Use of DNA fingerprinting and novel molecular methods to identify sources of Escherichia coli in the environment

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Use of DNA fingerprinting and novel molecular methods to identify sources of Escherichia coli in the environment
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Microbiology and Cell Science thesis, Ph. D   ( lcsh )
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Thesis (Ph. D.)--University of Florida, 2002.
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Includes bibliographical references (leaves 103-114).
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by Troy M. Scott.
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USE OF DNA FINGERPRINTING AND NOVEL MOLECULAR METHODS TO
IDENTIFY SOURCES OF Escherichia coli IN THE ENVIRONMENT














By

TROY M. SCOTT


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


2002



























Copyright 2002

by

Troy M. Scott













ACKNOWLEDGMENTS

I would first like to acknowledge my mentor, Dr. Samuel R.

Farrah, for his guidance and friendship throughout my graduate

career. He has always both encouraged and supported creativity in

my research. I would also like to thank the members of my graduate

committee, Dr. Edward M. Hoffmann, Dr. Phillip Achey, and Dr. Paul A.

Gulig for their guidance, assistance, and willingness to lend an ear.

Special thanks goes to Dr. Kenneth Portier for his statistical analyses,

and to Dr. Thomas Bobik, Greg Havemann, and Stuart Underwood for

lending their expertise in various aspects of molecular biology. This

study would not have been possible without the insight and assistance

of my friends and colleagues, Dr. George Lukasik, Dr. Salina Parveen,

Andrew Koo, and Jack Shelton. I would also like to thank my family

and friends, the entire Department of Microbiology and Cell Science,

my fellow graduate students, Cheryl Boice, Johnny Davis, and

Stephanie Sheperd, and the Engineering Research Center (ERC) for

Particle Science and Technology for their help and support (technical,

financial, and otherwise). Finally, I would like to acknowledge my

loving girlfriend, Alexandra Maistrellis, for being understanding and

supportive throughout this entire process.














TABLE OF CONTENTS
Page

ACKNOWLEDGMENTS................................ .............................. iii

LIST OF TABLES ........................................... ......................... vii

LIST OF FIGURES ................................................................... ix

ABSTRACT..............................................................................

1 INTRODUCTION.................................................................. 1

Disease-Causing Bacteria and their Detection in the Environment..1
Escherichia coli ................................................................2
Shigella......................................................................... 3
Salmonella ................................................................. 5
Vibrio............................................................................ 6
Campylobacter............................................................... 7
Disease-Causing Viruses and their Detection in the Environment...8
Adenovirus.......................... ........ .. ....................... .. 9
Poliovirus ......................................................................9
Hepatitis A .......................................................................11
Rotavirus ......................................................................... 12
Norwalk Agent ........................................................... 12
Disease-Causing Protozoa and their Detection in the
Environment..................................................................13
Entamoeba histolytica........................................ ........... 13
Giardia lamblia.............................................................14
Cryptosporidium parvum .................................................... 14
Microsporidia .............................................. .............. 16
Detection of Microbial Indicators of Fecal Pollution.................. 16
Methodology and Experimental Rationale ............................... 22

2 GEOGRAPHICAL VARIATION IN RIBOTYPE PROFILES OF
Escherichia coli ISOLATED FROM HUMANS, SWINE,
POULTRY, BEEF, AND DAIRY CATTLE IN FLORIDA....................25








Materials and Methods ...................................... ........... .. 26
Collection of Fecal Samples from Livestock and Humans.........26
Isolation of Escherichia coll...........................................27
Selection of E. coli Reference Strains ..................................27
DNA Extraction .................................................. ............29
Determination of DNA Concentration.............................. 29
Restriction Enzyme Digestion............................................. 29
Southern Blot Analysis ..................................... .......... 29
Probe Preparation....................................... ................30
Hybridization and Detection............................................. 30
Statistical Analysis............................................. .............30
Results ............................................................. ................... 31
Discussion .................................................................... 34

3 DEVELOPMENT OF A RAPID, PCR-BASED METHOD FOR USE
IN IDENTIFYING SOURCES OF FECAL POLLUTION......................40

Characteristics of Escherichia coli Fimbrial Adhesins.................41
Experimental Approach ............................................. ...... 43
Materials and Methods .............................................. ...... 46
Collection of Fecal Samples from Livestock and Humans.........46
Isolation of Escherichia coli...............................................47
AFLP Primers and Adapters .............................................47
Preparation of Genomic DNA and Adapter Ligation.................48
AFLP Reactions...............................................................48
Repetitive Element Polymerase Chain Reaction (Rep-PCR) ......49
PCR Amplification of rDNA Intergenic Spacer Regions...........49
PCR Amplication of FimA and FimH Genes in E. coli .............50
PCR Amplification of papG Genes in E. coli...........................53
Restriction Enzyme Analysis of rDNA, FimA, and FimH genes ..53
Gel Analysis................................................. .............. 55
Excision of Unique Bands and DNA Recovery...................... 55
Cloning of PCR Products and Fimbrial Genes .......................55
Analysis of Positive Clones..................................... ......... 56
Plasmid Isolation and DNA Sequencing................................56
Sequence and Phylogenetic Analyses of FimA Gene...............56
PCR Amplification of DNA Sequences Within the FimA Gene.... 58
Results................................................................. ...................... ....... 58
Collection of E. coli Isolated from Florida Livestock and
Hum an Sources............................................ .............. 58
AFLP Reactions...............................................................60
Screening of Primers Derived from AFLP Fragments..............60
Repetitive Element Polymerase Chain Reaction (Rep-PCR)......66
PCR Amplification of rDNA Intergenic Spacer Regions.............66








Cloning and sequence analysis of papG genes in E. coli..........68
PCR Amplification of FimA and FimH in E. coli.....................68
RFLP Profiles of PCR-Amplified rDNA and FimA Genes ............68
Cloning and Sequence Analysis of FimH genes in E. coli .........69
DNA Alignment Analysis of FimA Genes..............................73
Amino Acid Analysis of FimA Genes ....................................78
Hydrophilicity Profile of Type-1 Fimbrial Subunit (FimA)
Protein .................................... ....................................82
Phylogenetic Analysis of FimA Genes .................................82
Identification of E. coli Isolates by TMS and REV Primer Sets..86
Characterization of Plasmids Containing Portion of FimA Gene.89
Discussion ...................................................... ..............90

4 SUMMARY AND CONCLUSIONS............................................ 95

REFERENCES ...................................................................... 103

BIOGRAPHICAL SKETCH.................................................. 115













LIST OF TABLES


Table

1. Number and sources of E. coli isolates used in this study .........28

2. Species-level classification of ribotype profiles generated
from E. coli isolated from livestock ........................................32

3. Human/nonhuman classification of ribotype profiles generated
from E. coli isolated from livestock ........................................33

4. Primer sets used to amplify ribosomal DNA intergenic spacer
regions in Escherichia coli..................................... .......51

5. PCR primers used to amplify the FimA and FimH genes
in E. coli.................................................. .....................52

6. Primer sets used to amplify variant papG genes in E. coli..........54

7. Escherichia coli isolates used in phylogenetic analyses........... 57

8. Sequences of TMS and REV primer sets.................................59

9. Primer sets derived from unique DNA fragments generated by
Amplified Fragment Length Polymorphism .............................63

10. Human/nonhuman classification of Escherichia coli
using TMS and REV primer sets............................................88












LIST OF FIGURES


Figure Pag

1. Spatial plot of first two canonical dimensions for ribotype
profiles of E. coli isolated from livestock................................35

2. Spatial plot of first and third canonical dimensions for ribotype
profiles of E. coli isolated from livestock...............................36

3. Spatial plot of second and third canonical dimensions for
ribotype profiles of E. coli isolated from livestock...................37

4. AFLP patterns observed in 2% agarose gel ..............................61

5. AFLP patterns observed in 5% polyacrylamide gel ....................62

6. Rep-PCR fingerprints generated using primer set A.................63

7. RFLP of rep-PCR products generated using primer set A............65

8. Amplification of rDNA intergenic spacer regions in
Escherichia coli.................................................................. 67

9. Amplification of the gene encoding the major structural
component (FimA) of type-1 fimbriae in Escherichia coli............70

10. Amplification of the gene encoding the lectin component
(FimH) of type-1 fimbriae in Escherichia coli........................... 71

11. RFLP patterns observed after Alul restriction enzyme
digestion of the FimA gene in Escherichia coli..........................72

12. DNA sequence alignments of FimA genes from
group I E. coli isolates ............................................. ..... 74

13. DNA sequence alignments of FimA genes from
group II E. coli isolates.................................... .............. 75








14. DNA sequence alignments of FimA genes from
group III E. coli isolates ........................................... ..... 76

15. DNA sequence alignments of FimA genes from E. coli
(Groups I, II, and III) ........................................... ....... 77

16. DNA and amino acid sequence of FimA gene from group I
Escherichia coli isolates..................................... ............ 79

17. DNA and amino acid sequence of FimA gene from group II
Escherichia coli isolates .................................................... 80

18. DNA and amino acid sequence of FimA gene from group III
Escherichia coli isolates..................................................... 81

19. Hydrophilicity profile of type-1 fimbrial subunit protein (FimA)
in Escherichia coli............................................................. 83

20. Unrooted phylogenetic tree showing genetic relationship
between FimA genes from human and animal Escherichia
coli isolates sequenced in this study......................................84

21. Phylogenetic tree showing genetic relationship between
FimA genes from human and animal Escherichia coli
isolates sequenced in this study and in published
literature ................................................... ................. 85

22. Schematic representation of sequence of primer usage to
identify Human and Animal-derived FimA genes in
Escherichia coli................................................................. 87

23. Gel electrophoresis of plasmid pFAO1 (a) and PCR product
pCRFimA (b) using TMS1 and REVgg primer set ....................91

24. Sequence alignment of pCRFimA and group I FimA gene...........92














Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

USE OF DNA FINGERPRINTING AND NOVEL MOLECULAR METHODS TO
IDENTIFY SOURCES OF ESCHERICHIA COLI IN THE ENVIRONMENT

By

Troy M. Scott

May 2002


Chairman: Samuel R. Farrah
Major Department: Microbiology and Cell Science

Fecal pollution affects the quality and safety of many water

systems and can originate from both human and non-human sources

including farm runoff, wildlife impact, agricultural waste, inadequate

wastewater treatment, improper waste disposal, and septic failure.

Understanding the origin of fecal pollution is paramount in assessing

the proper risk and remedial action necessary after the problem has

been identified. Feces from humans and animals contain a variety of

pathogenic microorganisms, and many of these pathogens are not

readily detectable in the environment by conventional methods as they

are often present in very low numbers. In addition, different

pathogens are harbored by different animal species, making identifying








the type of pollution necessary for proper risk assessments to be

performed. The prediction of the presence of pathogens is typically

performed by the detection of established microbial indicators;

however, these indicators are not adequate in identifying sources of

pollution. Consequently, when they are detected in the environment

using conventional tests, the source and the full extent of potential

human health risks cannot be determined.

The first half of this study extended previous research using

ribotyping to differentiate E. coli (a well-established fecal indicator)

isolated from various animal species by including a greater number of

isolates collected from a larger geographic region. As a result, it was

determined that this method was not sufficient for differentiating

sources of E. coli at the host species level outside of a confined

watershed. For this reason and because ribotyping is time consuming

and expensive, the second half of this study sought a more rapid

molecular bacterial source tracking method by investigating the

possibility that specific genetic differences exist between Escherichia

coli isolated from animals and those isolated from humans. Several

methods, including AFLP, PCR ribotyping, and rep-PCR were used to

analyze the entire genome of E. coli from various sources for

significant or subtle genetic differences. Single genes were also

sequenced and analyzed for differences that could be useful in








discriminating E. coli isolates based on host origin. Specifically,

sequence analyses were performed on genes that code for fimbrial

adhesins in E. coli. Once unique sequences were found, specific PCR

primers were developed that were capable of amplifying these

sequences. The result was a rapid, molecular tool that can aid in

differentiating Escherichia coli derived from human and animal

sources.













CHAPTER 1
INTRODUCTION

Fecal pollution affects the quality and safety of many water

systems and can originate from both human and nonhuman sources

including farm runoff, wildlife impact, agricultural waste, inadequate

wastewater treatment, improper waste disposal, and septic failure.

Many bacterial, viral, and protozoan pathogens may be present in the

intestines of humans and animals. In order to properly assess the

microbiological quality and safety of any water supply, methods must

be designed to detect even small numbers of these organisms or

reliable indicators of their presence. This task is especially important

for water systems that are used by humans for drinking, for

recreation, or in the harvesting of seafood. Of the many human

microbial pathogens, several can be transmitted by contaminated

water. The following is a brief overview of some common organisms

that pose a risk to human health and methodologies used for their

detection.

Disease-Causing Bacteria and their Detection in the Environment

Members of the family Enterobacteriaceae are gram negative

bacilli that are found worldwide in soil, water, and vegetation.








Members of this family are part of the normal flora that inhabit the

intestines of humans and animals. Enterobacteriaceae are capable of

causing a wide variety of diseases, including septicemias,

gastrointestinal infections, and urinary tract infections. The primary

mode of transmission for most of these bacteria is the fecal-oral route

(or via contaminated food and water). Members most often causing

human disease include Escherichia, Salmonella, and Shigella.

Escherichia coli

Eschericia coli produces various adhesins that allow it to remain

attached to cells in the intestinal and urinary tract. Although it is a

member of the normal commensal flora in humans, E. coli is capable of

causing a wide spectrum of diseases when it contains virulence-

enhancing plasmids or bacteriophages or when it colonizes otherwise

sterile body tissues such as the urinary tract and bladder. Urinary

tract infections are a common manifestation of E.coli infection. The

infection typically originates when bacteria from the colon contaminate

the urethra, and then spread into the bladder. E. coli is also capable

of causing gastroenteritis. The strains of E. coli that cause

gastroenteritis are divided into five groups, each with specific sites of

activity and pathogenesis. The most serious of these strains is

Enterohemorrhagic E. coli (EHEC). Many serotypes of EHEC have been

found, but the 0157:H7 serotype is responsible for the most disease.








The amount of bacilli needed for EHEC infection is quite low (<100

bacilli) (Nicholls et al. 2000; Murray et al. 2001). Some infections can

be mild and uncomplicated; however, a possible presentation of EHEC

is hemorrhagic colitis with bloody diarrhea. The severe diarrhea and

hemorrhaging associated with this strain is caused by the Shiga-like

toxins, which disrupt protein synthesis in human cells. Hemolytic

uremic syndrome, a severe urinary tract infection characterized by

acute renal failure and hemolytic anemia, is another complication of

EHEC. This is a very serious complication, which can be fatal.

Contaminated water, due to fecal pollution, is a major means of

transmission for this organism. While most E. coli are considered

harmless or opportunistic pathogens, their presence is most often used

as an indicator of the presence of other fecal pathogens. The

detection of Enterohemorrhagic E. coli (particularly 0157:H7) is of

paramount importance and both molecular (PCR, probe hybridization)

and biochemical (inability to metabolize MUG or ferment sorbitol)

methods have been used to specifically identify this pathogen.

Shigella

Shigella species are also transmitted by the fecal-oral route and

are capable of causing severe, bloody, mucoid diarrhea with fever.

Shigellosis can spread rapidly in a community with poor sanitation

standards. Epidemic outbreaks often occur in crowded institutions,








such as daycare centers. The amount of bacteria required to cause an

infection is low (about 300 bacilli) (Holcomb et al. 1999). The bacteria

first attach and invade the M (microfold) cells in the Peyer's patches of

the large intestines. Cell-to-cell transmission via the epithelial lining

spreads the infection. Shigella dysenteriae produces Shiga toxin, an

exotoxin nearly identical to that produced by Enterohemorrhagic E. coli

and clinical symptoms are nearly identical to those caused by EHEC.

While most cases of Shigellosis are caused by contaminated food or by

direct person-to-person contact, the organism may also be spread by

contaminated drinking water. The detection of Shigella spp. in

environmental samples is difficult due to the low number of organisms

present and the presence of a large number of background flora.

Although enrichment and direct-detection techniques are available,

they are difficult to perform. Additionally, the growth of coliform

bacteria in environmental samples is antagonistic to the growth of

Shigella (Blostein et al. 1991). Because the infective dose is so low,

however, the presence of any amount of Shigella poses a threat to

human health (Stutman 1994). The preferred direct method of

detection of Shigella species in drinking water is PCR (Frankel et al.

1990). Another method of detection involves a colony blot

immunoassay (Szakal et al. 2001). These








methods are more sensitive in identifying pathogen-containing

samples than the traditional culture based methods.

Salmonella

Salmonella species are found in humans and a wide variety of

warm-blooded and cold-blooded animals, both wild and domestic.

Reservoirs are maintained by animal-animal spread. Humans obtain

Salmonella infections from eating or drinking contaminated food or

water and by direct fecal-oral spread. A large number of bacilli must

be ingested in order for symptomatic disease to ensue (Stutman

1994). Enteritis is the most common form of infection caused by

Salmonella enterica species. Symptoms include nonbloody diarrhea,

nausea, and vomiting.

Salmonella typhi infection occurs after ingestion of contaminated

food or water. The syndrome that follows is called typhoid fever.

Symptoms include a gradually increasing fever, headache, malaise,

and finally gastrointestinal symptoms. Septicemia, diarrhea, shock,

and infection of the gallbladder may also occur. Salmonella typhi

infections can be severe and fatal. The methods used in the detection

of Salmonella in water are not standardized and provide variable

degrees of reliability. Selective enrichment and identification

procedures are tedious and labor-intensive. Although these tests can

be performed with some degree of accuracy, a negative test result








cannot imply the absence of salmonellae or other enteric pathogens.

Various molecular methods for the detection of Salmonella have also

been proposed. Detection of Salmonella in the marine environment

and in shellfish is preferentially done by PCR. However, although PCR

is rapid and specific, marine samples often result in false-positive

results (Dupray et al. 1997). As with any PCR assay, the test does not

discriminate between viable and nonviable organisms (Dupray et al.

1997). Immunomagnetic separation has also been used to detect

Salmonella typhi in food and water. This technique so far has proven

to be more rapid than the traditional culture-based methods, which are

slow and often ambiguous (Yu et al. 1996).

Vibrio

Vibrio cholerae is a gram negative, facultative anaerobe of the

Vibrionaceae family. This bacterium grows in marine and estuarine

environments worldwide but disease is usually concentrated in areas of

poor sanitation and in underdeveloped countries. The primary mode

of transmission for Vibrio cholera is via the ingestion of contaminated

food (especially shellfish) or water. A high inoculum of bacteria is

required to cause infection (106-108 organisms) (Seas et al. 2000).

Soon after infection with Vibrio cholerae, large amounts of watery

diarrhea and vomiting occur. The severe fluid loss results in loss of

electrolytes and dehydration. Shock and renal failure can also occur.








Standard Methods are available for the concentration and detection of

V. cholerae. Usually, water samples are concentrated and enriched

and plated on selective and differential media for presumptive

identification. Verification of V. cholerae biotypes is usually achieved

by serological analysis (Clesceri et al. 1998). DNA probes are useful in

identifying which strains contain the cholera toxin gene (Clesceri et al.

1998; Hsu et al. 2001).

Campylobacter

The genus Campylobacter consists of gram-negative bacteria

that are motile due to the presence of a polar flagellum.

Campylobacter infections are zoonotic, with many different animals

acting as reservoir hosts. Humans acquire Campylobacter infections

through the ingestion of contaminated food and water. Fecal-oral

transmission from person-to-person can also occur.

Campylobacteriosis is currently the most commonly reported diarrheal

illness in the United States (Stutman 1994). Campylobacterjejuni

infections result in acute enteritis with abdominal pain, bloody

diarrhea, and fever. The infection also results in a serious loss of

electrolytes as well as dehydration. The method of detection of

Campylobacter in drinking water must be performed on large samples

and involves filtration/concentration, enrichment, and then detection








by use of selective enriched media containing antibiotics, biochemical

tests, or by molecular methods such as PCR (Waage et al. 1999).

Disease-Causing Viruses and their Detection in the Environment

It is estimated that over 100 human enteric viruses can be

transmitted by human feces (Puig et al. 1994). Most of these viruses

infect the gastrointestinal tract and are transmitted via person-to-

person contact or by contaminated food and water. The viruses known

to be present in relatively large numbers in human feces include

polioviruses, coxsackieviruses, echoviruses, adenoviruses, reoviruses,

rotaviruses, Hepatitis A virus, and Norwalk-like viruses. Although

these viruses are present in domestic wastewater and areas impacted

by reclaimed water year-round, it has been shown that the presence of

enteroviruses reach peak levels during the late summer and early fall

while Norwalk-type viruses and Rotaviruses predominate during the

colder winter months (Rotbart et al. 1999). Once in the environment,

viruses cannot replicate and their numbers either diminish or remain

constant. Even a low level of viruses in the environment can pose a

risk to human health, however, as many have a very low (<10)

infectious dose (Murray et al. 2001). Detection of viruses in

environmental samples consists of collection and concentration of

viruses from a large sample volume (usually done by filtration)








followed by a second concentration step and finally by procedures

designed for specific or general identification of viable virions.

Adenovirus

Adenoviruses belong to the family Adenoviridae. The genome of

the adenovirus consists of a single linear molecule of dsDNA.

Adenoviruses are capable of causing numerous clinical syndromes

including respiratory infections, ocular infections, genitourinary

infections, and enteric infections. The serotypes responsible for the

enteric infections include 31, 40 and 41. Gastroenteritis due to

adenovirus is most common in children. These enteric viruses are

spread by the fecal-oral route and epidemics have been recorded in

institutions such as daycare centers and hospitals. Swimming pools,

drinking water, and wastewater represent possible reservoirs for

adenoviruses. Adenoviruses are highly resistant to disinfection and

are commonly found in treated domestic wastewater (Pina et al.

1998). Detection of adenoviruses in cell culture is difficult and this

method is often coupled with PCR to increase sensitivity (Cho et al.

2000; Puig et al. 1994).

Poliovirus

Polioviruses are enteroviruses in the family Picornaviridae. The

poliovirus genome consists of +sense ssRNA and is contained within a

naked icosahedral capsid. Enteroviruses infect the alimentary canal,








and are very resistant to the conditions in the gut. Poliovirus is spread

predominantly through the fecal-oral route. Although vaccination has

virtually eradicated the virus in developed nations, outbreaks have

resulted from the consumption of contaminated water supplies and

sewage (Knolle et al. 1995). Most poliovirus infections cause minor

illness characterized by fever, vomiting, and a sore throat. However,

in some cases, muscle stiffness and pain lead to the rapid

development of flaccid paralysis. Death may occur due to cardiac or

respiratory failure. In those that survive the disease, there is a good

chance of permanent paralysis or post polio syndrome. One method of

detecting poliovirus and other enteroviruses in water or sewage is by

the use of absorption-elution techniques followed by cell culture

detection (Clesceri et al. 1998, Kittigul et al. 2000). Enteroviruses can

also be detected using direct RT-PCR, but this requires a concentrated

sample and does not differentiate between viable and nonviable

organisms. The problem with these methods, however, is that they

involve several time-consuming steps (Legeay et al. 2000). Another

problem with direct RT-PCR (or conventional cell culture) is that these

techniques may lead to erroneous results in environmental samples

(Reynolds et al. 2001). An integrated cell culture/polymerase chain

reaction methodology (ICC/PCR) is very useful in detecting the








presence of viable enteroviruses with greater accuracy (Reynolds et al.

2001).

Hepatitis A

Hepatitis A belongs to the genus Hepatovirus and is a member of

the Picornaviridae family. Hepatitis A is spread through the fecal-oral

route and is found only in the human reservoir. The diseases caused

by this virus are endemic in areas of overcrowding and poor sanitation

(such as developing countries). Major common-source outbreaks have

occurred due to contaminated wells and water supplies. Symptoms of

this infection include fever, malaise, nausea, dark urine, and

abdominal pain. Jaundice occurs as well, representing infection of the

liver. In a small number of cases, death may occur due to fulminant

hepatitis, but more often, all nonlethal infections resolve with complete

regeneration of the damaged liver parenchyma (Rose et al. 2000). A

killed HAV vaccine has been approved by the U.S. Food and Drug

Administration and is available for high-risk individuals, such as those

traveling to endemic regions (Murray et al. 2001). The methods of

detection of Hepatitis A are the similar to those used for poliovirus, but

are more involved. RT-PCR is commonly utilized (Kingsley and

Richards, 2001; Kittigul et al. 2000).








Rotavirus

Rotaviruses are members of the family Reoviridae. They are

non-enveloped and their genomes contain 10-12 molecules of dsRNA.

During an active infection, rotaviruses are shed in extremely large

numbers in feces. Transmission of rotavirus occurs mainly through

contact with feces. Waterborne epidemics do occur, and institutions

such as daycare centers and hospitals have high numbers of

infections. Infection with rotavirus can be asymptomatic or

symptomatic. Symptoms of rotavirus infection include vomiting, then

diarrhea with severe dehydration. Death is rare in well-developed

countries, but significantly higher in underdeveloped countries (Katyal

et al. 2000). Rotaviruses can be detected in drinking water by

filtration and concentration followed by reverse transcription PCR

analysis (Gratacap-Cavallier et al. 2000). A modified adsorption-

elution technique, followed by enzyme-linked immunosorbent assay

(ELISA) for concentration of rotavirus in sewage and drinking water is

also used (Kittigul et al. 2000).

Norwalk Agent

The Norwalk virus is a member of the family Caliciviridae. The

Norwalk virus is non-enveloped and the genome consists of +ssRNA.

The disease caused by the Norwalk virus has a very short incubation

period and the infection itself is short-lived. Symptoms include








nausea, vomiting, diarrhea, low fever, and abdominal cramps.

Common-source outbreaks frequently happen via fecal contamination

of food and water. Major outbreaks have occurred due to the

consumption of raw shellfish taken from sewage-polluted estuaries

(Le Guyader et al. 2000). Also, outbreaks have been attributed to

discharge of sewers into drinking supplies. Norwalk virus can also be

detected in environmental samples by filtration and concentration

followed by reverse transcription-PCR (Atmar and Estes, 2001) as well

as RT-PCR-oligoprobe amplification (Schwab et al. 2001).

Disease-Causing Protozoa and their Detection in the Environment

Entamoeba histolytica

Entamoeba histolytica infections occur worldwide and are the

third leading cause of death among parasitic infections. The cyst form

of this organism is infective to humans and the cysts have the ability

to survive in food and water. Transmission in water is common in

developing countries, where much of the water supply is untreated and

contaminated with feces. The use of human feces for fertilizer is also

an important source of infection. Several clinical presentations of E.

histolytica are known. Infection may be asymptomatic in some

individuals and fatal in others. Acute amebic colitis involving frequent

bloody stools and fever may develop. A similar syndrome, fulminant

colitis, may also occur. Ameboma, characterized by asymptomatic








lesions is yet another presentation. If left untreated, amoebae can

disseminate throughout the body causing disease in the brain, liver,

heart, and lungs (Cook 1997; Natarajan et al. 2000). Detection of

Entamoeba histolytica can be performed by direct microscopic

examination or by various molecular assays, including ELISA and PCR

(Evangelopoulos et al. 2001; Schunk et al. 2001; Zindrou et al. 2001).

Giardia lamblia

Giardia lamblia is the most commonly isolated intestinal parasite

in the world and it is especially prevalent in children in underdeveloped

countries (Gardner et al. 2001). Outbreaks of Giardia are associated

with the ingestion of unfiltered, inadequately chlorinated water.

Waterborne transmission causes giardiasis in travelers in endemic

countries. Symptoms of Giardia lamblia infection begin with the onset

of intestinal uneasiness, followed by nausea. Explosive, watery, foul-

smelling diarrhea follows. Abdominal cramps, low-grade fever, and

chills may also occur in some cases.

CrvDtosporidium parvum

Cryptosporidium parvum is an intestinal parasite found

worldwide. Humans obtain Cryptosporidium infections upon the

ingestion of oocysts present in food or water. The oocysts are widely

distributed in both sewage and drinking water. Swimming pool and

lake outbreaks have been identified, and as with other intestinal








parasites, travelers to countries with high rates of endemicity are

vulnerable to infection. The most common symptom of

Cryptosporidium parvum infection is diarrhea, which lasts for about

one week. Other symptoms include fever, abdominal pain, and

nausea. The American Society for Testing and Materials (ASTM)

analytic procedure is currently one method of choice for detecting

Giardia and Cryptosporidium species in source waters (Marshall et al.

1997). The method is time-consuming, difficult, and technically

complex. Variables such as weather conditions may change results.

The procedure involves sampling and filtration of a large sample of

water, followed by concentration and flotation. The recovered particles

are stained with fluorescent antibodies and observed with an

ultraviolet epiflourescence microscope. Characteristic staining patterns

identify Giardia and Cryptosporidium. EPA method 1623 and the

Information Collection Rule (ICR) Protozoan Method are also used for

recovery, identification, and quantification of Giardia and

Cryptosporidium in the environment (USEPA, 1995; USEPA, 1999).

Less technical, more accurate, and less time-consuming detection

methods are greatly needed. Cell-culture techniques have been

developed and are often supplemented by immunological or molecular

verification (DiGiovanni et al. 1999; Lowery et al. 2000; Rochelle et al.

1999; Rochelle et al. 1997; Rochelle et al. 1996).








MicrosDoridia

Members of the Order Microsporidia have the ability to infect a

wide range of vertebrate and nonvertebrate hosts. They are obligate

intracellular protozoa that form highly specialized, environmentally

resistant spores. Humans acquire Microsporidia infection via the

ingestion of spores. Surface water is the primary environmental

residence for Microsporidia. The exact route of infection is still

unknown; however, the fecal-oral route has been implicated. The

most common symptoms of Microsporidia infection are diarrhea,

dehydration, and weight loss. Most infections are found in association

with human immunodeficiency virus (HIV), implicating that an

immunocompromised host facilitates infection. Restriction fragment

length polymorphism analysis of PCR amplicons can be used to identify

various Microsporidia (Curry, 1998). In addition, direct microscopic

evaluation of specimens using immunofluorescence or electron

microscopy as well as strain-specific PCR and DNA hybridization assays

are emerging as effective means of identifying various species of

Microsporidia (DaSilva et al. 1997; Fournier et al. 2000; Franzen and

Muller, 1999; Moura et al. 1999).

Detection of Microbial Indicators of Fecal Pollution

Given the above information, and the various sources from

which these pathogens can originate, it is easy to conceive why








understanding the origin of fecal pollution is necessary to properly

assess the extent of risk and remedial action necessary after the

problem has been identified. As stated previously, human fecal waste

can contain various enteric pathogens, some of which are unique to

humans, including Salmonella typhi, Shigella spp., Hepatitis A, and

Norwalk-group viruses. However, other fecal pathogens are shared

with animals (e.g., various serotypes of Salmonella and E. coli). Many

of these fecal human pathogens are not readily detectable in the

environment by conventional methods as they are often present in

very low numbers. This is further complicated by the fact that many

of them have a considerably low infectious dose, which renders even a

low prevalence in polluted waters hazardous to human health.

Therefore, the prediction of their presence is typically performed by

the detection of established indicators of fecal pollution.

Escherichia coli has long been used as an indicator of fecal

pollution (Geldreich, 1966). It has good characteristics of an indicator,

such as not normally being pathogenic to humans, and is present at

concentrations much higher than the pathogens it predicts. However,

it is well established that E. coli is not limited to humans, but also

exists in the intestines of many other warm-blooded animals (Orskov

and Orskov, 1981). Consequently, when it is detected in water with

conventional bacteriological tests, its source and the full extent of








potential human health risks cannot be determined. This could be

remedied by the development of better testing methods and analysis

techniques that can define specific sources of E. coli.

To meet the challenge of identifying sources of fecal pollution,

various methods have been proposed. Initially, the ratio of fecal

coliforms to fecal streptococci was proposed, where a ratio of >4.0

would indicate human pollution and a ratio of < 0.7 would indicate

nonhuman pollution (Geldreich and Kenner, 1969). However, this

approach has proven to be unreliable due to variable survival rates of

fecal streptococci species and variable sensitivity to water treatments

(Pourcher et al. 1991).

Investigators have also reported that animal and human feces

contain different serotypes of RNA coliphages (Furuse et al. 1981),

suggesting that phages could be used to predict sources of pollution.

However, its usefulness is limited, because only a small percentage of

human fecal samples contain phages (Gerba 1987).

Numerous phenotypic and genotypic methods for discriminating

bacteria have been suggested. These include biochemical tests (Olsen

et al. 1992), phage susceptibility (Zierdt et al. 1980), outer

membrane protein profiles (Barenkamp 1981), antibody reactivity

(Wachsmuth 1986), fimbriation (Latham and Stamm, 1984),

bacteriocin production and susceptibility, and other methods.








However, these systems have serious disadvantages, including

unstable phenotypes, low sensitivity at the intraspecies level, and

limited specificity.

Human-specific chemical substances have also been used in fecal

source tracking. These include caffeine (Burkhardt et al. 1999), fecal

sterols (Edwards et al. 1998), and laundry optical brighteners.

However, the methodologies used for their detection are extremely

tedious and lack the desired sensitivity needed due to the dilution of

the chemical in the environment.

Multiple antibiotic resistance (MAR) is a method that has been

used to differentiate E. coli from different sources using antibiotics

commonly associated with human and animal therapy, as well as

animal feed (Cooke 1976; Harwood 2000; Parveen et al. 1997;

Wiggins 1996; Wiggins et al. 1999). However, ultimately, this is likely

not the technique of choice, since antibiotic resistance is often carried

on plasmids, which can be readily lost from cells via cultivation and

storage or by changes in environmental conditions. In addition,

strains from different locations may show variations in specific

sensitivities due to variable antibiotic use among humans and livestock

species. Furthermore, antibiotic sensitivity would not be useful in

situations where the isolates under study show no significant

resistance patterns, yet come from different animal species.








Pulsed field gel electrophoreses (PFGE) is a method of DNA

fingerprinting. The fingerprints are generated after treatment of

genomic bacterial DNA with rare-cutting restriction endonucleases.

PFGE has been a very useful technique in determining bacterial

relatedness but has thus far been ineffective in bacterial source

tracking studies (Parveen et al. 2001).

PCR amplification of repetitive DNA sequences (rep-PCR) in E.

coli has also been reported as a feasible method for differentiating E.

coli from human and animal sources (Dombek et al. 2000). This

method produces a reliable and reproducible fingerprint and is

relatively easy to perform. However, this method also requires that a

reference database be established and additional known isolates must

be fingerprinted from a large geographic region in order to assess the

potential universal application of this procedure.

Ribotyping is a method of DNA fingerprinting whereby highly

conserved rRNA genes are identified after treatment of genomic DNA

with restriction endonucleases. Ribotyping has proven to be a very

useful epidemiological technique for use with various bacteria,

including E. coli (Stull et al. 1988), Salmonella enterica (Olsen et al.

1992), V. cholerae 01 (Popovic et al. 1993), and V. vulnificus (Anzar

et al. 1993; Tamplin et al. 1996). Ribotyping can also effectively track

human and nonhuman sources of pollution with a high degree of








confidence (Carson et al. 2001; Parveen et al. 1999). This method is

often used in conjunction with other methods such as multiple

antibiotic resistance profiling and serological analyses to confirm

bacterial origin. The ribotyping method is a two-week procedure and

involves bacteriological culture and identification, DNA extraction, gel

electrophoresis, ribotyping, and discriminant analysis of the DNA

fragments. The success of this procedure depends on the size of the

reference database to which a ribotype profile from an unknown isolate

must be compared. The inability of many labs to compile a useful

database is one limitation of this procedure. Although this method has

proven successful, it is also expensive and time consuming.

PCR ribotyping uses PCR to amplify a fragment of the genomic

DNA which includes the spacer region between the genes coding for

16S and 23S rRNA. In previous studies, sequence polymorphisms in

these spacer regions have been used in differentiating closely related

members of a number of bacterial genera (Cartwright et al. 1995;

Kostman et al. 1992; Matar et al. 1993). Escherichia coli has been

shown to possess seven alleles of the rRNA gene cluster (Kiss et al.

1977). Successful bacterial source-tracking using this procedure

would most likely rely on the creation of a riboPCR profile database to

which unknown banding patterns could be compared followed by

discriminant analysis.








Rapid tests that discriminate human fecal pollution from bovine

fecal pollution are currently available using Length-heterogeneity PCR

(LH-PCR) and Terminal restriction fragment length polymorphism (T-

RFLP) analysis to characterize members of the Bacteriodes-Prevotella

group and the genus Bifidobacterium (Bernhard and Field, 2000).

This study produced reliable results; however, it analyzed a limited

number of isolates from only two hosts (humans and cows) from a

confined geographic area.

Methodology and Experimental Rationale

The first part of this study expanded on previous research using

ribotyping and discriminant analysis by including isolates collected

from four species of animal (beef cattle, dairy cattle, swine, poultry)

throughout Northern, Central, and Southern Florida. While published

studies have reported that ribotyping is a useful tool in identifying E.

coli based on host source, these studies used a limited number of

isolates from a confined geographic region (Carson et al. 2001;

Parveen et al. 1999). The present study attempted to determine

whether ribotype profiles are unique to isolates from a particular host.

In addition, it was investigated whether these profiles are useful

outside of a confined geographic region or whether this method only

provides discriminating power within a specific watershed.








The apparent success of the ribotyping procedure, as well as

other genetic fingerprinting methods, has provided empirical evidence

that unique DNA sequences exist within the E. coli genome that

directly or indirectly correlate with source. In addition to ribotyping

analysis, the second half of the present study examined the possibility

that groups of DNA sequences exist within the genome of E. coli that

are capable of discriminating source. Various methods of detecting

differences within the bacterial genome were compared and included

"brute-force" methodologies such as amplified fragment length

polymorphism (AFLP) analysis, PCR-ribotyping, repetitive element

polymerase chain reaction (rep-PCR), and restriction fragment length

polymorphism (RFLP) analysis as well as more direct, specific

methodologies such as sequence analysis of genes coding for fimbrial

and nonfimbrial adhesins present on the bacterial surface that play a

direct role in bacterial attachment and colonization.

The basis for the latter research approach was the possibility

that host specificity is a result of differential affinity of E. coli for

unique, specific receptors within a particular host. The gene that

codes for the major structural component of type 1 fimbriae (fimA)

and the lectin component of Type 1 fimbriae (fimH), as well as the

genes that code for the proteins constituting the distal portion of the

P1 pilus (lectin) in pyelonephritic Escherichia coli (papG, Classes I, II,








III) were considered as genes within the E. coli chromosome that may

show subtle genetic variations between isolates from different sources

due to differences in binding sites and receptors on different host cell

surfaces.













CHAPTER 2
GEOGRAPHICAL VARIATION IN RIBOTYPE PROFILES OF Escherichia
coli ISOLATED FROM HUMANS, SWINE, POULTRY, BEEF, AND DAIRY
CATTLE IN FLORIDA

Understanding the sources) of fecal pollution is paramount in

assessing the potential risks of the contamination to human health and

in properly determining the remedial actions necessary to correct the

problem. While many methods have been proposed, genotypic

methods provide the most reliable results, as phenotypic tests are

often less stable and more sensitive to environmental factors.

Ribotyping has been used by several researchers to discriminate

between closely related strains of bacteria as well as in bacterial

source tracking (Carson et al. 2001; Parveen et al. 1999; Svec et al.

2001). While these studies have shown genotypic differences between

human and animal-derived indicators, they have focused on isolates

collected from a confined geographic area and have not addressed the

question as to whether these profiles are watershed-specific or if they

can be applied universally to organisms from other geographic

locations.

In this study, Escherichia coli isolated from humans, beef cattle,

dairy cattle, swine, and poultry were collected from locations in








Northern, Central, and Southern Florida and ribotyped. The intent was

to determine if ribotype profiles: 1.) Were capable of discriminating

the source of E. coli at the species level, and 2.) Were specific for a

particular animal source in a specific, confined, or broad geographical

region.

Materials and Methods

Collection of Fecal Samples from Livestock and Humans

Compost feces were collected from swine, poultry, dairy and

cattle farms in three separate geographical regions of Florida over

seasonal time intervals. Samples from dairy cattle farms were

collected from retention ponds containing stall flush water located in

Greenville, FL (North), Hague, FL, (Central), and Okeechobee, FL

(South). Samples from beef cattle farms were collected from

composite manure pits and flush water retention ponds in Lake City,

FL (North), Alachua, FL (Central), and Okeechobee, FL (South).

Samples from swine farms were collected from retention ponds located

in Grand Ridge, FL (North), Gainesville, FL (Central), and Dade City, FL

(South). Samples from chicken farms were collected from retention

ponds located in Bushnell, FL (North), Dade City, FL (Central), and

Zolfo Springs (South). Water samples were collected from at least

three locations within the retention ponds and at least three separate

samples from composite manure pits were collected from each farm.








After collection, all samples were stored at 40C, transported to the

laboratory in refrigerated (40C) coolers, and processed within 24

hours. Human isolates were obtained directly from human volunteers,

residential septic systems, and from sewage lines that have no animal

impact. A summary of the types of isolates and samples taken is

shown in Table 1.

Isolation of Escherichia coli

Fecal samples were streaked on MacConkey agar plates (Difco)

within 24 hours of collection. Lactose-positive colonies were picked

and subcultured into Tryptic Soy Broth (TSB, Difco) containing 4-

Methylunbelliferyl B-D-Glucuronide (MUG) substrate (Sigma). MUG-

positive isolates were presumed to be E. coli and were verified using

the IMViC series of tests (Indole, Methyl Red, Voges-Proskauer,

Citrate). Isolates exhibiting ++-- IMViC profiles were confirmed as E.

coli.

Selection of E. coli Reference Strains

Several well-characterized human and nonhuman derived

Escherichia coli from our extensive collection were selected and used

in the establishment of an original database for isolate classification.

These reference strains are valuable for verifying sources of E. coli as

being either human or animal-derived. All isolates were maintained in

liquid nitrogen.












Table 1. Number and sources of E. coli isolates used in this study

Source Number of Location Sample Type
Isolates

Human 84 Central Septic tanks,
fecal samples


Beef 85 Northern, Central, Lagoon, manure
Southern pit (South)


Dairy 82 Northern, Central, Lagoon
Southern


Swine 80 Northern, Central, Lagoon
Southern


Poultry 70 Northern, Central, Lagoon
Southern








DNA Extraction

E. coli isolates were grown overnight in Tryptic Soy Broth (TSB)

and DNA was extracted using the Easy DNA kit (Invitrogen, Carlsbad,

CA) according to manufacturer's instructions.

Determination of DNA Concentration

DNA concentration was determined using a TKO 100 fluorometer

according to manufacturer's instructions.

Restriction Enzyme Digestion

Approximately 1 pg of DNA was digested with HindIII restriction

enzyme (Roche Molecular Biochemicals) according to manufacturer's

instructions. Digested DNA was separated on a 1.0% agarose gel at

30 V for 16 hours in 0.5X Tris-Borate-EDTA (TBE) buffer, stained with

ethidium bromide and viewed under UV light.

Southern Blot Analysis

After electrophoresis of restriction-digested DNA, agarose gels

containing restricted DNA were depurinated in 0.2M HCI for 10

minutes, denatured in 0.5M NaOH/1.5 M NaCI for 35 minutes, and

neutralized in 0.5 M Tris-HCI (pH 7.2)/1.5 M NaCI (0.0001 M) disodium

EDTA for 45 minutes. DNA was blotted from gels onto nylon

membranes (BioRad) using a vacuum blotting system (VacuGene XL)

and fixed with shortwave UV light for 5 minutes.








Probe Preparation

E. coli 16S and 23S rRNA was reverse transcribed into cDNA with

avian reverse transcriptase and labeled with digoxigenin-dUTP

according to the manufacturers instructions (Roche Molecular

Diagnostics, Mannheim, Germany).

Hybridization and Detection

Membranes were prehybridized at 65 OC for 30 minutes in 20mM

Na2HPO4 and 7% SDS (pH7.2) and then hybridized in the same

solution containing the digoxigenin-labeled probe at 650C for 16 hours.

After hybridization, membranes were washed twice for 60 min. each

time with 20mM Na2HPO4 and 5% SDS (pH 7.2) at 650C followed by 2

washes for 30 min with 20mM Na2HP04 and 1% SDS (pH 7.2) at 650C.

Membranes were then reacted with alkaline phosphatase conjugated

anti-DIG antibody and visualized by using nitroblue tetrazolium and 5-

bromo-4-chloro-3-indolyl-phosphate for colorimetric detection

according to the manufacturer's instructions (Roche Molecular

Diagnostics).

Statistical Analysis

RT banding profiles were read manually and DNA banding

patterns were translated into binary code. Binary codes were

examined using SAS (SAS Institute, Inc., Cary, N.C.) statistical

discrimination methodology. Results of the discrimination model were








summarized by use of the average rate of correct classification (ARCC)

and the percentage of correctly and misclassified isolates from the

classification table.

Results

Over 1800 E. coli were isolated and a total of 317 E. coli isolates

were ribotyped from dairy cattle, beef cattle, swine, and poultry from

northern, central, and southern Florida during the spring, summer,

fall, and winter seasons. Thirty-four unique RT bands were observed

and were used in the discriminate analysis. The ribotype

classifications of E. coli isolated from the four animal types are shown

in Table 2. As can be seen in the Table, the beef and dairy isolates

were collectively classified as dairy and nearly half of the poultry and

swine isolates were also classified as dairy. When the four animal

groups were combined, however, and tested against the

human/nonhuman database as a whole, 78.6% (n=249) were

classified as nonhuman and the remaining 21.4% (n=68) were

misclassified as human (Table 3).
















Table 2. Species-level classification of ribotype profiles
generated from E. coli isolated from livestock.
No. of isolates (%) classified as:
Source (#
of Beef Dairy Poultry Swine
isolates)

Beef (85) 5 (6) 61 (72) 18 (21) 1 (1)


Dairy 4 (5) 66 (80) 8 (10) 4 (5)
(82)

Poultry 5 (6) 45 (56) 26 (33) 4 (5)
(80)

Swine 3 (4) 33 (47) 21 (30) 13 (19)
(70)













Table 3. Human/nonhuman classification of ribotype profiles
generated from E. coli isolated from livestock
Source Nonhuman Human
(# of
isolates)

Beef 72 (84.7) 13 (15.3)
(85)

Dairy 66 (80.5) 16 (19.5)
(82)

Poultry 57 (71.3) 23 (28.5)
(80)

Swine 54 (77.1) 16 (22.9)
(70)
Total 249 (78.6) 68 (21.4)








In canonical discrimination, the sets of linear functions that best

separate the classes in the directions of most variability were

computed. If the classes are well separated, scatter plots of the

canonical scores should show well-separated scatters for the classes.

Figures 1, 2 and 3 are the scatter plots of the canonical scores for

these data. The four animal classes are not visually separated in any

of the plots. A useful scatter plot would show defined separation

between the data points, with little or no overlap. This suggests that

linear functions of the RT bands do not work well as discriminators. In

fact, several statistical parameters were used and no set of statistical

analyses was able to separate the data obtained from the different

animal sources due to significant overlap of RT profiles.

Discussion

The results of this study indicate, contrary to previously

published results, that the ribotyping procedure may not be useful in

identifying the specific animal sources of Escherichia coli collected from

a broad geographic region. In the present study, E. coli were collected

from Southern, Central, and Northern Florida from beef, dairy, poultry,

and swine farms. Ribotype profiles were generated from each animal

in each geographic location until no profile variation was observed.

These profiles were then cross-referenced within and between animal

sources and assessments were made as to whether they provided











Caoric dscriin~an RT dta

Cononical
Variable 2 _


4 3 -1 -1 9 1 3 4
Canonical Variable 1
Figure 1. Spatial plot of first two canonical dimensions for ribotype
profiles of E. coli isolated from livestock.













Caorical discrimina~ n RT dta

Canonical
V ; l


0 0 0 0 I







-3O

4A
-s ------------4 ----


-5 -4 -3 -2 -1

Cononicol
INs EDcol I Cra


0 I 2

Varioble I


Figure 2. Spatial plot of first and third canonical dimensions for
ribotype profiles of E. coli isolated from livestock


U I IUU I














Canicd discminaion RT data

Canonical
Varia le 3


-5 -4 -3 -1 -I 1 0 1 2 4
Canonicol Variable 2
u1M IE-coll aroact
Figure 3. Spatial plot of second and third canonical dimensions for
ribotype profiles of E. coli isolated from livestock.








discriminatory information. Overlap of ribotype profiles within and

between animal groups was significant. Therefore, no single profile or

group of profiles could be attributed to any particular animal source.

Reasons as to why this significant overlap in RT profiles was observed

which subsequently resulted in an inability to differentiate sources of

E. coli using this procedure are not known. One significant difference

between this study and a previous study by Carson et al. (2001) is the

diversity of the sample collection and, in particular, the type of

samples collected. Whereas Carson et al. collected individual fecal

samples from a confined geographic region; we collected E. coli from a

large geographic region; furthermore, the samples collected were

environmental water samples from lagoons or compost pits. It is

possible that the latter type of sample contains isolates that have been

subjected to various environmental stresses, which could potentially

cause mutations that adversely affect a ribotype profile. Therefore, a

combination of geographic and environmental variation may play a

significant role in affecting the ability of ribotyping to identify sources

of Escherichia coli in the environment.

One significant result of this study was the fact that ribotype

profiles from E. coli isolated from animals still differed significantly

from those obtained from human isolates. Therefore, it appears that

the method may have far reaching capacity for discriminating strictly








between isolates derived from animals from those derived from

humans. Overall, the correct classification of E. coli as being either

human or animal-derived was greater than 78%. Although there is

not an established standard of accuracy that has been defined for any

bacterial source tracking method, any method with a confidence level

over 50% has been considered as a worthwhile tool for predicting the

potential sources of fecal pollution in environmental waters.

Therefore, ribotyping continues to have merit as a viable molecular

tool to be used for this purpose.














CHAPTER 3
DEVELOPMENT OF A RAPID, PCR-BASED METHOD FOR USE IN
IDENTIFYING SOURCES OF FECAL POLLUTION

Many of the molecular methods that are currently used to

identify sources of fecal pollution are time-consuming, or involve the

use of expensive or specialized equipment. A rapid test method would

provide water quality managers with nearly real-time information so

that measures to correct the contamination problem could be taken

while the problem still exists or is easy to identify. Polymerase Chain

Reaction (PCR)- based methodologies are fast and reliable, and require

only specific primers, and a thermocycler, which is standard equipment

in most basic microbiology laboratories.

The purpose of this study was to develop a rapid method capable

of identifying specific regions within the genome of Escherichia coli

that can be used to differentiate organisms isolated from either human

or animal sources. Several methods, including AFLP, PCR ribotyping,

and rep-PCR were used to analyze the entire genome of E. coli for

significant or subtle genetic differences between organisms isolated

from different animal sources. Single genes were also sequenced and

analyzed for differences that could be useful in discriminating E. coli








isolates based on host origin. Specifically, sequence analyses were

performed on genes that code for fimbrial adhesins in E. coli. Once

unique sequences were found, specific PCR primers were developed

that are capable of identifying sources of E. coli and fecal pollution

with a moderate to high degree of accuracy as being from either

human or animal origin.

Characteristics of Eschericia coli Fimbrial Adhesins

The ability to adhere to mucosal surfaces on host cells is often a

limiting factor involved in the pathogenicity of an organism (Savage

and Fletcher 1985). The initial interaction between the mucosa of the

host cell and a bacterium is likely a random event, but subsequent

interactions may be the result of specific interaction between receptors

on the host cell and various adhesins present on the surface of the

bacterium (Savage and Fletcher 1985). Nevertheless, it is possible

and likely that bacterial adhesins and fimbriae play a specific role in

determining host-specificity of both pathogenic and non-pathogenic

bacteria.

Type 1 fimbriae are extracellular appendages present on the

surface of most strains of Escherichia coli and on many other members

of the family Enterobacteriaceae. They are helical, mannose-specific,

proteinaceous structures composed mainly of a single protein

monomer (FimA), but also consist of minor amounts of FimG, FimF,








and FimH (Savage and Fletcher 1985). The assembly of the repeating

major subunit (FimA) has a right-handed configuration with 3 1/8

subunits per revolution and a subunit pitch of 23.2 A, but the length of

each individual appendage is variable and dependent upon the

organism itself as well as on growth conditions (Brinton 1965).

The genetic sequence of FimA has been shown in previous

studies to be highly polymorphic (Li et al. 1997; Peek et al. 2001).

Sequence analysis of the fimA gene has already proven successful in

identifying DNA sequences capable of identifying or differentiating

Enterohemorrhagic (EHEC) Escherichia coli 0157:H7 from other E. coli

strains (Li et al. 1997; Roe et al. 2001). FimA has also been studied

for its ability to differentiate between closely related strains of

bacteria, including Escherichia coli and Salmonella typhimurium (Boyd

and Hartl 1998). In addition, FimA has been the subject of recent

publications that attempt to characterize and identify the sources)

and reasons for the observed genetic variability within the gene (Boyd

and Hartl 1998; Peek et al. 2001).

Approximately 30-70% of E. coli phenotypically display Type I

fimbriae (Orskov and Orskov, 1990; Tulles et al. 1992), but the gene

may be present in a higher percentage of isolates as it is known that

the gene is under a switch regulation by which expression can be








turned off in response to environmental and physiological conditions

(Olsen et al. 1998; Schembri et al. 1998).

Another type of fimbriae, P fimbriae, are a common genotypic

and phenotypic feature of uropathogenic E. coli. Their gene structure

is similar to that of type-1 fimbriae and consists of a major protein

subunit (PapA) as well as a fimbrial lectin (papG). Three different

papG (P fimbrial lectin) alleles are present in E. coli. These adhesins

bind specifically to Gal alpha 1-4 Gal-containing glycolipids on host

cells and their specificity for variations in different receptors has been

shown to correlate with host tropism (Bertin et al. 2000; Hansson et

al. 1995; Haslam et al. 1994; Marklund et al. 1992;). Just as in FimA,

the PapA gene is highly polymorphic and studies have investigated the

reasons) for this observed diversity (Boyd and Hartl 1998).

Experimental Approach

In this study, Amplified Fragment Length Polymorphism (AFLP),

PCR-ribotyping, repetitive element polymerase chain reaction (Rep-

PCR), and Restriction Fragment Length Polymorphism (RFLP) analyses

were used as "brute force" methodologies designed to detect genetic

differences in Escherichia coli isolated from human and animal sources.

The AFLP technique is based on the detection of genomic

restriction fragments by PCR amplification, and can be used for DNA of

any origin or complexity. Fingerprints are produced without prior








sequence knowledge using specific adapters ligated to the ends of

restriction fragments. Amplification is then carried out using adapter-

specific primers and fingerprints can be analyzed for specific, unique

differences evidenced by the presence or absence of a specific band or

banding pattern. Unlike many similar procedures, this procedure is

highly reproducible and the number of fragments detected in a single

reaction can be tuned by using primer sets of varying selectivity and

adjusting the stringency of the PCR reaction conditions.

PCR ribotyping uses PCR to amplify a fragment of the genomic

DNA which includes the spacer region between the genes coding for

16S and 23S rRNA. In previous studies, sequence length

polymorphisms in these spacer regions have been used in

differentiating closely related members of a number of bacterial genera

(Cartwright et al. 1995; Kostman et al. 1992; Matar et al. 1993).

Escherichia coli has been shown to possess seven alleles of the rRNA

gene cluster (Kiss et al. 1977).

Repetitive element-PCR uses primers corresponding to

interspersed repetitive DNA elements present in various locations

within the prokaryotic genome and PCR to generate highly specific and

reproducible genomic fingerprints. Three methods of repetitive

sequence analysis have been used with each targeting a specific family

of repetitive element. These include repetitive extragenic palindromic








(REP) sequences, Enterobacterial Repetitive Intergenic Consensus

(ERIC) sequences, and BOX elements, which are extragenic repeating

elements first described by Versalovic et al. (1994). The

corresponding protocols are referred to as REP-PCR, ERIC-PCR, and

BOX-PCR respectively, and rep-PCR collectively. Generally, the BOX

primer set is used in cases where a detailed characterization is needed

as this primer generates robust fingerprints, and generally yields a

highly complex pattern of amplified fragments. The REP primer set

generally generates a lower level of complexity, while the ERIC primer

set is more sensitive to sub-optimal PCR conditions, such as the

presence of contaminants in the DNA preparation. For these reasons,

Bacterial Source Tracking (BST) research has initially focused on the

use of the BOX primer in performing rep-PCR. The resulting genetic

fingerprint using BOX-PCR contains several bands, which can

subsequently be analyzed, categorized by host source, and used to

construct a database to which fingerprints from unknown isolates can

be compared. This method has been used previously in bacterial

source tracking studies as well as in several studies designed to

differentiate between closely related strains of bacteria (Dombek et al.

2000; Versalovic et al. 1994; Versalovic et al. 1998).

In a more specific approach, genes encoding fimbrial and

nonfimbrial adhesins present on the surface of many strains of








Escherichia coli were amplified using PCR, purified, cloned, sequenced,

and analyzed for the presence of genetic differences between

organisms isolated from human and animal sources.

Several genetic fingerprints were generated using the

aforementioned "brute-force" techniques, and specific, unique DNA

fragments were identified using the AFLP technique. These fragments

were cloned and sequenced, and PCR primers were developed that

selectively amplified these sequences. In addition, regions within the

genes coding for bacterial fimbriae were also used as templates for

PCR primer production. These tentative probes were then screened

against several, well-characterized E. coli from both human and animal

sources. The end result was the construction of several sets of PCR

primers that selectively amplify distinct portions of the E. coli genome

and are capable of discriminating human from nonhuman-derived

organisms depending on selective amplification of these gene

fragments.

Materials and Methods

Collection of Fecal Samples from Livestock and Humans

Compost fecal samples were collected from dairy, beef, swine,

and poultry farms located in southern, central, and northern Florida.

Samples were collected quarterly with sampling dates corresponding to

different seasons. Human isolates were obtained directly from human








volunteers, residential septic systems, and from sewage lines that

have no animal impact.

Isolation of Escherichia coli

Fecal samples were streaked on MacConkey agar plates (Difco)

within 24 hours of collection. Lactose-positive colonies were picked

and subculture into Tryptic Soy Broth (TSB, Difco) containing MUG

substrate (Sigma). MUG-positive isolates were presumed to be E. coli

and were verified using the IMViC series of tests (Indole, Methyl Red,

Voges-Proskauer, Citrate). Isolates exhibiting ++-- IMViC profiles

were confirmed as E. coli

AFLP Primers and Adapters

All oligonucleotides were synthesized by Genomechanix, Inc.

(Alachua, FL). The structure of the EcoRI adapter is:

5'-CTC GTA GAC TGC GTA CC-3'
3'-CAT CTG ACG CAT GGT TAA-5'

The structure of the MseI adapter is:

5'-GAC GAT GAG TCC TGA G-3'
3'-TA CTC AGG ACT CAT-5'

Primers were generated that were specific for adapter sequences

and contained either one or two selective bases at their 3' end to

increase their specificity and limit the number of AFLP products.

Primers containing one selective nucleotide were used in the

"preselective" amplification step and those containing two selective








nucleotides were used in the subsequent "selective" final amplification.

The sequence of the primer sets were as follows: Selective

nucleotides are in bold. (EcoRI 5'-GACTGCGTACC AATTC AC-3')

(MseI 5'- GATGAGTCCTGAGTAA CA-3').

Preparation of Genomic DNA and Adapter Ligation

Genomic DNA was extracted using the DNA Easy kit according to

manufacturer's instructions (Invitrogen, Inc., Carlsbad, CA). The

restriction and ligation steps were then performed simultaneously

according to the method of Vos et al. (1996) with minor modifications.

6.2 plL (~250 g) of genomic DNA was then mixed with an equal

volume of restriction- ligation mix, and the reaction was incubated for

3 hours at 370 C. After the reaction was completed, the mixture was

diluted in 187 pL of nuclease-free water and used as a template for

preselective PCR amplification.

AFLP Reactions

The AFLP reactions were performed using the primer sets

described previously. PCR reactions were carried out using HotStarTaq

DNA polymerase and reagents (Qiagen, Inc.). Both preselective and

selective amplification steps were performed and the reaction

conditions varied so as to decrease the number of AFLP fragments

observed after the selective amplification. The preselective

amplification was performed using the following protocol: 950 C for 15








minutes (to activate the HotStarTaq), followed by 30 cycles of 940 C

for 20 s, 560 C for 30 s, and 720 C for 2 min. A final extension at 720

C was then performed for 2 min. followed by 600 C for 30 minutes.

The selective amplification utilized 1 iLL of the product from the

preselective amplification as a template. This amplification used the

same reaction conditions as in the preselective amplification; however,

to increase specificity and decrease the number of AFLP products, the

selective amplification used an initial annealing temperature of 660 C

which was decreased one degree for nine subsequent cycles to 560 C

and was followed by an additional 20 cycles using the 560 C annealing

temperature. All amplification steps were performed using an

Eppendorf Mastercycler Thermocycler.

Repetitive Element Polvmerase Chain Reaction (rep-PCR)

Rep-PCR reactions were carried out on whole cells using the

procedure described by Versalovic et al. (1994) and the BOXA1R

primers described by Versalovic et al. (1998) and subsequently used

by Dombek et al. (2000). The sequence of the BOXA1R primer is

5'-CTACGGCAAGGCGACGCTGACG-3'.

PCR Amplification of rRNA Intergenic Spacer Regions

The PCR ribotyping procedure was performed using the primer

sets shown in Table 4. PCR reactions were carried out using

HotStarTaq polymerase and reagents (Qiagen, Inc.). The amplification








was carried out using the following conditions: 950 C for 15 minutes

(to activate the HotStarTaq), followed by 2 cycles of denaturation at

940 C for 1 min, 10 sec., annealing at 550 C for 2 min. 30 s, and

extension at 720 C for 3 min. Cycles 3-34 included the following:

denaturation at 940 C for 30 s, annealing at 550 C for 2 min 30s, and

extension at 720 C for 3 min. After the final cycle was complete, the

reaction was extended at 720 C for 10 min. Changing denaturing and

annealing times to 20 seconds and 30 seconds, respectively, increased

diversity of banding pattern and was used for subsequent reactions.

PCR Amplification of fimA and fimH Genes

Primers designed to amplify the major structural component of

type 1 fimbriae in E. coli (fimA) and its flanking regions (Li et al. 1997)

as well as the lectin of type 1 fimbriae (fimH) were developed using

published sequences (Li et al. 1997; GenBank) and are shown in Table

5. PCR reactions were performed in a 20 pL reaction mixture

containing 1X PCR buffer, 2.5 mM MgCl2, 200 gM of each of the four

deoxyribonucleotides, 0.3 iM of each primer, and 2.5 U of HotStarTaq

DNA polymerase (Qiagen). Amplification was performed for 30 cycles

consisting of 940C for 1 min, 650C for 1 min, and 720C for 1 min.,

followed by 10 min at 720 C. PCR products were separated on a 1.5%

agarose gel.













Table 4. Primer sets used to amplify ribosomal DNA intergenic spacer
regions in Escherichia coli

Primer Pair

rDNA 1 5'-AAGTCGTAACAAGGT-3'
5'-TACTGGTTCACTATCGGTCA-3'


rDNA 2 5'-TTGTAACACACGCCCGTCA-3'
5'-GGTACCTTAGATGTTTCAGT-3'


rDNA 3 5'-AAGTCGTAACAAGGT-3'
5'-GGTACCTTAGATGTTTCAGT-3'














Table 5. PCR primers used to amplify the fimA and fimH genes in E.
coli
Primer Name Sequence Product
size (bp)

FimA fwd 5'-ACGTTTCTGTGGCTCGACGCATCT-3' 850
FimA rev 5'-ACGTCCCTGAACCTGGGTAGGTTA-3'


FimH fwd 5'-TACCGCTATCCCTATTGGCGG-3' 480
FimH rev 5'-ACATCACGAGCAGAAACATC-3'








PCR Amplification of papG Genes in Escherichia coli


PCR reactions to amplify papG genes were performed in a 20 iiL

reaction mixture containing 1X PCR buffer, 2.5 mM MgCl2, 200 PM of

each of the four deoxyribonucleotides, 0.3 pM of each primer, and 2.5

U of HotStarTaq DNA polymerase (Qiagen). An initial step of 15

minutes at 950 was performed to activate the DNA polymerase.

Amplification was performed for 30 cycles consisting of denaturation

(940 for 1 min.), annealing (560 for 30 s), and extension (720 for 2

min.) This was followed by a final extension at 720 for 10 min. Primer

pairs specific for each of the three classes of papG genes were

identical to those used by Johnson and Brown (1996) (Table 6).

Restriction Enzyme Analysis of rDNA. fimA and fimH Genes

Five pL of each PCR-amplified rDNA product was used for

digestion with several restriction endonucleases according to the

manufacturer's instructions (New England BioLabs, Inc., Beverly,

Mass.). Several restriction enzymes were used: Alul, HaeIII, EcoRI,

HindIII, BamHI, Sau3AI, and Msel. FimA and FimH PCR products

(81iL) were used directly for restriction digestion with 3 U of Alul (New

England Biolabs) without further purification at 370 C for one hour.














Table 6. Primer sets used to amplify variant papG genes in Escherichia
coli

product
PapG class Primer pair size (bp)

Class I 5'-TCGTGCTCAGGTCCGGAATTT-3' 461
5'-TGGCATCCCCCAACATTATCG-3'


Class II 5'-GGGATGAGCGGGCCTTTGAT-3' 190
5'-CGGGCCCCCAAGTAACTCG-3'


Class III 5'-GGCCTGCAATGGATTTACCTGG-3' 258
5'-CCACCAAATGACCATGCCAGAC-3'








Gel Analysis

All AFLP, RFLP, and various PCR products were analyzed using

either 1.5% agarose or 5% polyacrylamide gel electrophoresis. DNA

was viewed using GelStar nucleic acid stain (Biowhittaker, Inc.) and

UV light or silver staining, respectively. Unique bands were identified

by visual analysis.

Excision of Unique Bands and DNA Recovery

Following the various fingerprinting procedures, bands unique to

either human source or nonhuman source E. coli were identified by

visual analysis. DNA from polyacrylamide gels was extracted with a

Microcon purification kit (Millipore Inc.) and resuspended in nuclease-

free deionized water. DNA bands from agarose gels were extracted

using a gel extraction kit (Qiagen, Inc.) and prepared for cloning

according to manufacturer's specifications.

Cloning of PCR products and Fimbrial Genes

Following gel extraction and DNA recovery, cloning was carried

out using a TOPO TA Cloning kit (Invitrogen, Carlsbad, CA). Amplicons

were ligated into the pCR 2.1 vector and transformed into competent

E. coli TOP10F' cells. Transformed cells were plated on Luria-Bertani

agar supplemented with 100 pg/mL ampicillin, isopropyl-p-D-

thiogalactopyranoside (IPTG), and 5-bromo-4-chloro-3-indolyl-Beta-D-

galactoside (X-gal).








Analysis of Positive Clones

The pCR 2.1 TOPO TA cloning vector is a lacZ- based system and

analysis of positive clones was performed using blue/white screening.

Plasmid Isolation and DNA Sequencing

Plasmids were extracted using a plasmid miniprep kit (Qiagen,

Inc.) according to manufacturer's instructions. Dideoxy sequencing

reactions were performed using a Perkin Elmer GeneAmp PCR System

9600 (Perkin Elmer-Cetus, Norwalk, Conn.) Extension products were

separated and read with a U-COR DNA Sequencer model 4000L.

Sequence and Phvloaenetic Analyses of FimA Gene

Ten unique FimA sequences from both human and animal-

derived Escherichia coli isolates were identified in this study and were

combined with data from 11 previously published E. coli fimA

sequences (GENBANK). Isolate designations and sources are depicted

in Table 7. The sequences were aligned and compared using Biowire

Jellyfish software, and phylogenetic analyses were conducted using

Clustalw and Treeview software. Additional E. coli isolates were

characterized; however, some overlap was observed in general genetic

sequence of the FimA gene. These isolates were used in confirmatory

PCR tests as well as in additional ribotyping analyses.









Table 7. Escherichia coli isolates used in phylogenetic analyses

FimA GenBank No. Strain I.D. designation Host Reference
Information

None Group I (AA1) Human This study

AF206652 EPEC (Group I) Human Peek et al.
(2001)
AF206658 0157:H7 (Group I) Human Peek et al.

AF206659 0157:H7 (Group I) Human Peek et al.

U20815 0157:H7 (Group I) Human Unpublished

M27603 Uropathogenic (Group I) Human Orndorff &
Falkow (1985)

X00981 K-12 (Group I) Human Klemm (1984)

None PS171 (Group I) Poultryl This study

None PN233 (Group I) Poultry2 This study

AF206656 EPEC (no serogroup des.) Human Peek et al.

None Group II (ET1) Humani This study

None Group II (ET2) Human2 This study

None Group II (G1) Human3 This study

AF206657 055:H7 (Group II) Human Peek et al.

D13186 0:78 (Group II) Avian Sekizaki et al.
(1993)
None BC232 (Group II) Beef This study

None PS175 (Group II) Poultry This study

None Group III (E19) Human This study

Y10902 Group III Human Unpublished

None Group III (DC8) Dairy cow This study

Z37500 02:K1 (Group III) Avian Marc & Dho-
Moulin (1996)








PCR Amplification of DNA Sequences Within the FimA Gene

Sequence analysis of the FimA gene revealed differences

between E. coli isolates from human and animal sources and six

separate primers (3 forward, 3 reverse) were developed that were

complementary to these regions. Nested PCR reactions were

performed on PCR-amplified FimA genes (I1L of diluted PCR product)

using one of the three TMS forward primers (TMS1, TMS2, and TMS3)

and three separate reverse primers, TMSgg,TMSag, and TMSct (Table

8; explanation of source of primers in results section). The reactions

were carried out in 20gL volumes containing 1X PCR buffer, 200pM

each dNTP, 0.3pM of each primer, and 2.5 U of HotStarTaq DNA

polymerase. The cycling conditions were as follows: 950 C for 15

minutes (to activate HotStarTaq), followed by 30 cycles of 940 C for 1

min., 580 C for 1 min., and 720 C for 1 min.

Results

Collection of E. coli from Florida livestock and Human Sources

Fecal samples from humans and animals were identical to those

collected and analyzed in the ribotyping study described previously.

Escherichia coli were either isolated separately or isolates that had

been ribotyped were analyzed for the presence of discriminating

sequences. Only isolates displaying a definitive human or nonhuman












Table 8. Sequences of TMS and REV primer sets.


Primer Sequence

TMS1 fwd 5'-ACGGCGATTGATGCGGG-3'

TMS2 fwd 5'-TACGGCAATTGATCGTACG-3'

TMS3 fwd 5'-GACTGAGATTGACAGAGCT-3'

TMS3' fwd 5'-CTGGCTGAAACTACACCAC-3'

TMS4 fwd 5'-GTACCGCAATTGATGGCICT -3'

REVgg* 5'-GCAGCACCCGGGGTTGAGG-3'

REVct 5'-GCAGCACCCGGGGTTGACT-3'

REVag 5'-GCAGCACCCGGGGTTGAAG-3'
*The last two 3' nucleotides of the REV primers are unique. Underlined nucleotide is
an intentional mismatch to increase specificity of the primer. TMS3' fwd and TMS4
fwd are alternative primers. A 437 bp product is generated using TMS3' fwd primer.
TMS4 fwd amplifies a 212 bp product in nonhuman source isolates along with REVgg
that are not identified by the TMS1, TMS2, or TMS3 forward primers.








ribotype profile were used; however, additional isolates were not

ribotyped prior to analysis of FimA sequences.

AFLP reactions

AFLP products were analyzed by both agarose gel

electrophoresis (Figure 4) and polyacrylamide gel electrophoresis

(Figure 5). Several unique bands were identified and were purified

and cloned for sequencing.

Screening of Primers Derived from AFLP Fragments

Once clones were sequenced, primers were designed that

flanked the cloned regions (Table 9). Eight primer sets were

developed but were not useful for differentiating sources of E. coli.

Interesting results were obtained using one primer set (set A),

however, and are shown in Figure 6. This primer set amplified several

regions within the E. coli genome and resulted in reproducible banding

patterns unique to different isolates much as has been reported using

rep-PCR (Dombek et al. 2001). Although no single band was amplified

using this set that was capable of discriminating E. coli based on

source, groups of bands showed up at different frequencies from

isolates from different sources. In addition, restriction digestion (Alul)

of the PCR products generated using this primer set produced

additional unique patterns that allowed for further differentiation of

unknown E. coli isolates (Figure 7). For this reason, this primer set
































Figure 4. AFLP patterns observed in a 2% agarose gel. Lanes 1-
4 are patterns from human isolates. Lanes 5-8 are patterns
from nonhuman isolates. Arrows show unique bands.



















61









L 1 2 3 4 5 6 7 8 9 10 11 12 L


t -. fgla iyr'j gmK-:. : .- .. :_. *. .-_a_ .-
Figure 5. AFLP patterns observed on 5% polyacrylamide gel. Lanes
1,2,5,6,7,and 8 are profiles from human-derived E. coli. Lanes
3,4,9,10,11,and 12 are profiles from nonhuman derived E. coli.














Table 9. Primer sets derived from unique DNA fragments generated
by Amplified Fragment Length Polymorphism

Designation Primer Pair Product size
(bp)

Afwd 5'-GCCCCTGATTGTCCGCCTGCCGC-3' multiple
Arev 5'-TTACACAGGTATCCCCAAAAGG-3'

A(2)fwd 5'-CAGGTATCCCCAAAAGG-3' 362
A(2)rev 5'-TAGCCCCTGATTGTCCGC-3'

A(3)fwd 5'-GGTTTACACAGGTATC-3' 418
A(3)rev 5'-ACGTAGCCCCTGATTG-3'

Bfwd 5'-ATCAGATTGTCCAAAAC-3' 642
Brev 5'-ACAGGTATCCCCAAAAAG-3'

Efwd 5'-TTACACAGGTATCCCCAAAAGG-3' 202
Erev 5'-ATCAGATTGTCCAAAAACGGGG-3'

E(2)fwd 5'-5'-TCATCGGCAAAATGGTCC-3' 152
E(2)rev 5'-GTATTGCAGCAGGAGCGA-3'

E'fwd 5'-GAGTCCAGGCGTTATGAATAATC-3' 254
E'rev 5'-GAATGCAGAAATGTTGATGGGC-3'

Ffwd 5'-AGTTTGGTGCCATCG-3' multiple
Frev 5'-GCAAAATCCCTCTCG-3'













M 1 2 3 4 5 6 7 8 M


Figure 6. Rep-PCR fingerprints generated using primer set A. Lanes
1-4 are animal isolates and Lanes 5-8 are human isolates. The
molecular weight marker is a pGEM HindIII digest (Promega, Inc.)














M 1 2 3 4 5 6 7 8 M


Figure 7. RFLP of rep-PCR products generated using primer set
A. Lanes 1-4 are animal isolates and Lanes 5-8 are human
isolates. Wells correspond to rep-PCR products in figure 6. The
molecular weight marker is a pGEM HindIII digest (Promega,
Inc.)








may prove useful as a fingerprinting primer if a reference database

were to be constructed using fingerprints of isolates from known

sources. This result is outside the scope of this study, as we are

seeking to avoid reference-based analyses that rely on comparisons to

previously characterized isolates.

Repetitive Element Polvmerase Chain Reaction (rep-PCR)

Because primer A derived from a single AFLP fragment was

shown to possess the capacity to amplify several regions within the E.

coli genome resulting in multiple bands, the use of the Rep-PCR

method developed by Versalovic et al. (1994) and later used by

Dombek et al. (2000) was applied to Escherichia coli isolated from

humans and livestock in the state of Florida. Several isolates were

fingerprinted and showed multiple banding profiles (data not shown).

PCR Amplification of rDNA Interoenic Spacer Regions

Three primer sets were used to amplify the intergenic spacer

regions between the genes that code for 16S and 23S rRNA in E. coli.

Primer set 1 provided the most variable and discriminating patterns

initially (Figure 8). Primer sets 2 and 3 provided less information to be

used for discriminatory analysis. This technique, however, did not

result in the identification of a single band or bands that had

discriminatory power. Similar to results obtained with primer set A, a

reference database would need to be constructed in order to compare














M 2 3 4 5 6 7 8 9 M


Figure 8. Amplification of rDNA intergenic spacer regions in
Escherichia coli. Lanes 2-6 are nonhuman isolates. Lanes 7-9
are human isolates. The molecular weight marker is a pGEM
HindIII digest (Promega, Inc.). Arrows point to doublets that
are most discriminatory using this procedure. (Note that animal
source isolates have lower molecular weight doublets than
human source isolates).








profiles from unknown isolates to those generated using known

isolates.

Cloning and Seauence Analysis of PaDG genes in E. coli

PCR was used to amplify the variant papG genes (classes I, II,

and III) of Escherichia coli isolated from humans (4) and animal (4)

sources. Only the papGII allele was detected in these isolates and all

eight PCR fragments were cloned and sequenced. Sequence analysis

revealed no consistent or significant differences between E. coli

isolated from humans and those isolated from animals. Additional

isolates were screened for the presence of either papGI or papGIII

alleles but the genes were not detected. Because of the absence of

the other two papG alleles and the homogeneity of the papGII gene in

these isolates, no further organisms were characterized on the basis of

this gene.

PCR Amplification of FimA and FimH Genes in E. coli

Amplification of the fimA gene in E. coli produced a 850 bp

fragment (Figure 9). Amplification of a region within the fimH gene

produced a 480 bp fragment (Figure 10).

RFLP Profiles of PCR-Amolified rDNA and Fim Genes

Restriction digestion of rDNA amplicons produced several

patterns, indicating the highly polymorphic nature of the ribosomal








intergenic spacer region. No single restriction pattern was unique to

either human or animal isolates (Data not shown).

Restriction digestion of FimA genes using Alul are shown in

Figure 11. No single RFLP pattern provided any discriminatory power,

but the diversity of RFLP patterns prompted further investigation of the

gene. Subsequent sequence analysis revealed that significant

sequence differences are present within isolates exhibiting similar or

identical RFLP patterns. Restriction digestion of the FimH PCR product

by various enzymes failed to produce any variability in restriction

patterns.

Cloning and Seouence Analysis of FimH Genes in Escherichia coli

FimH genes (E. coli) from human (3) and animal (2) sources

were cloned and sequenced. Sequence analysis revealed no significant

or consistent variability within the gene between isolates from different

host sources. Minor variations were detected that resulted in changes

in amino acid composition and previous data has shown that a change

of a single amino acid can significantly alter lectin binding specificity

(Harris et al. 2001; Schembri et al. 2001); however, these differences

were not conserved within one group of E. coli isolates and this gene

was not investigated further. Cloning and sequence analysis of FimA

genes was discussed previously and isolates characterized in this study

are listed in Table 7.














M 1 2 3 4 5 6 78 M


Figure 9. Amplification of the gene encoding the major
structural component (FimA) of type-I fimbriae in Escherichia
coll. Lane 1 is a FimA(-) animal isolate. Lanes 2-4 are animal
isolates. Lanes 5-8 are human isolates. The molecular weight
marker is a pGEM HindIII digest (Promega).



































Figure 10. Amplification of the gene encoding the lectin
component (FimH) of type-I fimbriae in Escherichia coli
Lanes 1-4 are animal isolates. Lanes 5-8 are human isolates.
The molecular weight marker is a pGEM HindIII digest
(Promega).


I L 7 R














j -7 0 tIA I I


Figure 11. RFLP patterns observed after Alul restriction enzyme
digestion of the fimA gene in Escherichia coli. Lanes 1-6 are
human isolates. Lanes 7-11 are animal isolates.








DNA Alignment Analysis of FimA Genes


Alignment analysis of human and animal-derived FimA genes

from Groups I, II, and III, revealed several regions of genetic diversity

(Figures 12,13,14,15). Group-specific forward primers, TMS1 (bp307-

312), TMS2 (bp307-312), and TMS3 (bp313-318) were

complementary to the most conserved cluster of diversity. Group III

isolates also contained a six base pair insertion a positions 78-83 and

this area was used to construct an alternative primer set, TMS3' fwd

(Table 8). Several other differences were also identified within the

groups, but these differences were less conserved within organisms

isolated from the same host. One region in particular, however,

contained two base changes (bp495-496 in groups I and II; bp500-

501 in Group II) that corresponded more consistently with host source

(Figures 12-15). In group I, which contains predominantly human

isolates, an adenine and guanine at positions 495 and 496 are unique

to human pathogenic E. coli isolates (EHEC, EPEC) while two cytosines

at this position are present in organisms isolated from humans, and to

a lesser extent, animal isolates. In group II, the trend is reversed,

and Group III isolates possess the same discriminating downstream

sequences as Group I, however, their position is shifted to positions

500 and 501 due to upstream insertions. The differences at










GroupI Poult. I

GroupI Human w


Groupl Pouit. 5
GroupI Human 5 6mmm1w


GroupI P olutt.ii
GroupI Human 113s




GroupI Poult. 127
GroupI Human 6027 -0 ew


GroupI Poult.221 i
GroupI Human 22


GroupI Poult. it.11- 2 76-
GroupI Human 2744


GroupI Poult. ot 49-
GroupI Human 3312


GroupI Poul outt. 3
Growpl Human 38 : ~jAC


Group! Pouit.441 *
Groups Human 441L I ~ i i


GroupI Posit4 ..... ....
Group! Human 496~

Figure 12. DNA sequence alignments of FimA genes from group I E.
coli isolates. TMS and REV primers are highlighted in gray.










GrouplI Humanl 1~"
GroupII Beef


GroupII Human 56



Groupli Beef



GroupI Hun n616
GroupII Beef Ii656 qu




GroupIl Hmnnana n2...
GroupIl Beef 220


GroupII Human27A .equeneg
GroupiI Beef 27T an R ~ ir


GroupII Human_33_0w0nmu -
GroupII Beef 3 3 0


GroupII Human38ma 38 (CI
GroupI Beef 38858-...


GrouplI Hnmaumnn440AI
Groupll Bef 4440 218CG3 -A'-T J-


GroupII
GroupII Beef 45w

Figure 13. DNA sequence alignments of FimA genes from group II E.
coil isolates. TMS and REV primers are highlighted in gray.









GroupIIIDairy
GroupIIIlumaxn

GroupIIIDairy
GroupIIHuman


GroupIii ilayanll ...
GRoAp i ipi~um anl G mTTTAPCCGCTCGATT-TGA3GT-- GA-


GroupIIDairy550 55


GrouplIIHuman2l 555


FGroupare DN alifro rop27 I`s
GroupIII~airy37.


GroupIIIHuman331 AwmAmc




GroupIIIDairy44 -



GroupIIIDairy49


GroupIIIDairy550= 554
GroupIIIHuman551 555

Figure 14. DNA sequence alignments of FimA genes from group III E.
coli isolates. TMS and REV primers are highlighted in gray.
Alternative fwd primer set is also highlighted (bp70-83).


1-- ... .


1rTGAkATAAkT C T-4TTTTCCTTTCTGznTC-









GIIHuman 1 H
GIIIHuman 1

GI Human 1
GII Human61 MKESSMc&TMMI ------ E-EMAMMEjHEM|e
GIIIHuman61
GI Human 61

GII Human221
GIIIHumjanll8
GI Human 112


GIIIHumanl3luAn'OC4


Gil Humai24
GIIIHman230



GI Human 29
Gil Humana20-- C i n"

GIIIHuman33 226MEMIJEaM
GI Human 2336 3 6 CM C .



Gil Human339tF

GIIIHuman34I98II
GI Human 39233M


GIIIHuman3J459a 4 WGaCG
GI Human C44GC39WcMIC
GII IH=a85c^^jBlslHtgc


GII Human54 55549
GIIIHuman5105n 555
GI Human 50 549

Figure 15. DNA sequence alignments of FimA genes from E. coli
(groups I, II, and III).








these positions served as the template for the source-specific reverse

primers REVgg, REVct, and REVag (Table 8).

Amino Acid Analysis of FimA Genes

Sequenced FimA genes were translated and analyzed using

computer software (DNA Strider) in order to determine if the observed

differences in DNA sequence also corresponded to phenotypic changes

in the FimA protein. Figures 16-18 depict the amino acid sequence

from groups I, II, and III, respectively. All regions within the gene

that were used for primer development also contained unique amino

acids. This observation supports the possibility that these changes

potentially alter function and suggests a relationship between

phenotype and host source. In group I, residues 103 (alanine) and

104 (glycine) were unique to this group. Likewise, group II isolates

had unique amino acids (arginine, threonine) at these positions.

Group III isolates had discriminating amino acids serinee, alanine) at

positions 105 and 106. Furthermore, Group I isolates with a glutamic

acid at position 165 are strictly human pathogens, while some overlap

is observed between isolates containing an alanine at position 165.

Human isolates in group II contain an alanine at position 165, while

animal isolates contain a glutamic acid. Human isolates in group III

contain a glutamic acid at position 167, while animal isolates in this

group contain an alanine at this position.










1/1 31/11
ATG AAA ATT AAA ACT CTG GCA ATC GTT GTT CTG TCG GCT CTG TCC CTC AGT TCT ACA gCG
Met lys ile lys thr leu ala ile val val leu ser ala leu ser leu ser ser thr ala
61/21 91/31
GCT CTG GCC OCT GCC ACG ACG GTT AAT GGT GGG ACC GTT CAC TTT AAA GGG GAA TT GTT
ala leu ala ala ala thr thr val asn gly gly thr val his phe lys gly glu val val
121/41 151/51
AAC GCC gCT TGC GCA GTT GAT GCA GGC TCT GTT GAT CAA ACC GTT CAG TTA GGA CAS GTT
asn ala ala cys ala val asp ala gly ser val asp gln thr val gln leu gly gin val
181/61 211/71
CGT ACC GCA TCG CTG GCA CAG GAC GGA GCA ACC AGT TCT GCT GTC GGT TTT AAC ATT CAR
arg thr ala ser leu ala gln asp gly ala thr ser ser ala val gly phe asn ile gin
241/81 271/91
CTG AAT GAT TGC GAT ACC AAT GTT GCA TCT AAA GCC GCT GTT GCC TTT TTA GGT ACG GOC
leu asn asp cys asp thr asn val ala ser lys ala ala val ala phe leu gly thr ala
301/101 331/111
ATT GAT GCO GOT CAT ACC AAC GTT CTG GCT CTG CAG AGT TCA GCT GCG GGT AGC SCA ACA
ile asp ala gly his thr asm val leu ala leu gin ser ser ala ala gly ser ala thr
361/121 391/131
AAC oTT GGT GOT CA0 ATC CTG GAC AGA ACG GGT OCT GCg CTG ACG CTG GAT GGT GCg ACA
asn val gly val gin ile leu asp arg thr gly ala ala leu thr leu asp gly ala thr
421/141 451/151
TTC AGT GAG CAA ACA ACC CTG AT AAT C GGT ACT AAC ACC ATT CCG TtC CAB GCG COT TAT
phe ser qlu gin thr thr leu asn asn gly thr asn thr ile pro phe gin ala arg tyr
481/161 511/171
TAT GCA ATC GGC CA ACC CCG GGT GCT GCT AAT CG GAT GCG ACC TTC AA GTT CAB
tyr ala ile gly ala thr pro gly ala ala asn ala asp ala thr phe lys val gin
541/181
TAT CAA TAA
tyr gin OCH

Figure 16. DNA and amino acid sequence of FimA gene from Group I
Escherichia coli isolates. Amino acid differences are highlighted. Residue
165 shows both amino acids present at this position in human and animal
isolates.










1/1 31/11
ATG AAA ATT AAA ACT CTG GCA ATC GTT GTT CTG TCG GTT CTG TCC CTC AT TC CA gC
Met lys ile lys thr leu ala ile val val leu ser val leu ser leu ser ser ala ala
61/21 91/31
GCT CTG GCC GAT ACT ACG ACG GTA AAT GOT GGG ACC GTT CAC TTT AAA GoG GA oTT GTT
ala leu ala asp thr thr thr val asn gly gly thr val his phe lys gly glu val val
121/41 151/51
AAC GCC gCT TGC GCA GTT SAT GCA GGC TCT GTT GaT CAA ACC GTT CAB TIA GGC CAG GTT
asn ala ala cys ala val asp ala gly ser val asp gin thr val gin leu gly gin val
181/61 211/71
CGT ACC GCT AGC CTG AAG CAG GCT GGA GCA ACC AGC TCT 0CC GTT GGT TTT AAC ATT CA
arg thr ala ser leu lys gin ala gly ala thr ser ser ala val gly phe asn ile gin
241/81 271/91
CCG AAT GAT TOC GAT ACC ACT OTT GCC ACA AAA GCC GCT GTT GCC TTC TEA GGT ACG GCA
pro asn asp cys asp thr thr val ala thr lys ala ala val ala phe len gly thr ala
301/101 331/111
ATT GAt cgT &CO CAT ACT OAT GTA CTG OCT CTG CAG AGT TCA GCT GCG GGT AGC GCA ACA
ile asp arg thr his thr asp val leu ala leu gin ser ser ala ala gly ser ala thr
361/121 391/131
AAC GTT GGT GTG CAG ATC CTG AC AGA ACG GT T OCT GCG CTS GCO CTG GAC GGT G5G ACA
asn val gly val gin ie leu asp arg thr gly ala ala leu ala leu asp gly ala thr
421/141 451/151
TTT AGT TCA GAA ACA ACC CTG AAT AAC SGA ACC AAC ACC ATT CCG TTC CAB GCG COT TAT
phe ser ser glu thr thr leu asn asn gly thr asn thr lie pro phe gin ala arg ty
481/161 511/171
TTT GCA ACC CA ACC TCCCG GGT GCT GCT AAT GCG SAT GC CC TTC AAG GTT CA
phe ala thr gly ala thr pro gly ala ala asn ala asp ala thr phe lys val gin
541/181
TAT CAA TAA
tyr gin OCH


Figure 17. DNA and amino acid sequence of FimA gene from Group II
Escherichia coli isolates. Amino acid differences are highlighted.
Residue 165 shows both amino acids present at this position in human
and animal isolates.










1/1 31/11
ATG AAA ATT AAA ACT CTG GCG ATT GTT GTT CTG TCG GCT CTG TCC CTG ACT TCT ACA GCG
Met lys ile lys thr leu ala ile val val leu ser ala leu ser leu ser ser thr ala
61/21 91/31
GCT CTG GCT GAA ACT ACA CCC ACG ACG GTA AAT GGT GGG ACC GTT CAC TTT AAA GGG GAA
ala leu ala gin thr thr pro thr thr val asn gly gly thr val his phe lys gly glu
121/41 151/51
GTT GTT AAC GCC GCT TGC GCA GTT GAT GCA GGC TCT GTT GAT CAA ACC GTT CAG TTG GGC
val val asn ala ala cys ala val asp ala gly ser val asp gln thr val gin len gly
181/61 211/71
CAG GTT CGT ACC GCT AGT CTG AAG CA ACT GGA GCA ACC AGC TCT GCT GTC GG TTT AAC
gin val arg thr ala ser leu lys gin thr glyla t er e ala a gly pe asn
241/81 271/91
ATT CAG CTG AAT GAT TGC GAT ACC AOT GTT GCC ACA AAA GCC GCT GTT GCC TTC TTS GMS
ile gin leu asn asp cys asp thr ser val ala thr lys ala ala val ala phe leu gly
301/101 331/111
ACT GCG ATT GAC AOT GCT CAT CCT AAA GTA CTG GCT CTG CAM AGT TCA GCT GCG GGT AGC
thr ala ile asp ser ala his pro lys val leu ala leu gin ser ser ala ala gly ser
361/121 391/131
GCA ACA AAT OTT GGT GTG CAB ATA CTG GAC AGA ACA GGA AIT QAG CTG AG- CTG 50C GGT
ala thr asn val gly val gn le leu asp arg thr gly asm glu leu thr leu asp gly
421/141 451/151
GCG ACA TTT AGT SCA CAA ACA ACC TTS AAT AAC GGT ACC AAC ACC ATT CCG TTC CA GCG
ala thr phe ser ala gin thr thr leu asn asn gly thr asn thr ile pro phe gin ala
481/161 511/171
CGT TAT TAT GCA ATC GGC GCA AC CCG GGC GCT GCT AAT CG GAT GCG ACC TTC AAG
arg tyr tyr ala ile gly ala thr pro gly ala ala asn ala asp ala thr phe lys
541/181
GTT CAG TAT CAA TAA
val gin tyr gin OCH


Figure 18. DNA and amino acid sequence of FimA gene from Groups
III Escherichia coli isolates. Amino acid differences are highlighted.
Residue 167 shows both amino acids present at this position in human
and animal isolates.








HydroDhilicitv Profile of Type 1 Fimbrial Subunit (FimA) Protein

Because genetic differences within the FimA gene were clustered

together, the hydrophilicity profile for the FimA protein was calculated

using the method of Hopp et al. (1981) in order to identify regions that

may be exposed to the environment and would therefore be more apt

to be affected by diversifying selection. The hydrophilicity profile is

shown in Figure 19. As would be expected, the N-terminal region is

highly hydrophobic, which is characteristic of a region harboring the

signal peptide for a membrane-bound structure. Several hydrophilic

maxima are also evident, with the most prominent one encompassing

residues 101-107. This peak corresponds to the polymorphic region

within FimA that is the basis of the TMS forward primer sets. Other

minor peaks correspond to additional areas exhibiting additional

genetic variation within the FimA gene.

Phvlogenetic Analysis of FimA Genes

Phylogenetic analysis of FimA genes cloned in this study are

shown in Figures 20 and 21. As can be seen in the Figures, the three

groups cluster well in the unrooted tree analysis. The more complex

rooted analysis, using the isolates cloned in this study as well as other

published FimA sequences, also shows the groups clustering together,

and a separation of human and animal isolates.













1 i---






e i
0.5$- -t- t


S O f|- MA M lO rA CD? M 1O r, Li
o I I lO rL w m 0 -2 ul
-0.5




-1.5 !

-2
Sequence position


Figure 19. Hydrophilicity profile of type 1 fimbrial subunit protein
(FimA) in Escherichia coli.


















/ 1 !pouMy"

GGoplllpi [xernt t hul i
G-01 GI b~
















Groull2 tu POnLO


0.01


Figure 20. Unrooted phylogenetic tree showing genetic relationship
between FimA genes from human and animal Escherichia coli isolates
sequenced in this study. Scale bar = 1% divergence.












Group Human

AF20065M Human 0157 H7

AF206852 4uman EPEC

AF20M68 Human 0157 H7

U20815 Human 0157 H7


AF2066S Human EPEC

Goupll Beef

AP200687 Human 055 HT

Group Poultry


S roupil HumSn2

3roupllt Dairy
----- Gm "oh 0
Omupff Human

Y092 Human

Z3750DAvian 02 Ki

Group PoutAyl

Groupt Pultry2

M03 Human

XOOB3 K-12
0.1



Figure 21. Phylogenetic tree showing genetic relationship between
FimA genes from human and animal Escherichia coli isolates
sequenced in this study and in published literature. Scale bar = 10%
divergence.









Identification of E. coli Isolates by TMS and REV Primer Sets

Figure 22 shows a schematic of how the TMS and REV primers

are used to identify the source of unknown E. coli isolates using a PCR-

amplified FimA gene as template. A positive result is a 212 bp product

The results of screening several E. coli isolates from various sources

are shown in Table 10. For identification of a single isolate, nine

separate PCR reactions must be performed. Each of the three forward

TMS primers, (TMS1, TMS2, and TMS3), must be used separately with

each of the reverse primers, REVgg, REVct, and REVag. A negative

PCR result is considered indicative of a nonhuman isolate. Some

isolates that cannot be identified using the three TMS forward primers

can be identified using an alternative primer combination (TMS4,

REVgg; Table 8). A positive PCR product is considered as a nonhuman

E. coli isolate. This fimbrial sequence was not observed in this study,

however. In addition, no isolates in this study were amplified using

the REVag reverse primer. The TMS4 forward primer and REVag

reverse primer were developed from fimbrial sequences obtained from

GENBANK and published literature (Peek et al. 2001). The overall

correct classification rate of isolates in the Florida collection is 70%.

Beef, Dairy, and Swine isolates were correctly identified as nonhuman

at a rate of 68%, 79%, and 96%, respectively. Poultry isolates were

only positively identified at 55% of the time, however. The reasons










FimAiwhola
cWlHo


TMS1 fti w/
I I
EYt KEVYl
19 HS


UTM2 fad w/
I I


KEV
HS


NEVH
NHS


TMS ftw w/

KEYVas rEVg KEVY
HS hUraid NHS


Figure 22. Schematic representation of sequence of primer usage to
identify Human and Animal-derived FimA genes in Escherichia coli.
*HS = human source isolate; NHS = nonhuman source isolate












Table 10. Human/nonhuman classification of Escherichia coli using
TMS and REV primer sets

No. (%) of isolates classified as:
Source (No. of Human Nonhuman
isolates)

Beef (25) 8 (32) 17 (68)


Dairy (56) 12 (21) 44 (79)


Swine (45) 2 (4) 43 (96)


Poultry (38) 17 (45) 21 (55)


Total Human (104) 65 (63) 39 (37)


Total Nonhuman 39 (23) 125 (77)
(164)
* TMS primers do not differentiate between species. Absence of a PCR
product is classified as nonhuman.




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