.001
Asia220.4990.3360.663149.35785.9391.1430
Europe300.7270.5960.828193.06284.9791.8460
North America130.8710.7490.939348.86996.562.160
Oceania20.9450.6540.9940.2000.655
South America10.9620.350.9990001
Income level
Low10.90.1450.9980001
Lower middle80.3980.180.66654.12387.0671.211<0.001
Upper middle160.4720.2810.673116.08987.0791.950
High470.790.7020.858644.84592.8671.9560
Regarding the prevalence of Arcobacteraceae among continents, South America showed the highest pooled prevalence with 96.2% (0.962; 95% CI: 0.350–0.999), followed by Oceania, North America, Europe, Asia and finally Africa, with the lowest pooled prevalence value of 19.2% (0.192; 95% CI: 0.047–0.536) (Table 1). When analyzing prevalence data in subgroups categorized by the income level of the countries, the highest prevalence was presented by countries with a low-income level, at 90.0% (0.900; 95% CI: 0.145–0.998), followed by the countries of high-income level, at 79.0% (0.79; 95% CI: 0.702–0.858), of upper middle-income level, at 47.2% (0.472; 95% CI: 0.281–0.673) and lower middle, at 39.8% (0.398; 95% CI: 0.180–0.666). A high heterogeneity (I2 > 75%) was observed in the subgroup analysis by countries, except for Czech Republic and India, which showed a moderate heterogeneity. Additionally, the I2 statistics demonstrated a high heterogeneity (I2 > 75%) for all the continents. This parameter was not calculated when less than three studies were considered. Industrial pollution load, poor water and sewage treatment facilities, inadequate water pollution control laws and rapid urbanization rates have contributed to the increasing degradation of the aquatic environment in many developed and developing countries [21], which in turn may potentiate the emergence of genus Arcobacteraceae. The observed scenario regarding the prevalence according to the geographical location and level of economic development must be analyzed carefully, given the high heterogeneity between studies. The estimated prevalence by geographical location is clearly affected by the type of samples analyzed in each study, as all types of aquatic samples were included in this analysis, namely from wastewater treatment plants. Nonetheless, this analysis shows the global distribution of members of the family Arcobacteraceae in aquatic environments worldwide. Furthermore, several other parameters may influence the observed trend, such as the methods of detection used among studies and even the distribution of studies analyzed by countries. Indeed, the highest prevalence was observed for South America and for the low-income country included that considered only one study, with a low number of samples analyzed (twelve and four samples, respectively). Nonetheless, in general, more studies are globally needed to understand the prevalence of Arcobacteraceae worldwide.

2.4. Subgroup Analysis by Parameters of Samples Analysis

As the volume of the sample analyzed is a parameter that may clearly influence the prevalence of Arcobacteraceae, we further performed a subgroup analysis considering the sample size. For that, the studies were divided into four groups, regarding the amount of sample analyzed (Volume of sample 0–200 mL; 201–500 mL; 1 L and >1 L). When it was not possible to clearly define the volume of sample used in the analysis, the studies were excluded. Through the analysis of the results, it was observed that when the volume of the samples was up to 200 mL, there was a lower prevalence of detection of Arcobacteraceae (58.7%), but if the volume exceeded 201 mL, the estimated prevalence increased to at least 82.0% (Table 2).
Table 2

Meta-analysis of the prevalence of Arcobacteraceae according to the volume of sample analyzed.

Volume of Sample (mL) n Pooled Prevalence95% CIQ-ValueI2tau2p-Value
Lower LimitUpper Limit
0–200440.5870.4790.687445.84890.3561.312<0.001
201–50040.8200.4800.95832.09590.65310.209<0.001
100030.9030.6840.9768.35876.0690.517<0.001
>100070.8580.6660.94872.32491.7044.86<0.001
The amount of used sample is one of the factors that may influence the isolation or detection of bacteria. When a bacterium is present in a low number in environmental water samples, the straightforward way is to analyze larger sample volumes to increase the recovery; however, in turbid environmental water, for example, the high levels of background bacteria can interfere and prevent the isolation or detection of bacteria, such as described for thermotolerant campylobacters [22]. In the case of bacteria from the Arcobacteraceae family, the influence of the volume of sample has not been clarified, with only a limited number of the studies examining its presence using a quantitative approach. In addition to the volume of sample analyzed, the laboratory detection technique used will likely influence the reported prevalence. Herein, data was divided and analyzed considering five subgroups (Table 3). Considering the results, studies using molecular methodologies presented a higher estimated prevalence when compared with culture techniques. Furthermore, similar prevalence values were found for direct and after enrichment isolation, or for direct or after enrichment molecular detection, when excluding the metagenomic studies. The use of molecular methods allows a faster and more sensitive detection of bacteria, being able to detect both viable and non-viable cells, as well as viable but not cultivable cells. Nonetheless, this methodology has some drawbacks as well, associated with the fact that some molecular methodologies do not allow to distinguish dead from live cells or to recover bacterial isolates that can be used for further studies [14,23,24,25]. Several culture methods are used and the recovery of bacteria from this family can be associated with various factors related with the sample, but also with the disparity in the sensitivity and specificity of isolation methods [25], pointing out the need for a standard protocol for the isolation of Arcobacteraceae species from diverse samples [11,23,25]. Also, the use of a selective supplements may lead to lower recovery rates in environmental water samples, due to stressed or injured cells, which may be affected by using these compounds leading to a reduced recovery rate [25,26]. Despite this, when data from culture methodologies with or without an enrichment step are examined, prevalence estimates are close to 43.3% (0.433; 95% CI: 0.348–0.521) and 48.7% (0.487; 95% CI: 0.274–0.705), respectively. Considering the results related to direct molecular detection, a subgroup analysis was performed, dividing data into detection by metagenomic sequencing methodologies and detection methods by PCR techniques or other methods of nucleic acids amplification. When comparing these methodologies, the highest percentage of the detection of Arcobacteraceae species was achieved through direct sequencing of the samples (96.0%) instead of using conventional PCR identification techniques (68.8%). This may be associated with the fact that most of PCR methods are directed for some species-specific detection, which has intrinsic limitations beyond the ones associated with the methodology used.
Table 3

Meta-analysis of the prevalence of Arcobacteraceae according to the used detection method.

Methods n Pooled Prevalence95% CIQ-ValueI2tau2p-Value
Lower LimitUpper Limit
Culture—after enrichment370.4330.3480.521278.03887.0520.779<0.001
Culture—without enrichment40.4870.2740.7059.53568.5360.5430.023
Molecular after enrichment100.6310.4370.7939.80977.3920.924<0.001
Molecular direct300.8760.7690.937422.34993.1344.281<0.001
—metagenomic sequencing 160.960.8910.9867.954000.926
—PCR and other amplification methods 140.6880.4380.862277.22295.3114.058<0.001
Considering the diversity of protocols used for the isolation, detection and identification of Arcobacteraceae members, these data must be interpreted with caution.

2.5. Subgroup Analysis by Aquatic Source

A subgroup analysis based on the type of sample examined was performed, taking into consideration the wastewater treatment plants (WWTP) at three distinct stages: influent, treatment at any point and effluent. The results showed that the pooled prevalence of samples collected from raw sewage and WWTP were the ones with the highest prevalence values, followed by samples of seawater, surface water, ground water, processing water from food processing plants and, lastly, water classified as for human consumption with a prevalence of 3.2% (Table 4). The high values of pooled prevalence found in seawater and surface water may be a concern due to its potential recreational use, but also due to its possible influence on the food chain. Further, surface and groundwater are usually used as a water source in developing countries for multiple purposes, increasing the potential health risk. In turn, the lower values of the estimated prevalence of Arcobacteraceae species in processing water and drinking water may be associated with the potential inactivation effect of these bacteria by the chlorination process of the water [27], which may be ineffective [28,29].
Table 4

Meta-analysis of the prevalence of Arcobacteraceae according to sample sources.

Sources Samples n Pooled Prevalence95% CIQ-ValueI2tau2p-Value
Lower LimitUpper Limit
Seawater110.7800.6000.89393.28389.2801.453<0.001
Surface water280.6450.4850.778368.52592.6732.406<0.001
Ground water70.3960.1980.63631.5981.0071.176<0.001
Raw sewage200.9060.7860.962120.60884.2463.325<0.001
Processing Water90.3430.1410.62433.62476.2071.942<0.001
Drinking water70.0320.0140.0692.791000.835
WWTP
Influent WWTPTreatment WWTP110.9640.930.9823.556000.965
70.9310.7520.98424.55975.5692.703<0.001
Effluent WWTP90.8760.7740.93612.72537.130.3660.122
The presence of Arcobacteraceae in environmental waters indicates that it can survive and persist in those waters, which points to their potential to be waterborne pathogens. Furthermore, water can act as a contamination vehicle for these species, namely in the food chain [3]. Some studies suggest that fecal contamination may be responsible for introducing these bacteria into the water, being the presence of arcobacters correlated with a high level of fecal pollution [30]. In fact, among the outbreaks associated with arcobacters, some have suggested that the consumed water could have been contaminated by sewage [31,32]. However, the presence of high recovery rates of Arcobacteraceae in sea and surface waters may be due not only to the proximity of possible sources of fecal pollution, but also because several species have already been described as native to marine environments. In fact, many waterborne species of this family are found with high frequency in seawater or seafood from coastal waters [3,33]. The highest prevalence in this meta-analysis was found in the wastewater entering wastewater treatment plants (WWTP), which is in line with the reported prevalence in raw sewage. Thus, to assess the effectiveness of treatments in WWTP in eliminating this contamination, we followed with a subgroup analysis. Despite that a small decrease in the pooled prevalence of Arcobacteraceae through the WWTP was observed, a high prevalence continues to be observed, which could be seen as a potential health concern. Some authors suggest that these species are well suited to survive in adverse conditions, such as those in wastewater treatment plants, where their discharge into the environment is classified as a global problem [34]. Kristensen et al., 2020 described that the high relative abundance of arcobacters in the effluent may be associated with the removal of influent microorganisms in biological WWTPs. In the case of arcobacters, a large fraction of cells dispersed in the water phase prevails due to the reduced ability of these bacteria to flocculate and attach to the activated sludge flocs, preventing their effective removal [34]. This points to the need to reevaluate the treatment processes adopted or to even develop more effective methodologies to eliminate or potentially minimize the discharge of this emerging pathogen.

2.6. Subgroup Analysis by Arcobacteraceae Species

Considering that species from Arcobacteraceae family can be seen as waterborne pathogens, but also as naturally found in these environments, we proceeded with a subgroup analysis considering the different species. In this subgroup analysis, when a study presented prevalence data for each species determined by culture and molecular techniques, the global value or the highest value was collected for analysis. When evaluating the prevalence of the different species identified in the several categories of water samples, considering the ones that were identified in at least three studies, Al. butzleri was the species with the highest overall prevalence (58.3%), followed by Al. cryaerophilus (42.5%), Malaciobacter mytili (16.2%), Al. thereius (15.4%), Pseudarcobacter cloacae (14.8%), Pseudarcobacter defluvii (14.7%), Al. skirrowii (12.7%) and Arcobacter nitrofigilis (8.8%) (Table 5). Al. butzleri presented the highest pooled prevalence in most different water categories revealing the highest prevalence in seven of nine different water types, followed by Al. cryaerophilus, two of the species most associated with human diseases.
Table 5

Meta-analysis of the prevalence of Arcobacteraceae according to the sources of samples and species.

SpeciesDrinking Water, AnimalsDrinking Water, HumansSurface WaterSeawaterProcessing WaterRaw SewageInfluent WWTPTreatment WWTPEfluent WWTPOverall
n Pooled Prevalence (95% CI) n Pooled Prevalence (95% CI) n Pooled Prevalence (95% CI) n Pooled Prevalence (95% CI) n Pooled Prevalence (95% CI) n Pooled Prevalence (95% CI) n Pooled Prevalence (95% CI) n Pooled Prevalence (95% CI) n Pooled Prevalence (95% CI) n Pooled Prevalence (95% CI)
Aliarcobacter butzleri 30.090(0.019–0.342)20.029(0.004–0.195)180.503 (0.347–0.659)50.704 (0.389–0.898)30.090 (0.019–0.342)130.696 (0.502–0.838)40.954 (0.776–0.992)30.832 (0.485–0.963)30.830 (0.49–0.961)560.583 (0.483–0.675)
Aliarcobacter skirrowii 0-̵̵̵̵̶-0-̵̵̵̵̶-10.962 (0.597–0.998)10.042 (0.003–0.425)0-̵̵̵̵̶-10.033 (0.062–0.366)10.125 (0.031–0.386)30.071 (0.014–0.288)10.071 (0.004–0.577)80.127 (0.057–0.258)
Aliarcobacter cryaerophilus 20.079 (0.007–0.50)0-̵̵̵̵̶-40.465 (0.120–0.847)40.207 (0.049–0.570)20.089 (0.01–0.479)90.500 (0.251–0.749)30.524 (0.135–0.885)40.770 (0.369–0.950)20.796 (0.237–0.98)300.425 (0.285–0.579)
Aliarcobacter thereius 0-̵̵̵̵̶-0-̵̵̵̵̶-0-̵̵̵̵̶-0-̵̵̵̵̶-0-̵̵̵̵̶-10.167 (0.023–0.631)10.167 (0.023–0.631)30.167 (0.055–0.409)10.071 (0.004–0.577)60.154 (0.068–0.311)
Arcobacter nitrofigilis 0-̵̵̵̵̶-0-̵̵̵̵̶-0-̵̵̵̵̶-10.042 (0.003–0.425)0-̵̵̵̵̶-20.108 (0.027–0.346)10.167 (0.023–0.631)30.071 (0.014–0.288)30.071 (0.014–0.288)100.088 (0.041–0.178)
Malaciobacter mytili 0-̵̵̵̵̶-0-̵̵̵̵̶-0-̵̵̵̵̶-20.207 (0.062–0.506)0-̵̵̵̵̶-10.033 (0.001–0.475)0-̵̵̵̵̶-0-̵̵̵̵̶-0-̵̵̵̵̶-30.162 (0.052–0.405)
Pseudarcobacter cloacae 0-̵̵̵̵̶-0-̵̵̵̵̶-0-̵̵̵̵̶-10.091 (0.013–0.439) -̵̵̵̵̶-20.197 (0.054–0.512)10.333 (0.084–0.732)30.071 (0.014–0.288)10.071 (0.004–0.577)80.148 (0.072–0.281)
Pseudarcobacter defluvii 0-̵̵̵̵̶-0-̵̵̵̵̶-0-̵̵̵̵̶-10.042 (0.003–0.425)0-̵̵̵̵̶-20.150 (0.049–0.377)10.167 (0.023–0.631)30.167 (0.055–0.409)20.160 (0.031–0.530)90.147 (0.078–0.261)

-̵̵̵̵̶-: Corresponds to no value.

Çelik and Ünver (2005) suggested that Al. butzleri may present a stronger viability than other species in water, while presenting a competitive inhibitory effect in the population dynamic with other species [35]. Nonetheless, when analyzing these results, it should be considered that isolation and identification methods are needed for the analysis of the species considered, since the currently used methodologies may lead to an underestimation of the presence of some Arcobacteraceae species throughout the aquatic environment. This systematic review and meta-analysis on the prevalence of species from the Arcobacteraceae family provides a comprehensive analysis on its occurrence and wide distribution worldwide. The use of meta-analytic techniques to assess the prevalence of pathogens in the environment, while allowing to overcome some flaws of the traditional review, also has the advantage of considering the relative weight with which each individual study contributes to the final result. The lack of defined criteria for carrying out the systematic review and meta-analysis outside clinical settings represents, however, one of its weaknesses. In addition, this study also includes some limitations: (a) there was a lack of studies in some regions across the world, (b) the confounding effect of using samples from different aquatic environments in the global estimate of prevalence, (c) the low number of samples analyzed in some studies or (d) the diversity of the detection and identification methods with different sensitivities and specificities. Despite this, the results confirm that the species from this family have a wide geographical distribution, being present on diverse aquatic environments. The presence of the pathogenic species in these environments represents a public health risk, particularly when accessible to animals and humans. Thus, this study demonstrates the need for the monitoring and surveillance of water quality and safety, considering the presence of Arcobacteraceae species, as well as to assess to microbial risk. Further, some concern can be associated with Arcobacteraceae in wastewater plants effluents, highlighting the need for rapid action and review of bacterial elimination processes of this family, as effluents may eventually impact the receiving water body quality and in turn contaminate animals and food products that are easily accessible to humans.

3. Materials and Methods

3.1. Search Strategy and Study Selection

A comprehensive systematic literature search from databases ISI Web of Science, PubMed and Scopus were accessed for studies in February 2021 using the following search strategy: Arcobacter AND (Water OR groundwater OR seawater OR influent OR Effluent OR ambient OR sewage OR wastewater). This systematic review was performed following the PRISMA protocol. The recovered records were exported to Rayyan QCRI (https://rayyan.qcri.org/welcome (accessed on 31 January 2022)) for the initial screening. Thereafter, all the studies from the search were independently analyzed by the title, abstract and selected full-text by two reviewers, and a third reviewer arbitrated any divergence. Full-text articles published or in press were collected, while reviews, conference abstracts and chapter books were excluded. Only studies in English, Portuguese and Spanish were accessed for inclusion. Articles were considered for full-text review if (1) the full-text article could be retrieved, (2) it reported primary data or (3) the article reported isolation by culture or detection by molecular techniques of Arcobacteraceae or their species in water samples.

3.2. Data Extraction and Statistical Analyses

After a careful analysis, the following data were extracted and summarized from each included article: first author’s last name, year of publication, country, continent, income level, total analyzed samples, source of the samples, detection technique, volume of water used for analysis, species identified/detected and prevalence or number of positive samples. Meta-analysis of the prevalence of Arcobacteraceae was performed using Comprehensive Meta-Analysis Software v.2.0 (https://www.meta-analysis.com/ (accessed on 31 January 2022)). Forest plots were generated to show the study-specific effect sizes, with the pooled prevalence (PP) considered with a 95% confidence interval (CI), using the random-effects model. Heterogeneity among studies was measured by applying the I2 statistics. Values close to 0% indicate no heterogeneity, whilst values close to 25%, 50% and 75% correspond to a low, moderate and high heterogeneity, respectively. p-values correspond to the heterogeneities between studies from a Chi-squared test of the null hypothesis that there is no heterogeneity. The potential impact of publication bias on the present meta-analysis was assessed by three different analyses: funnel plot [36,37]; Egger’s regression test [38,39] and Duval and Tweedie’s Trim and Fill approach [40,41]. This allowed us to obtain the best estimate of the unbiased pooled effect size, creating a funnel plot including both the observed studies (shown as blue circles) and the necessary imputed studies (shown as red circles) to obtain the absence of bias. A sensitivity analysis was performed by removing each study at a time to evaluate the stability of the results. Subgroup analysis was performed on the outcome under the study per countries, continents (Turkey was included in Asia), income level, volume of analyzed water, laboratory detection technique, Arcobacteraceae species and water types.
  86 in total

1.  Tracing enteric pathogen contamination in sub-Saharan African groundwater.

Authors:  J P R Sorensen; D J Lapworth; D S Read; D C W Nkhuwa; R A Bell; M Chibesa; M Chirwa; J Kabika; M Liemisa; S Pedley
Journal:  Sci Total Environ       Date:  2015-09-28       Impact factor: 7.963

2.  Waterborne outbreak of acute gastroenteritis in a costal area in Slovenia in June and July 2008.

Authors:  B Kopilović; V Ucakar; N Koren; M Krek; Alenka Kraigher
Journal:  Euro Surveill       Date:  2008-08-21

3.  Application of MALDI-TOF MS for the subtyping of Arcobacter butzleri strains and comparison with their MLST and PFGE types.

Authors:  Federica Giacometti; Silvia Piva; Katleen Vranckx; Katrien De Bruyne; Ilenia Drigo; Alex Lucchi; Gerardo Manfreda; Andrea Serraino
Journal:  Int J Food Microbiol       Date:  2018-04-16       Impact factor: 5.277

4.  Isolation and Identification of Arcobacter spp. by Multiplex PCR from Water Sources in Kars Region.

Authors:  Elif Çelik; Ahmet Ünver
Journal:  Curr Microbiol       Date:  2015-07-26       Impact factor: 2.188

5.  Prevalence and distribution of Arcobacter species in various sources in Turkey and molecular analysis of isolated strains by ERIC-PCR.

Authors:  F Aydin; K S Gümüşsoy; H I Atabay; T Iça; S Abay
Journal:  J Appl Microbiol       Date:  2007-07       Impact factor: 3.772

6.  Neighborhood diversity of potentially pathogenic bacteria in drinking water from the city of Maroua, Cameroon.

Authors:  Jessica Healy-Profitós; Seungjun Lee; Arabi Mouhaman; Rebecca Garabed; Mark Moritz; Barbara Piperata; Jiyoung Lee
Journal:  J Water Health       Date:  2016-06       Impact factor: 1.744

7.  Highly heterogeneous temporal dynamics in the abundance and diversity of the emerging pathogens Arcobacter at an urban beach.

Authors:  Richard L Carney; Mark V Brown; Nachshon Siboni; Jean-Baptiste Raina; Tim Kahlke; Simon M Mitrovic; Justin R Seymour
Journal:  Water Res       Date:  2019-12-18       Impact factor: 11.236

8.  Occurrence and genetic diversity of Arcobacter butzleri in an artisanal dairy plant in Italy.

Authors:  Federica Giacometti; Alex Lucchi; Gerardo Manfreda; Daniela Florio; Renato Giulio Zanoni; Andrea Serraino
Journal:  Appl Environ Microbiol       Date:  2013-08-23       Impact factor: 4.792

9.  Assessment of Fecal Indicator Bacteria and Potential Pathogen Co-Occurrence at a Shellfish Growing Area.

Authors:  Andrew K Leight; Byron C Crump; Raleigh R Hood
Journal:  Front Microbiol       Date:  2018-03-14       Impact factor: 5.640

10.  Massive microbiological groundwater contamination associated with a waterborne outbreak in Lake Erie, South Bass Island, Ohio.

Authors:  Theng-Theng Fong; Linda S Mansfield; David L Wilson; David J Schwab; Stephanie L Molloy; Joan B Rose
Journal:  Environ Health Perspect       Date:  2007-02-06       Impact factor: 9.031

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1.  Polyaniline-Derived Nitrogen-Containing Carbon Nanostructures with Different Morphologies as Anode Modifier in Microbial Fuel Cells.

Authors:  Irina Lascu; Claudiu Locovei; Corina Bradu; Cristina Gheorghiu; Ana Maria Tanase; Anca Dumitru
Journal:  Int J Mol Sci       Date:  2022-09-23       Impact factor: 6.208

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