Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 + 3676 word(s) 3676 2021-11-23 09:57:54 |
2 Done -35 word(s) 3641 2021-12-30 02:24:04 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Schellhorn, H. Bacterial Markers for Fecal Pollution Detection. Encyclopedia. Available online: https://encyclopedia.pub/entry/17631 (accessed on 24 April 2024).
Schellhorn H. Bacterial Markers for Fecal Pollution Detection. Encyclopedia. Available at: https://encyclopedia.pub/entry/17631. Accessed April 24, 2024.
Schellhorn, Herb. "Bacterial Markers for Fecal Pollution Detection" Encyclopedia, https://encyclopedia.pub/entry/17631 (accessed April 24, 2024).
Schellhorn, H. (2021, December 29). Bacterial Markers for Fecal Pollution Detection. In Encyclopedia. https://encyclopedia.pub/entry/17631
Schellhorn, Herb. "Bacterial Markers for Fecal Pollution Detection." Encyclopedia. Web. 29 December, 2021.
Bacterial Markers for Fecal Pollution Detection
Edit

The goals of fecal pollution detection include fecal waste source tracking and identifying the presence of pathogens, therefore assessing potential health risks. 

Bacterial Coliforms Bacteroides Enterococcus Escherichia coli source tracking

1. Bacterial Markers

One major purpose of fecal pollution detection is to identify the presence of pathogens to identify the fecal waste source and potential health risks. With the realization that waterborne transmission of bacterial diseases was a public health concern in the 18th century, governments established sanitary systems to monitor drinking water safety and build water treatment facilities [1]. A question arises—should one monitor waterborne pathogens directly or employ proxy indicators? There are many bacterial, protozoan, and viral enteric pathogens that can cause diseases. Their methods of detection are often laborious, time-consuming, and require specialized expertise and biosafe laboratory settings. Pathogens in environmental water are sporadic and sparse, making it difficult or costly to measure these pathogens [2]. In addition, waterborne pathogens in the environment are less dangerous at low concentrations compared to those in GI tracts, but their laboratory enumeration often involves concentration from large volumes of water samples; therefore, these concentrated pathogens may cause severe human diseases during their measurement [3][4].
Water quality monitoring to detect fecal pollution can employ biological fecal indicators to proxy many potential pathogens. A typical fecal indicator should fulfill the following criteria [3][2][5]:
(1) It should be detected only in feces-polluted environments and should not be detected in non-fecal-polluted environments; i.e., it should have a high association with fecal pollution with little or no background noise;
(2) It should be detectable in the same host as the pathogens, and its abundance should reflect pathogen abundance both inside and outside the host; i.e., it should have tight correlations with pathogens/diseases;
(3) It should be detectable in the host intestine, feces, and also fecal-polluted environmental waters so that it can be assessed using inexpensive and simple methods; i.e., it should have good detection sensitivity;
(4) It should not multiply outside the host intestine but should be viable or in a detectable form for some time comparable to fecal pathogens;
(5) It should be safe to measure for field and lab workers, not causing severe human diseases.
The value of common fecal indicator bacteria (FIB) is that they occur widely in the feces of birds, mammals, and humans, posing a robust way to detect fecal pollution. However, lack of host specificity is also a problem when determining the specific source of fecal pollution, i.e., fecal pollution source tracking. Advances in the field of microbial source tracking have now provided new fecal indicators that can be used to identify specific fecal pollution sources (e.g., human sewage). If a proxy is used to detect human fecal pollution, ideally it should be exclusively of human sources and not be found in animals. Here researchers introduce well-validated bacterial, viral and molecular indicators, emphasizing their association with pathogens, their presence in fecal wastes, their host specificity, their persistence in the environment, and their pathogenicity.
Host specificity is one of the most critical criteria for any fecal indicator because it determines whether a given fecal indicator can be used to identify the specific sources of fecal pollution, i.e., fecal source tracking [6]. Accurate source tracking helps water quality regulators to locate pollution sources, such as fecal pollution from a nearby WWTP or an animal farm. Host specificity can be readily assessed by the proportion of the false-positive results detected in nontarget fecal pollution sources [7]. Fecal indicators with absolute human specificity must be detected only in humans and must not be detectable in any animals, whereas those of poor human specificity may also be detected in animals, plants, or environments without association with fecal pollution. Livestock in a farm/slaughterhouse [8][9] and wild animals in forests/natural reserves [10] can also be sources of fecal pollution and pathogens. Thus, fecal indicators specific to one animal host are worth noticing because they help identify the species of animal hosts and the possible source locations.
Sensitivity is another critical criterion which is evaluated by the positive proportions in target fecal pollution sources. Fecal indicators of perfect sensitivity should be detectable in all target fecal pollution sources, whereas those of poor sensitivity may be detectable in a minor proportion of target fecal pollution sources in situations where pollution is high. Sensitivity measurement is, of course, affected by fecal indicator concentrations. Even fecal indicators of high sensitivity may be undetectable in target samples if they are diluted or have undergone significant losses through sample processing steps, causing false negatives.

2. Coliforms

Coliform bacteria, or total coliforms or simply coliforms, are a group of Gram-negative, facultatively anaerobic, non-spore-forming and rod-shaped bacteria that can ferment lactose to acid and gas at ~37 °C within 48 h, constituting ~10% of gut microorganisms [11]. Traditionally, total coliforms included four closely related genera within the family Enterobacteriaceae: Escherichia, Enterobacter, Klebsiella and Citrobacter [12]. But today, some species of over 19 bacterial genera (e.g., Hafnia, Serratia and Raoultella) can be classified as coliforms based on the phenotypic characteristics above [13]. Total coliforms are used to evaluate water treatment efficacy in fecal wastes removal and assess the integrity of water distribution systems [14] because they mainly originate from the GI tracts of humans and warm-blooded animals (i.e., mammals and birds), and thus, their presence in water can indicate possible fecal pollution. In 1975, the U.S. EPA issued the National Primary Drinking Water Regulations, which allowed a maximum of 5% drinking water samples positive for total coliforms tested in a month [15]. Then, in 1989, the U.S. EPA published the first Total Coliform Rule, which supplemented a Maximum Contaminant Level Goal of zero total coliforms in nationwide drinking waters [16]. To date, total coliforms are still routinely monitored in drinking water.
The recognition of free-living coliforms in non-enteric environments, such as freshwater, soil and vegetation, that do not have a history associated with fecal pollution [17][18] has cast doubt on the exclusive association between total coliforms and fecal pollution. For example, Klebsiella variicola is a member of total coliforms but is typically a plant endosymbiont [18]. Thus, not all members of total coliforms are suitable indicators of fecal pollution, and presence of total coliforms in drinking water does not necessarily indicate fecal pollution [14]. To overcome this issue, fecal coliforms, which are defined as coliforms originating from the intestines of warm-blooded animals capable of fermenting lactose at 44.5–45.5 °C, are proposed as a monitoring target [19]. As a subgroup of total coliforms, fecal coliforms have better associations with fecal pollution because the non-fecal-origin part is excluded [20]. Fecal coliforms detected in aquafarm harvesting areas such as an oyster bed are indicative of fecal pollution, causing ecological issues and economic losses [21]. Note that neither total coliform nor fecal coliform is a natural taxon but a method-based bacteria category for convenience. Researchers now understand that even within the category of fecal coliforms, some are not exclusively of fecal origin, hence the transition to Escherichia coli as a better fecal indicator. Among fecal coliforms, E. coli is the dominant species isolated from water (>95%) and is the most frequently used indicator [22].
Since coliforms can be cultured with ease, there are culture-based and culture-independent methods to detect and enumerate coliforms in water. Frequently used culture-based enumeration methods include the (i) classical plate count on violet-red-bile-lactose agar medium [23] or chromogenic media based on the activities of β-D-galactosidase (of coliforms) and β-glucuronidase (of E. coli) [24], (ii) most probable number procedure in lauryl tryptose broth [25] and IDEXX systems, (iii) membrane filtration in selective M-Endo medium [26] and (iv) lateral-flow immune-chromatographic assay using antibodies recognizing coliform genera [27]. Culture-independent methods include (i) real-time PCR targeting the lacZ gene of coliforms [28][29], (ii) fluorescence-based DNA microarray probing E. coli [30], (iii) flow cytometry [31] and (iv) next-generation sequencing or metagenomics that profile all microorganisms, including total/fecal coliforms [32].
Except for a few strains such as E. coli O157:H7, fecal coliforms are generally not considered to be pathogenic. However, drinking water free of coliforms or not exceeding coliform regulatory thresholds is not necessarily safe to drink. Seven waterborne disease outbreaks, affecting more than 3000 people across 5 American states between 1991 and 1992, occurred in drinking water not exceeding the 1989 Maximum Contaminant Levels [33]. Protozoal parasites Giardia and Cryptosporidium were identified as the etiological agents. Therefore, coliforms should not be the sole indicator for successful drinking water quality assessment.

3. Escherichia coli

Escherichia coli is used as a fecal indicator as part of drinking water regulations [1]. The U.S. EPA added E. coli to the water monitoring and assessment list in 1985 [34]. According to an early investigation by the U.S. EPA, E. coli has the highest correlation to swimming-associated diseases at freshwater beaches on the east coast of the U.S. [35]. First, it shows a strong association with fecal pollution, as it is found in all feces of warm-blooded animals and a few reptiles at high concentrations [1][36], and remains at detectable levels in waters subject to animal fecal pollution, such as sewage, rivers, lakes, groundwater and coastal areas [37][38]. In addition, E. coli is a facultative anaerobe and is easy to culture, so it can be readily measured using both culture-based and culture-independent methods. Second, E. coli is highly associated with a fecal origin and is less likely to be present in natural environments free of animal feces. It was believed to be of exclusively fecal origin when selected as a fecal indicator, which, however, is no longer accurate with the recognition of “naturalized” E. coli, which persists and may replicate in non-enteric/non-fecal environments such as soil, sediment, beaches and aquatic plants [39][40]. “Naturalized” E. coli may not come from a recent fecal input, though it is still believed to have diverged from E. coli of fecal origins.
It is important to distinguish between fecal pollution caused by human wastes and that caused by animals, because human fecal pollution is generally associated with high health risks from human-specific pathogens and high loads of antibiotics and ARBs. One major limitation of E. coli as a fecal indicator lies in its poor specificity to human feces. Despite the substantial genetic diversity of E. coli fecal isolates, epidemiological studies have identified weak associations between a particular E. coli clone and a given host [41][42]. For example, a B1 subgroup clone that exhibits the hly virulence gene is unique to animals [41], and a B2 subgroup VIII, O81 serotype clone is specific to humans [43]. E. coli strains showing stringent host specificity may be specialized candidates for fecal source tracking indicators. Still, most E. coli strains discovered in human fecal samples are not specific to humans, causing difficulties in fecal pollution source tracking.
E. coli was initially believed to have poor survival and to be unlikely to multiply after being released into the environment through deposition of fecal wastes because of the environment being so different from animal gastrointestinal tracts and because of environmental stresses such as insufficient organic matter [44], sunlight inactivation and high salinity [45]. However, prolonged E. coli survival can be found at low temperatures [46], and enhanced E. coli replication is seen at higher temperatures, where relatively sufficient nutrients are likely to support its regrowth [47]. Lake sediments rich in organic contents also favor the survival of E. coli at lower temperatures [48]. When grown as biofilms, E. coli has a significantly higher tolerance against chlorine than planktonic E. coli [49]. In conclusion, the persistence of E. coli is greatly affected by environmental conditions.
Changes in climate, such as an increase in temperature and rainfall, may cause fluctuations of E. coli counts in waters [50][51][52]. A rainfall event can result in up to a three-fold increase of E. coli counts in recreational waters compared to before rainfall, and this increase can persist for up to 12 h [52][53]. After a rainfall event, increases in E. coli counts may occur due to the “first flush” from stormwater drainage or agricultural waste runoff coming along with the flow [53][54]. Furthermore, bacteria including E. coli tend to form flocs, adhere to rocks and other particles, then settle down to the sediment of freshwater ecosystems. A heavy rain or storm event may resuspend these bacterial cells from sediments, leading to a 30–37 times higher bacterial load in water [55][56]. Thus, climate and meteorological parameters should be monitored before and during water sample collection for E. coli testing to help interpret data.
Most strains of E. coli are commensal or symbiotic to their animal hosts in the gastrointestinal tracks [57]. For example, indigenous gut E. coli strains can be highly competitive for proline, and their depletion of proline helps inhibit the colonization of pathogenic E. coli strain O157:H7 [58]. These non-pathogenic strains are considered safe fecal indicators (categorized as biosafety Level I organisms in the U.S.) and can be enumerated by similar methods, as described for coliforms in environmental waters. In addition, there are specialized methods that only detect certain E. coli strains, such as ATCC 47,076, in drinking water [59]. Pathogenic E. coli strains, including the aforementioned O157, a Shiga toxin-producing E. coli (STEC) serotype categorized as a biosafety Level II organism, caused 5441 infections across the United States in 1996 [60]. The previous study [61] identified a nine base-pair conserved DNA sequence insertion located in the ybiX gene that is unique to O157 strains and can be used for O157 quantification by qPCR. Pathogenic E. coli strains may have better correlations with diseases, and therefore, their enumeration can be a means to assess potential health risks to the public.

4. Enterococcus

Enterococci share traits with E. coli that are useful for environmental monitoring. First, they both are facultative anaerobic bacteria detected abundantly in the GI tracts of humans and many animals and are shed in feces at high concentrations. Furthermore, both are easy to culture, both have generally low pathogenicity (at Biosafety Level 1, except for a few species), both have abundances highly associated with GI diseases, and both are subsequently common indicators for water quality monitoring, fecal pollution detection and health risk assessment by culture-based and culture-independent methods [1]. Apart from in humans, enterococci have been detected in insects (e.g., drosophila), domestic animals (e.g., cattle and cats), plants (e.g., forage crops) [62][63][64], as well as non-enteric environments (e.g., soil and beach sand) [1]. These discoveries indicated a limited host specificity of enterococci and possible origins other than feces.
Both E. coli and enterococci have long been used as FIB because of their association with waterborne diseases [65]. Two epidemiological studies recognized enterococci as good indicators of GI diseases among swimmers at both freshwater and marine beaches [66][67]. Enterococci have been the sole recommended FIB by U.S. EPA for marine waters since 1986 [68] because they have higher survival in salt water than coliforms (including E. coli) and are thought to be more tightly associated with human pathogens [69][70]. However, using enterococci as fecal indicators has been criticized as well because enterococci are not exclusively of fecal origin and have limited host specificity, as aforementioned. These characteristics may hinder accurate fecal pollution source tracking because non-fecal-origin enterococci may not be associated with health risks, and animal-specific enterococci-associated pathogens may have variable survival strategies in the environment and health risks from human-specific pathogens [71].
The persistence of enterococci in the non-enteric environment is robust, as enterococci can survive across a wide range of temperatures (from 10 to 45 °C) [1], are intrinsically resistant to multiple antibiotics (e.g., ampicillin, cephalosporin and kanamycin) [72], and can survive high salinity (6.5% w/w NaCl) and alkaline (up to pH 10) [73]. Enterococcus faecium and Enterococcus faecalis are generally the two most abundant species of Enterococcus found in human fecal microbiota [74]. They generally have a longer persistence in marine water than E. coli [75][76]. They tend to adhere to biotic or abiotic surfaces to form biofilms, protecting them from environmental stresses such as temperature fluctuations, UV radiation, predation, and wave action [77]. Heavy rain or a storm can disrupt these biofilms and release the enterococci into the water column [78]. In environmental waters, adverse conditions, such as solar radiation, starvation, and low temperatures, may decrease enterococci culturability and induce them to enter the VBNC state [79][80]. VBNC cells are unlikely to be detected via culture-based methods.
Epidemiological studies support an association between enterococci from human fecal sources (e.g., urban sewage) and waterborne diseases in recreational waters [66][81][82]. Higher enterococci densities are associated with an increasing occurrence of GI illnesses among beachgoers at beaches impacted by treated sewage effluent [66]. In addition, human pathogens such as Giardia and Salmonella are found in higher densities and positively correlated with enterococci concentrations in recreational waters impacted by sewage effluent [81][82]. Along with human fecal pollution, exposure to animal feces poses health threats. Globally, one-third of childrens’ deaths due to GI illnesses in 2015 were caused by pathogens that are found in animal feces [83]. It is predicted that enterococci densities as low as 35 CFUs/100 mL from cattle manure pose health risks [71]. Thus, enterococci levels are indicative of general health risks from both human and animal fecal pollution. However, without associated source tracking information, it is difficult to unambiguously identify the fecal hosts/sources of enterococci.

5. Clostridium perfringens

Clostridium perfringens is a Gram-positive, spore-forming, biofilm-forming, anaerobic and pathogenic species (at biosafety Level II) associated with feces [84]. It is among the first fecal indicators in aquatic environments [85]. C. perfringens can be found in the gut of fish and warm-blooded animals, such as pigs and ducks [86][87][88], as well as in some non-enteric environments, such as soil, streams and marine sediments [89][90]. Despite having limited host specificity, C. perfringens can be present in higher abundances in human feces than animal feces. As a pathogenic species, its presence itself indicates possible health risks to humans and animals.
Species of the genus Clostridium are obligate anaerobes and cannot multiply in environmental waters. Spores of C. perfringens are coated by a thick peptidoglycan cortex structure that provides resistance against environmental stresses such as chlorination, heat and UV radiation and resistance against toxins in industrial wastes [91]; thus, C. perfringens spores can survive longer in polluted waters than other FIB, especially in freshwaters [91][92]. The inability to multiply in non-enteric environments and the prolonged environmental viability of its spores make C. perfringens a better indicator of long-term or accumulative fecal pollution. Criticisms against the usage of C. perfringens also focus on its prolonged viability and wide distribution in aquatic environments. Its spores can be detected in places far from the pollution input site, indicative of either remote or old fecal pollution [93]. Besides, its abundance does not always correlate with abundances of other FIB [89]. Hence, combined usage of C. perfringens and other FIB may better predict pathogens.
Detection and quantification of C. perfringens can be conducted by culture-based and culture-independent methods. It can be isolated from water samples by the membrane filtration and Rapid Fung double tube methods [94], then cultivated in anaerobic chambers at 44–46 °C [95]. Available media include mCP medium, tryptose-sulfite-cycloserine agar, and tryptone-sulfite-neomycin agar [96][97]. Rapid and culture-independent enumeration methods include qPCR targeting the cpn60 gene [98], DNA sequencing targeting 16S rDNA genes or the whole genome, and the newly developed Saltatory Rolling Circle Amplification targeting the cpa gene, which is conducted at a constant temperature and does not require a thermocycler or gel electrophoresis [99].

6. Bacteroides

Species of genus Bacteroides are frequently used fecal indicators for source tracking purposes. They are low-pathogenic indicators (biosafety Level I) with promising host specificity compared to facultative anaerobic FIB [100]. Bacteroides are obligate anaerobes of gut origins, unlikely to multiply in a non-enteric environment, and are present at significantly higher densities in the GI tracts and feces of humans than coliforms or enterococci [7]. Bacteroides can be found in warm-blooded animal hosts such as humans, dogs, pigs, and also fish, which are cold-blooded [101][102][103]. Unlike coliforms or enterococci, Bacteroides spp. isolated from humans and some animal hosts are unique to one or a group of hosts [104].
Unlike facultative anaerobic FIB, the isolation and cultivation of Bacteroides cells require anoxic chambers, which is costly, time-consuming and labor-intensive [105]. Bacteroides can grow at 37 °C in many selective media, such as Brain Heart Infusion medium, Bacteroides Bile Esculin agar, and Blood Hemin Vitamin K medium containing antibiotics [105][106][107]. In most applications, Bacteroides grows into visible colonies on plates within 24 h, and colonies will be large enough to enumerate in 36 and 48 h. Some Bacteroides species can be identified to the species level within four hours by a few biochemical tests, such as the API ZYM system that detects activities of Bacteroides-specific enzymes [108].
The use of biological molecular markers bypasses the difficulties of anaerobic cultivation and enables the routine detection of Bacteroides spp. The aforementioned host-specific 16S rDNA markers can be used to detect and quantify Bacteroides in environmental samples and thus enable source tracking of the fecal pollution. Among human-specific Bacteroides 16S rDNA sequences, the region to be amplified by the primer set HF183F (Human Fecal 183 forward primer) and Bac708R (reverse primer) ranks among the most recognized markers to assess human fecal pollution and to discriminate it from animal fecal pollution because of its high sensitivity and specificity to humans [109]. Although HF183 fluorescent probe-based assays may sometimes cross-react with animal feces, its concentration in human feces can be 1000-fold more, or higher, than in animal feces [110]. In 2012, the U.S. EPA recommended an illness-based recreational water quality threshold of 32 illnesses per 1000 primary contact recreators using enterococci or E. coli [68]. In 2020, as Bacteroides HF183 becomes widely used, a threshold of 525 HF183 copies/100 mL recreational water was proposed by Boehm and Soller [111]. Apart from 16S rDNA sequences, there are other Bacteroides human molecular markers, such as genes encoding a hypothetical protein of Bacteroidales-like cell surfaces [112], which showed a >97% human specificity.
Obligate anaerobes such as Bacteroides cannot grow or multiply in environmental waters and have shorter survival periods than aerobes, facultative anaerobes, or viruses [7]. This property can provide a time progression of fecal pollution in environmental waters after Bacteroides spp. are released [113]. Molecular markers of both viable and non-viable cells can be detected using qPCR and DNA sequencing, so that they are less affected by cell states [114]. For example, the portion of culturable enterococci and E. coli in unfiltered freshwater can be reduced by 90% within 1.2 h and 1.4 h in sunlight, whereas it takes more than 6 h for the same reduction for HF183 and human polyomavirus [110].

References

  1. Edberg, S.C.; Rice, E.W.; Karlin, R.J.; Allen, M.J. Escherichia coli: The best biological drinking water indicator for public health protection. Symp. Ser. Soc. Appl. Microbiol. 2000, 88, 106S–116S.
  2. Cabral, J.P. Water microbiology. Bacterial pathogens and water. Int. J. Environ. Res. Public Health 2010, 7, 3657–3703.
  3. Glassmeyer, S.T.; Furlong, E.T.; Kolpin, D.W.; Cahill, J.D.; Zaugg, S.D.; Werner, S.L.; Meyer, M.T.; Kryak, D.D. Transport of chemical and microbial compounds from known wastewater discharges: Potential for use as indicators of human fecal contamination. Environ. Sci. Technol. 2005, 39, 5157–5169.
  4. Fuhrmeister, E.R.; Ercumen, A.; Pickering, A.J.; Jeanis, K.M.; Ahmed, M.; Brown, S.; Arnold, B.F.; Hubbard, A.E.; Alam, M.; Sen, D.; et al. Predictors of Enteric Pathogens in the Domestic Environment from Human and Animal Sources in Rural Bangladesh. Environ. Sci. Technol. 2019, 53, 10023–10033.
  5. Rochelle-Newall, E.; Nguyen, T.M.; Le, T.P.; Sengtaheuanghoung, O.; Ribolzi, O. A short review of fecal indicator bacteria in tropical aquatic ecosystems: Knowledge gaps and future directions. Front. Microbiol. 2015, 6, 308.
  6. Ahmed, W.; Gyawali, P.; Feng, S.; McLellan, S.L. Host Specificity and Sensitivity of Established and Novel Sewage-Associated Marker Genes in Human and Nonhuman Fecal Samples. Appl. Environ. Microbiol. 2019, 85, e00641-19.
  7. Tran, N.H.; Gin, K.Y.; Ngo, H.H. Fecal pollution source tracking toolbox for identification, evaluation and characterization of fecal contamination in receiving urban surface waters and groundwater. Sci. Total Environ. 2015, 538, 38–57.
  8. Ahmed, W.; Goonetilleke, A.; Gardner, T. Human and bovine adenoviruses for the detection of source-specific fecal pollution in coastal waters in Australia. Water Res. 2010, 44, 4662–4673.
  9. Hundesa, A.; Bofill-Mas, S.; Maluquer de Motes, C.; Rodriguez-Manzano, J.; Bach, A.; Casas, M.; Girones, R. Development of a quantitative PCR assay for the quantitation of bovine polyomavirus as a microbial source-tracking tool. J. Virol. Methods 2010, 163, 385–389.
  10. Harrach, B.; Tarján, Z.L.; Benkő, M. Adenoviruses across the animal kingdom: A walk in the zoo. FEBS Lett. 2019, 593, 3660–3673.
  11. Robinson, R.K. Encyclopedia of Food Microbiology; Academic Press: New York, NY, USA, 2014.
  12. Masiello, S.N.; Martin, N.H.; Trmcic, A.; Wiedmann, M.; Boor, K.J. Identification and characterization of psychrotolerant coliform bacteria isolated from pasteurized fluid milk. J. Dairy Sci. 2016, 99, 130–140.
  13. Martin, N.H.; Trmčić, A.; Hsieh, T.-H.; Boor, K.J.; Wiedmann, M. The evolving role of coliforms as indicators of unhygienic processing conditions in dairy foods. Front. Microbiol. 2016, 7, 1549.
  14. Craun, G.F.; Berger, P.S.; Calderon, R.L. Coliform bacteria and waterborne disease outbreaks. J.-Am. Water Work. Assoc. 1997, 89, 96–104.
  15. U.S. Environmental Protection Agency. National Interim Primary Drinking Water Regulations; U.S. Environmental Protection Agency: Washington, DC, USA, 1976.
  16. U.S. Environmental Protection Agency. National Primary Drinking Water Regulations Total Coliforms Final Rule; U.S. Environmental Protection Agency: Washington, DC, USA, 1989.
  17. Das, S.K.; Das, S.K. Influence of phosphorus and organic matter on microbial transformation of arsenic. Environ. Technol. Innov. 2020, 19, 100930.
  18. Rosenblueth, M.; Martinez, L.; Silva, J.; Martinez-Romero, E. Klebsiella variicola, a novel species with clinical and plant-associated isolates. Syst. Appl. Microbiol. 2004, 27, 27–35.
  19. Kabler, P.W.; Clark, H.F. Coliform group and fecal coliform organisms as indicators of pollution in drinking water. J.-Am. Water Work. Assoc. 1960, 52, 1577–1579.
  20. Coliform Bacteria in Drinking Water Supplies; New York State Department of Health, Center for Environmental Health: New York, NY, USA, 2017.
  21. Florini, S.; Shahsavari, E.; Ngo, T.; Aburto-Medina, A.; Smith, D.J.; Ball, A.S. Factors Influencing the Concentration of Fecal Coliforms in Oysters in the River Blackwater Estuary, UK. Water 2020, 12, 1086.
  22. Bartram, J.; Ballance, R. Water Quality Monitoring: A Practical Guide to the Design and Implementation of Freshwater Quality Studies and Monitoring Programmes; CRC Press: Boca Raton, FL, USA, 1996.
  23. Leclercq, A.; Wanegue, C.; Baylac, P. Comparison of fecal coliform agar and violet red bile lactose agar for fecal coliform enumeration in foods. Appl. Environ. Microbiol. 2002, 68, 1631–1638.
  24. Alonso, J.; Soriano, A.; Amoros, I.; Ferrus, M. Quantitative determination of E. coli, and fecal coliforms in water using a chromogenic medium. J. Environ. Sci. Health Part A 1998, 33, 1229–1248.
  25. Evans, T.M.; LeChevallier, M.W.; Waarvick, C.E.; Seidler, R.J. Coliform species recovered from untreated surface water and drinking water by the membrane filter, standard, and modified most-probable-number techniques. Appl. Environ. Microbiol. 1981, 41, 657–663.
  26. Dunling, W.; Fiessel, W. Evaluation of media for simultaneous enumeration of total coliform and Escherichia coli in drinking water supplies by membrane filtration techniques. J. Environ. Sci. 2008, 20, 273–277.
  27. Tominaga, T. Rapid quantification of coliforms in ready-to-eat foods using lateral-flow immunochromatographic assay. J. Food Saf. 2020, 40, e12835.
  28. Hu, S.; Yu, Y.; Li, R.; Xia, X.; Xiao, X.; Li, X. Real-time TaqMan PCR for rapid detection and quantification of coliforms in chilled meat. Food Anal. Methods 2016, 9, 813–822.
  29. Martin, M.C.; Martinez, N.; del Rio, B.; Ladero, V.; Fernandez, M.; Alvarez, M.A. A novel real-time polymerase chain reaction-based method for the detection and quantification of lactose-fermenting Enterobacteriaceae in the dairy and other food industries. J. Dairy Sci. 2010, 93, 860–867.
  30. Li, X.; Harwood, V.J.; Nayak, B.; Staley, C.; Sadowsky, M.J.; Weidhaas, J. A novel microbial source tracking microarray for pathogen detection and fecal source identification in environmental systems. Environ. Sci. Technol. 2015, 49, 7319–7329.
  31. Cheswick, R.; Cartmell, E.; Lee, S.; Upton, A.; Weir, P.; Moore, G.; Nocker, A.; Jefferson, B.; Jarvis, P. Comparing flow cytometry with culture-based methods for microbial monitoring and as a diagnostic tool for assessing drinking water treatment processes. Environ. Int. 2019, 130, 104893.
  32. Xia, Y.; Li, A.-D.; Deng, Y.; Jiang, X.-T.; Li, L.-G.; Zhang, T. MinION nanopore sequencing enables correlation between resistome phenotype and genotype of coliform bacteria in municipal sewage. Front. Microbiol. 2017, 8, 2105.
  33. Moore, A.C.; Herwaldt, B.L.; Craun, G.F.; Calderon, R.L.; Highsmith, A.K.; Juranek, D.D. Waterborne disease in the United States, 1991 and 1992. J.-Am. Water Work. Assoc. 1994, 86, 87–97.
  34. U.S. Environmental Protection Agency. Test Methods for Escherichia coli and Enterococci in Water by the Membrane Filter Procedure; (Method #1103.1); U.S. Environmental Protection Agency: Washington, DC, USA, 1985.
  35. U.S. Environmental Protection Agency. Ambient Water Quality Criteria for Bacteria—1986; U.S. Environmental Protection Agency: Washington, DC, USA, 1986.
  36. Ishii, S.; Sadowsky, M.J. Escherichia coli in the Environment: Implications for Water Quality and Human Health. Microbes. Environ. 2008, 23, 101–108.
  37. Souid, F.; Agoubi, B.; Hamdi, M.; Telahigue, F.; Kharroubi, A. Groundwater chemical and fecal contamination assessment of the Jerba unconfined aquifer, southeast of Tunisia. Arab. J. Geosci. 2017, 10, 231.
  38. Dheenan, P.S.; Jha, D.K.; Das, A.K.; Vinithkumar, N.V.; Devi, M.P.; Kirubagaran, R. Geographic information systems and multivariate analysis to evaluate fecal bacterial pollution in coastal waters of Andaman, India. Environ. Pollut. 2016, 214, 45–53.
  39. Byappanahalli, M.N.; Whitman, R.L.; Shively, D.A.; Sadowsky, M.J.; Ishii, S. Population structure, persistence, and seasonality of autochthonous Escherichia coli in temperate, coastal forest soil from a Great Lakes watershed. Environ. Microbiol. 2006, 8, 504–513.
  40. Power, M.L.; Littlefield-Wyer, J.; Gordon, D.M.; Veal, D.A.; Slade, M.B. Phenotypic and genotypic characterization of encapsulated Escherichia coli isolated from blooms in two Australian lakes. Environ. Microbiol. 2005, 7, 631–640.
  41. Escobar-Paramo, P.; Le Menac’h, A.; Le Gall, T.; Amorin, C.; Gouriou, S.; Picard, B.; Skurnik, D.; Denamur, E. Identification of forces shaping the commensal Escherichia coli genetic structure by comparing animal and human isolates. Environ. Microbiol. 2006, 8, 1975–1984.
  42. Gordon, D.M.; Cowling, A. The distribution and genetic structure of Escherichia coli in Australian vertebrates: Host and geographic effects. Microbiology 2003, 149, 3575–3586.
  43. Clermont, O.; Lescat, M.; O’Brien, C.L.; Gordon, D.M.; Tenaillon, O.; Denamur, E. Evidence for a human-specific Escherichia coli clone. Environ. Microbiol. 2008, 10, 1000–1006.
  44. Williams, A.; Avery, L.; Killham, K.; Jones, D.L. Persistence of Escherichia coli O157 on farm surfaces under different environmental conditions. J. Appl. Microbiol. 2005, 98, 1075–1083.
  45. Sinton, L.W.; Hall, C.H.; Lynch, P.A.; Davies-Colley, R.J. Sunlight inactivation of fecal indicator bacteria and bacteriophages from waste stabilization pond effluent in fresh and saline waters. Appl. Environ. Microbiol. 2002, 68, 1122–1131.
  46. Brennan, F.P.; Grant, J.; Botting, C.H.; O’Flaherty, V.; Richards, K.G.; Abram, F. Insights into the low-temperature adaptation and nutritional flexibility of a soil-persistent Escherichia coli. FEMS Microbiol. Ecol. 2013, 84, 75–85.
  47. Vital, M.; Hammes, F.; Egli, T. Competition of Escherichia coli O157 with a drinking water bacterial community at low nutrient concentrations. Water Res. 2012, 46, 6279–6290.
  48. Haller, L.; Poté, J.; Loizeau, J.-L.; Wildi, W. Distribution and survival of faecal indicator bacteria in the sediments of the Bay of Vidy, Lake Geneva, Switzerland. Ecol. Indic. 2009, 9, 540–547.
  49. Schwering, M.; Song, J.; Louie, M.; Turner, R.J.; Ceri, H. Multi-species biofilms defined from drinking water microorganisms provide increased protection against chlorine disinfection. Biofouling 2013, 29, 917–928.
  50. Mellefont, L.A.; McMeekin, T.A.; Ross, T. Performance evaluation of a model describing the effects of temperature, water activity, pH and lactic acid concentration on the growth of Escherichia coli. Int. J. Food Microbiol. 2003, 82, 45–58.
  51. Abia, A.L.; Ubomba-Jaswa, E.; Momba, M.N. Impact of seasonal variation on Escherichia coli concentrations in the riverbed sediments in the Apies River, South Africa. Sci. Total Environ. 2015, 537, 462–469.
  52. Stocker, M.D.; Pachepsky, Y.A.; Hill, R.L.; Shelton, D.R. Depth-Dependent Survival of Escherichia coli and Enterococci in Soil after Manure Application and Simulated Rainfall. Appl. Environ. Microbiol. 2015, 81, 4801–4808.
  53. Kleinheinz, G.T.; McDermott, C.M.; Hughes, S.; Brown, A. Effects of rainfall on E. coli concentrations at Door County, Wisconsin beaches. Int. J. Microbiol. 2009, 2009, 876050.
  54. Mugler, C.; Ribolzi, O.; Viguier, M.; Janeau, J.L.; Jarde, E.; Latsachack, K.; Henry-Des-Tureaux, T.; Thammahacksa, C.; Valentin, C.; Sengtaheuanghoung, O.; et al. Experimental and modelling evidence of splash effects on manure borne Escherichia coli washoff. Environ. Sci. Pollut. Res. Int. 2021, 28, 33009–33020.
  55. Stumpf, C.H.; Piehler, M.F.; Thompson, S.; Noble, R.T. Loading of fecal indicator bacteria in North Carolina tidal creek headwaters: Hydrographic patterns and terrestrial runoff relationships. Water Res. 2010, 44, 4704–4715.
  56. Abia, A.L.; James, C.; Ubomba-Jaswa, E.; Benteke Momba, M.N. Microbial Remobilisation on Riverbed Sediment Disturbance in Experimental Flumes and a Human-Impacted River: Implication for Water Resource Management and Public Health in Developing Sub-Saharan African Countries. Int. J. Environ. Res. Public Health 2017, 14, 306.
  57. Ducarmon, Q.R.; Zwittink, R.D.; Hornung, B.V.H.; van Schaik, W.; Young, V.B.; Kuijper, E.J. Gut Microbiota and Colonization Resistance against Bacterial Enteric Infection. Microbiol. Mol. Biol. Rev. 2019, 83, e00007-19.
  58. Momose, Y.; Hirayama, K.; Itoh, K. Competition for proline between indigenous Escherichia coli and E. coli O157: H7 in gnotobiotic mice associated with infant intestinal microbiota and its contribution to the colonization resistance against E. coli O157: H7. Antonie Van Leeuwenhoek 2008, 94, 165–171.
  59. Panhwar, S.; Aftab, A.; Keerio, H.A.; Sarmadivaleh, M.; Tamer, U. A Novel Approach for Real-Time Enumeration of Escherichia coli ATCC 47076 in Water through High Multi-Functional Engineered Nano-Dispersible Electrode. J. Electrochem. Soc. 2021, 168, 037514.
  60. Centers for Disease Control and Prevention. National Shiga Toxin-Producing Escherichia coli (STEC) Surveillance Annual Report, 2016; CDC: Atlanta, GA, USA, 2018.
  61. Wong, S.Y.; Paschos, A.; Gupta, R.S.; Schellhorn, H.E. Insertion/deletion-based approach for the detection of Escherichia coli O157: H7 in freshwater environments. Environ. Sci. Technol. 2014, 48, 11462–11470.
  62. Cox, C.R.; Gilmore, M.S. Native microbial colonization of Drosophila melanogaster and its use as a model of Enterococcus faecalis pathogenesis. Infect. Immun. 2007, 75, 1565–1576.
  63. Ghosh, A.; Kukanich, K.; Brown, C.E.; Zurek, L. Resident Cats in Small Animal Veterinary Hospitals Carry Multi-Drug Resistant Enterococci and are Likely Involved in Cross-Contamination of the Hospital Environment. Front. Microbiol. 2012, 3, 62.
  64. Cai, Y. Identification and characterization of Enterococcus species isolated from forage crops and their influence on silage fermentation. J. Dairy Sci. 1999, 82, 2466–2471.
  65. Napier, M.D.; Haugland, R.; Poole, C.; Dufour, A.P.; Stewart, J.R.; Weber, D.J.; Varma, M.; Lavender, J.S.; Wade, T.J. Exposure to human-associated fecal indicators and self-reported illness among swimmers at recreational beaches: A cohort study. Environ. Health 2017, 16, 103.
  66. Wade, T.J.; Sams, E.; Brenner, K.P.; Haugland, R.; Chern, E.; Beach, M.; Wymer, L.; Rankin, C.C.; Love, D.; Li, Q. Rapidly measured indicators of recreational water quality and swimming-associated illness at marine beaches: A prospective cohort study. Environ. Health 2010, 9, 66.
  67. Wade, T.J.; Calderon, R.L.; Brenner, K.P.; Sams, E.; Beach, M.; Haugland, R.; Wymer, L.; Dufour, A.P. High sensitivity of children to swimming-associated gastrointestinal illness: Results using a rapid assay of recreational water quality. Epidemiology 2008, 19, 375–383.
  68. U.S. Environmental Protection Agency. Recreational Water Quality Criteria; U.S. Environmental Protection Agency: Washington, DC, USA, 2012.
  69. Wymer, L.J.; Brenner, K.P.; Martinson, J.W.; Stutts, W.R.; Schaub, S.; Dufour, A.P. The EMPACT Beaches Project: Results from a Study on Microbiological Monitoring in Recreational Waters; USEPA: Washington, DC, USA, 2005.
  70. Health and Welfare Canada. Guidelines for Canadian Recreational Water Quality, 3rd ed.; Healthy Environments and Consumer Safety Branch, Health Canada: Ottawa, ON, Canada, 2012.
  71. Soller, J.A.; Schoen, M.E.; Bartrand, T.; Ravenscroft, J.E.; Ashbolt, N.J. Estimated human health risks from exposure to recreational waters impacted by human and non-human sources of faecal contamination. Water Res. 2010, 44, 4674–4691.
  72. Miller, W.R.; Munita, J.M.; Arias, C.A. Mechanisms of antibiotic resistance in enterococci. Expert Rev. Anti-Infect. 2014, 12, 1221–1236.
  73. Cheng, W.; Chen, J.-C. Effect of cultivation broth pH, temperature and NaCl concentration on virulence of an Enterococcus-like bacterium to the giant freshwater prawn Macrobrachium rosenbergii. Dis. Aquat. Org. 1999, 36, 233–237.
  74. Dubin, K.; Pamer, E.G. Enterococci and their interactions with the intestinal microbiome. Microbiol. Spectr. 2017, 5, 5–6.
  75. Roslev, P.; Iversen, L.; Sonderbo, H.L.; Iversen, N.; Bastholm, S. Uptake and persistence of human associated Enterococcus in the mussel Mytilus edulis: Relevance for faecal pollution source tracking. J. Appl. Microbiol. 2009, 107, 944–953.
  76. Nishiyama, M.; Iguchi, A.; Suzuki, Y. Identification of Enterococcus faecium and Enterococcus faecalis as vanC-type vancomycin-resistant enterococci (VRE) from sewage and river water in the provincial city of Miyazaki, Japan. J. Environ. Sci. Health Part A 2015, 50, 16–25.
  77. Piggot, A.M.; Klaus, J.S.; Johnson, S.; Phillips, M.C.; Solo-Gabriele, H.M. Relationship between enterococcal levels and sediment biofilms at recreational beaches in South Florida. Appl. Environ. Microbiol. 2012, 78, 5973–5982.
  78. Wiegner, T.N.; Mead, L.H.; Molloy, S.L. A comparison of water quality between low-and high-flow river conditions in a tropical estuary, Hilo Bay, Hawaii. Estuaries Coasts 2013, 36, 319–333.
  79. Deller, S.; Mascher, F.; Platzer, S.; Reinthaler, F.F.; Marth, E. Effect of solar radiation on survival of indicator bacteria in bathing waters. Cent. Eur. J. Public Health 2006, 14, 133–137.
  80. Heim, S.; Del Mar Lleo, M.; Bonato, B.; Guzman, C.A.; Canepari, P. The viable but nonculturable state and starvation are different stress responses of Enterococcus faecalis, as determined by proteome analysis. J. Bacteriol. 2002, 184, 6739–6745.
  81. Dorevitch, S.; Doi, M.; Hsu, F.C.; Lin, K.T.; Roberts, J.D.; Liu, L.C.; Gladding, R.; Vannoy, E.; Li, H.; Javor, M.; et al. A comparison of rapid and conventional measures of indicator bacteria as predictors of waterborne protozoan pathogen presence and density. J. Environ. Monit. 2011, 13, 2427–2435.
  82. Mansilha, C.R.; Coelho, C.A.; Reinas, A.; Moutinho, A.; Ferreira, S.; Pizarro, C.; Tavares, A. Salmonella: The forgotten pathogen: Health hazards of compliance with European Bathing Water Legislation. Mar. Pollut. Bull. 2010, 60, 819–826.
  83. Wang, H.; Naghavi, M.; Allen, C.; Barber, R.M.; Bhutta, Z.A.; Carter, A.; Casey, D.C.; Charlson, F.J.; Chen, A.Z.; Coates, M.M. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: A systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016, 388, 1459–1544.
  84. Koo, B.S.; Hwang, E.H.; Kim, G.; Park, J.Y.; Oh, H.; Lim, K.S.; Kang, P.; Lee, H.Y.; Jeong, K.J.; Mo, I.; et al. Prevalence and characterization of Clostridium perfringens isolated from feces of captive cynomolgus monkeys (Macaca fascicularis). Anaerobe 2020, 64, 102236.
  85. Matches, J.R.; Liston, J.; Curran, D. Clostridium perfringens in the environment. Appl. Microbiol. 1974, 28, 655–660.
  86. Sabry, M.; Abd El-Moein, K.; Hamza, E.; Abdel Kader, F. Occurrence of Clostridium perfringens Types A, E, and C in Fresh Fish and Its Public Health Significance. J. Food Prot. 2016, 79, 994–1000.
  87. Scott, A.; Tien, Y.C.; Drury, C.F.; Reynolds, W.D.; Topp, E. Enrichment of antibiotic resistance genes in soil receiving composts derived from swine manure, yard wastes, or food wastes, and evidence for multiyear persistence of swine Clostridium spp. Can. J. Microbiol. 2018, 64, 201–208.
  88. Milton, A.A.P.; Sanjukta, R.; Gogoi, A.P.; Momin, K.M.; Priya, G.B.; Das, S.; Ghatak, S.; Sen, A.; Kandpal, B.K. Prevalence, molecular typing and antibiotic resistance of Clostridium perfringens in free range ducks in Northeast India. Anaerobe 2020, 64, 102242.
  89. Fujioka, R.S. Monitoring coastal marine waters for spore-forming bacteria of faecal and soil origin to determine point from non-point source pollution. Water Sci. Technol. 2001, 44, 181–188.
  90. Skanavis, C.; Yanko, W.A. Clostridium perfringens as a potential indicator for the presence of sewage solids in marine sediments. Mar. Pollut. Bull. 2001, 42, 31–35.
  91. Paredes-Sabja, D.; Sarker, N.; Setlow, B.; Setlow, P.; Sarker, M.R. Roles of DacB and spm proteins in clostridium perfringens spore resistance to moist heat, chemicals, and UV radiation. Appl. Environ. Microbiol. 2008, 74, 3730–3738.
  92. Wang, G.; Paredes-Sabja, D.; Sarker, M.; Green, C.; Setlow, P.; Li, Y.q. Effects of wet heat treatment on the germination of individual spores of C lostridium perfringens. J. Appl. Microbiol. 2012, 113, 824–836.
  93. Savichtcheva, O.; Okabe, S. Alternative indicators of fecal pollution: Relations with pathogens and conventional indicators, current methodologies for direct pathogen monitoring and future application perspectives. Water Res. 2006, 40, 2463–2476.
  94. Vijayavel, K.; Kashian, D. Evaluation of Clostridium perfringens as a tracer of sewage contamination in sediments by two enumeration methods. Environ. Monit. Assess. 2014, 186, 5617–5624.
  95. Sartory, D. Membrane filtration enumeration of faecal clostridia and Clostridium perfringens in water. Water Res. 1986, 20, 1255–1260.
  96. Sartory, D.P.; Field, M.; Curbishley, S.M.; Pritchard, A.M. Evaluation of two media for the membrane filtration enumeration of Clostridium perfringens from water. Lett. Appl. Microbiol. 1998, 27, 323–327.
  97. Marshall, R.S.; Steenbergen, J.F.; McClung, L. Rapid technique for the enumeration of Clostridium perfringens. Appl. Microbiol. 1965, 13, 559–563.
  98. Karpowicz, E.; Novinscak, A.; Barlocher, F.; Filion, M. qPCR quantification and genetic characterization of Clostridium perfringens populations in biosolids composted for 2 years. J. Appl. Microbiol. 2010, 108, 571–581.
  99. Milton, A.A.P.; Momin, K.M.; Priya, G.B.; Ghatak, S.; Gandhale, P.N.; Angappan, M.; Das, S.; Sen, A. A novel in situ methodology for visual detection of Clostridium perfringens in pork harnessing saltatory rolling circle amplification. Anaerobe 2021, 69, 102324.
  100. Bernhard, A.E.; Field, K.G. Identification of nonpoint sources of fecal pollution in coastal waters by using host-specific 16S ribosomal DNA genetic markers from fecal anaerobes. Appl. Environ. Microbiol. 2000, 66, 1587–1594.
  101. Pilla, R.; Suchodolski, J.S. The Role of the Canine Gut Microbiome and Metabolome in Health and Gastrointestinal Disease. Front. Vet. Sci. 2019, 6, 498.
  102. Bergamaschi, M.; Tiezzi, F.; Howard, J.; Huang, Y.J.; Gray, K.A.; Schillebeeckx, C.; McNulty, N.P.; Maltecca, C. Gut microbiome composition differences among breeds impact feed efficiency in swine. Microbiome 2020, 8, 110.
  103. Kabiri, L.; Alum, A.; Rock, C.; McLain, J.E.; Abbaszadegan, M. Isolation of Bacteroides from fish and human fecal samples for identification of unique molecular markers. Can. J. Microbiol. 2013, 59, 771–777.
  104. Ko, H.Y.; Cho, K.; Park, S.; Kim, J.H.; Kang, J.H.; Jeong, Y.S.; Choi, J.D.; Sin, Y.; Lee, C.; Ko, G. Host-Specific Bacteroides Markers-Based Microbial Source Tracking in Aquaculture Areas. Microbes Environ. 2018, 33, 151–161.
  105. Bacic, M.K.; Smith, C.J. Laboratory maintenance and cultivation of bacteroides species. Curr. Protoc. Microbiol. 2008, 9, 13C-1.
  106. Livingston, S.J.; Kominos, S.D.; Yee, R.B. New medium for selection and presumptive identification of the Bacteroides fragilis group. J. Clin. Microbiol. 1978, 7, 448–453.
  107. Ho, P.L.; Ho, L.Y.; Yau, C.Y.; Tong, M.K.; Chow, K.H. A Novel Selective Medium for Isolation of Bacteroides fragilis from Clinical Specimens. J. Clin. Microbiol. 2017, 55, 384–390.
  108. Jenkins, S.A.; Drucker, D.B.; Keaney, M.G.; Ganguli, L.A. Evaluation of the RAPID ID 32A system for the identification of Bacteroides fragilis and related organisms. J. Appl. Bacteriol. 1991, 71, 360–365.
  109. Ahmed, W.; Hughes, B.; Harwood, V.J. Current status of marker genes of Bacteroides and related taxa for identifying sewage pollution in environmental waters. Water 2016, 8, 231.
  110. Kirs, M.; Caffaro-Filho, R.A.; Wong, M.; Harwood, V.J.; Moravcik, P.; Fujioka, R.S. Human-associated Bacteroides spp. and human polyomaviruses as microbial source tracking markers in Hawaii. Appl. Environ. Microbiol. 2016, 82, 6757–6767.
  111. Boehm, A.B.; Soller, J.A. Refined ambient water quality thresholds for human-associated fecal indicator HF183 for recreational waters with and without co-occurring gull fecal contamination. Microb. Risk Anal. 2020, 16, 100139.
  112. Shanks, O.C.; Kelty, C.A.; Sivaganesan, M.; Varma, M.; Haugland, R.A. Quantitative PCR for genetic markers of human fecal pollution. Appl. Environ. Microbiol. 2009, 75, 5507–5513.
  113. Toledo-Hernandez, C.; Ryu, H.; Gonzalez-Nieves, J.; Huertas, E.; Toranzos, G.A.; Santo Domingo, J.W. Tracking the primary sources of fecal pollution in a tropical watershed in a one-year study. Appl. Environ. Microbiol. 2013, 79, 1689–1696.
  114. Zimmer-Faust, A.G.; Thulsiraj, V.; Marambio-Jones, C.; Cao, Y.; Griffith, J.F.; Holden, P.A.; Jay, J.A. Effect of freshwater sediment characteristics on the persistence of fecal indicator bacteria and genetic markers within a Southern California watershed. Water Res. 2017, 119, 1–11.
More
Information
Subjects: Water Resources
Contributor MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
View Times: 324
Revisions: 2 times (View History)
Update Date: 30 Dec 2021
1000/1000