Commercial Soils As a Potential Vehicle for Antibiotic Resistance Transmission

Commercial Soils as a Potential Vehicle for Antibiotic Resistance Transmission

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

Christina Grace Bellinger

Graduate Program in Food Science and Technology

The Ohio State University

2017

Master's Examination Committee:

Hua H. Wang, Advisor

John Litchfield

Luis Rodriguez-Saona

Copyrighted by

Christina Grace Bellinger

2017

Abstract

There is growing concern as to the continued ability of antibiotics in clinical settings to be effective due to increases in antibiotic resistance in pathogens. This increase is a major threat to human health, with approximately 23,000 annually killed by untreatable bacteria in the United States alone. The environment is a potential reservoir for antibiotic resistance genes and soil is high in bacterial diversity. This study aims to analyze augmented soils, especially a pilot study on their resistome, to assess the potential risk of commercial soil in disseminating antibiotic resistant bacteria to humans and the environment. A study of fifteen commercial soils was conducted using culture-dependent and metagenomic methods, with six noncommercial garden and general environmental soils used for comparison. Serially diluted soil samples were plated on plate count agar

(PCA) and individual colonies were picked and transferred to antibiotic-supplemented agar using the following types and concentrations: ampicillin (16g/L), tetracycline

(100g/L), erythromycin (100g/L), and lincomycin (16mg/L). DNA was extracted from soil samples, pooled and sequenced by high throughput sequencing. Primers were designed for three resistance genes in relative high abundance, aac(3)-Id, catB6, and

MacB. PCR amplification to detect these genes in individual samples was conducted. All samples studied lacked response to at least one antibiotic using culturing methods, on average 66% to ampicillin, 77% to lincomycin, 15% to erythromycin, and 9% to tetracycline. A total of 59 total phyla were represented in the pooled soil sample, representing 2118 different genera, with the vast majority of bacteria present belonging to the phylum Proteobacteria. aminoglycoside resistance genes presented at elevated levels.

Aac(3)-Id was detected in five commercial and one noncommercial soil. catB6 was

ii detected in one soil. The ratio of antibiotic resistance gene hits to total 16S rRNA was

0.023, consistent with previous studies of residential soil and much lower than animal manures, which can range from 0.75-3ARG/16S rRNA. In summary, pilot results suggest commercial soils may not represent a major pool of antibiotic resistance genes but more analysis is needed to fully understand their place in the antibiotic resistance ecology.

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Acknowledgements

Many thanks go out to my advisor Dr. Hua Wang, my indispensable labmates Yu Li, Lu

Zhang, Zihua Wang and especially Yang Zhou for her help in the early stages of this experiment, and to my wife Jessica for her unending support during the process.

Vita

2006-2010 ...... Our Lady of the Elms High School

2011-2015 ...... B.S. Food Science and Technology,

...... Ohio State University

2015-present ...... M.S. Food Science and Technology,

...... Ohio State University

Fields of Study

Major Field: Food Science and Technology

Table of Contents

Abstract………………………………………………………………………………… ii

Acknowledgments……………………………………………………………………… iii

Vita……………………………………………………………………………………… iv

List of tables……………………………………………………………………………. vii

List of figures …………………………………………………………………………. viii

Objectives of study……………………………………………………………………. x

Chapters

1. Literature review………………………………………………………………... 1

1.0 Antibiotic use and resistance: an overview…………………………………. 1

1.1 History of antibiotics and antibiotic resistance……………………………. 2

1.2 Antibiotics of interest……..……………………………………………….. 9

1.3 How antibiotic resistance is acquired……………………………………... 14

1.4 Mechanisms of antibiotic resistance……………………………………... 18

1.5 Persistence of antibiotic resistance………………………………………. 23

1.6 Soils………………………………………………………………………. 24

1.7 Soil antibiotic production and resistance………………………………… 27

1.8 Augmentations to soil…………………………………………………….. 28

2. Introduction and reasoning…………………………………………………… 32

3. Materials and methods………………………………………………………… 35

4. Results…………………………………………………………………………. 41

5. Discussion……………………………………………………………………… 57

6. Future directions……………………………………………………………….. 64

Bibliography…………………………………………………………………………… 65

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List of Tables

Table 1. pH of commercial soil samples as determined by handheld pH meter……….. 43

Table 2. pH of noncommercial soils as determined by handheld pH meter……………. 44

Table 3. Predominant resistance genes present in deep sequenced DNA from pooled soil sample…………………………………………………………………………………... 51

Table 4. Designed primers for DNA sequencing…………………………………...... 53

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List of Figures

Figure 1. Log CFU of soil samples spread plated on PCA agar and incubated for 48 hours at 30°C ...... 45

Figure 2. Log CFU for noncommercial samples spread-plated on PCA agar and incubated for 48 hours at 30ºC...... 46

Figure 3. Growth of colonies on antibiotic-containing PCA plates (A: Ampicillin, L:

Lincomycin, E: Erythromycin, T: Tetracycline) after 48 hours incubation at 30°C, commercial samples...... 49

Figure 4. Growth of colonies on antibiotic-containing PCA plates (A: Ampicillin, L:

Lincomycin, E: Erythromycin, T: Tetracycline) after 48 hours incubation at 30°C, noncommercial control samples...... 50

Figure 5. Multidrug resistance detected in colonies on antibiotic-containing PCA plates incubated for 48 hours at 30°C, commercial samples...... 51

Figure 6. Main bacterial phyla represented in pooled DNA after deep sequencing; phyla containing more than 50 bacteria present in soil sample only are represented...... 52

Figure 7. Main bacterial classes represented in pooled DNA after deep sequencing; only classes containing more than 100 reads in soil samples are illustrated...... 53

Figure 8. Antibiotic resistance gene sequence hits present in pooled soil sample after deep sequencing...... 54

Figure 9. 16S PCR amplification of 16S rRNA gene fragment with DNA extracted by soil kit...... 56

Figure 10. 16S PCR amplification of gene fragment aac(3)-Id in commercial soil samples...... 58

Figure 11. 16S PCR amplification of gene fragment aac(3)-Id in noncommercial soil samples...... 59

Figure 12. 16S PCR amplification of gene fragment catB6 in commercial soil samples...... 60

Objectives of study

This research aims to improve our understanding on risk factors in antibiotic resistance gene dissemination in the ecosystem by analyzing commercial soils and the potential effects of manure and nutrient augmentations have on the soil resistome.

Chapter 1: Literature Review

1.0. ANTIBIOTIC USE AND RESISTANCE: AN OVERVIEW

Antibiotics are small molecules used to selectively address bacteria while leaving eukaryotic cells unharmed. They can be bacteriostatic, or block growth only, or bacteriocidal, killing cells, and can be broad or narrow-spectrum, able to affect a wide range of bacteria present or specific types, such as Gram-positive bacteria (Drlica and

Perlin 2011).

The typical focus when discussing antibiotics is their clinical use in humans. They are prescribed in the following circumstances: bacterial infections that pose a high risk of spreading to others if not controlled, infections unable to clear without medication, infections whose recovery time would be significantly sped up by antibiotic use, and those that carry high risks of complications if not treated rapidly. They are also common treatment for individuals whose immune systems are weakened or fully compromised-- e.g. elderly people, HIV patients, people undergoing chemotherapy--and in a prophylactic context for people about to undergo removal or transplant surgeries (NHS 2017).

However, there is growing concern as to the continued ability of antibiotics in clinical settings to be effective due to increases in antibiotic resistance in pathogens. This increase is a major threat to human health, with approximately 23,000 annually killed by untreatable bacteria in the United States alone (Frieden 2013).

Veterinary antibiotics also make up a large portion of antibiotic use overall, and have significant microbiological implications for animal health, production and the overall environment. They are used as growth promoters to increase feed efficiency as well as in treating diseases, although the European Union, Canada, and the United States now ban the practice of using antibiotics as growth promoters for feed animals because of the concerns about its impact on antibiotic resistance worldwide (most antibiotics used for these purposes are classified as sub-therapeutic and can enter the environment in significant quantities in active form through urine and feces (Sarmah 2006). For example sheep can excrete 21% of oral oxytetracycline (Montforts 1999). In surface water, ground water, drinking water, and sewage, antibiotics and their associated metabolites can be detected from ng/L to μg/L concentrations, including in some cases water that has gone through municipal treatment. (Daghrir and Drogui 2013). Wastewater treatment efficacy in reducing the amount of tetracycline, for example, ranged from 12% removal to 80% removal in two studies (Spongberg and Witter 2008, Karthikeyan and Meyer 2006).

Control strategies implemented thus far primarily focus on reduction in direct antibiotic use in clinical settings and food animal production, which has only had a modest impact on the overall prevalence of antibiotic resistance, and numerous studies have demonstrated that selective pressure due to the presence of antibiotics is not solely responsible for bacterial uptake and maintenance of mobile gene elements conferring antibiotic resistance (Wang 2009). In fact, studies of infant gut microbiota have shown up to 1010 CFU/g of antibiotic resistant bacteria shortly after birth despite no administration of antibiotics (Zhang 2011).

The continuing spread of antibiotic resistance even after changes have been made in use in clinical and veterinary settings implies other reservoirs and avenues for transmission exist that have not been fully analyzed, such as the environment.

1.1 HISTORY

Historical records of Jordanian red soils being used in an antibiotic-like manner for skin infections had led to studies that confirmed naturally antibiotic-producing bacteria present in those soils (Falkinham and others 2009). As early as 1884, Joseph Lister recorded the use of Penicillium molds for the treatment of infected wounds (Selwyn

1979). Considerable debate as to the reason for the inhibition of microbes due to molds existed among scientists of the time; for example John Tyndall theorized it was due to oxygen-limiting properties of the molds rather than the production of a compound

(Tyndall 1881). This phenomenon was further studied and understood by the end of the

19th century by scientists such as Garre, Corneil, and Babes, and it was established that the inhibition of microorganism growth was caused by substances produced by other microorganisms (Corniel 1885, Garre 1887).

The first antimicrobial sulfa drug, arsphenamine, was developed in 1909 by Paul Ehrlich and Sahachiro Hata and used to combat syphilis; it was a bacteriostatic organoarsenic compound that inhibited protein synthesis as well as DNA and RNA and also converted to an active form in the body that was toxic to parasites, and was widely in use until the

1940s, when antibiotics entered into common usage (Thorburn 1983).

Sulfonamidochrysoiodine, synthesized as a dye and studied for its antimicrobial properties, was the basis of the first sulfonamide antibiotic. It was used successfully in a

3 high profile case for curing the septic strep throat infection of the American president’s son, and so entered widespread use (Laub 1986).

The discovery of penicillin, which opened the door to an era of rapid discovery and development of many antibiotics, occurred in 1928. Alexander Fleming, a researcher at

St. Mary Hospital in London, discovered a blue mold contaminant, later identified as

Penicillium notatum, on old culture plates exhibited antimicrobial properties. Further study of the antimicrobial properties of P. notatum included the early development of the minimum inhibitory concentration (MIC) technique, but no established clinical effects, as the compounds he isolated were too unstable to be of use (Fleming 1929). Using

Fleming’s work as a basis, Florey and Chain continued research on penicillins that led to the first successful medical trials of penicillins in 1941 (Abraham and others 1941) and subsequent widespread use to treat wounded soldiers in WWII; due to the high level of need at the time, alternate sources beyond Fleming’s cultures of P. notatum was necessary and so Penicillium chrysogenum molds originating from commercial cantaloupe, established as also producing the necessary antimicrobial compounds by

Mary Hunt in 1943, were used and mass production became possible (Maiti and others

1998).

Another class of beta-lactam antibiotics, cephalosporins, were discovered two years later from fungus present in sewer waters in Caligari, Italy, whose population had less incidence of typhoid fever than normal (Bo 2000). The fungus in question,

Cephalosporium acrimonium, inhibited the growth of some Gram-negative organisms, including Salmonella typhi, and its isolation led to the development of a variety of semi-

4 synthetics over the next two decades with modifications to the C7 side chain to increase potency (Morin and others 1963).

Tetracyclines, likewise, were discovered in the late 1940s, products of Streptomyces aureofaciens and S. rimosus. Other variants were established later from further exploration of Streptomyces strains. Early tetracyclines, while successful, had poor oral absorption and semisynthetics such as lymecyclin were developed to increase water solubility, with a subsequent ‘generation’ of semisynthetic glycylcyclines following after to address solubility and also growing resistance; the first case of tetracycline resistance in a clinical setting was discovered in 1953 and an increasing number of bacteria now exhibit resistance (Chopra and Roberts 2001).

Around this time, the development of aminoglycoside antibiotics began, with streptomycin as the first isolated in 1943 from soil actinomycetes. Observed antimicrobial effects of soil compounds were studied in detail by Waksman and Schatz and isolated streptomycin was tested as a treatment for tuberculosis, a major killer at the time (Schatz and others 1944). The rapid development of resistance and side effects associated with the treatment made it unsuitable as a drug treatment at the time, until a

“triple therapy” consisting of streptomycin combined with isonicotinic acid hydrazide and 4-aminosalicylic acid was developed, which proved to cure 90-95% of existing tuberculosis cases (Fox and others 1954).

Penicillin G, a narrow-spectrum type developed in 1945, was widely used in the subsequent decade and was one of the first whose clinical use was majorly impacted by the development of resistance; resistance to penicillin G in nosocomial infections of

Staphylococcus aureus was reported by 80% of hospitals that used the drug as early as

1957 (Lowy 1998). The drug was also frequently administered for meningitis and subsequent increased rates of resistance in Neisseria gonorrhea were detected around this time (Eickhoff and Finland 1965). Resistant bacteria in the hospital setting, it should be noted, is spread in part by lack of proper adherence to hygienic practices by doctors such as glove-changing protocols and handwashing (Weinstein 2001). In the case of nosocomial infections with antibiotic resistant bacteria, increasing rates of occurrence may be due to contamination/spreading between patients rather than an indicator of massive resistance arising.

During this time, anti-staphylococcal penicillinase-resistant penicillins were developed to respond to the increase in resistance developing within hospitals. These types have a very narrow mode of action and are only used against staphylococcal infections and include methicillin and oxacillin (Rolison and others 1960). Methicillin has become known primarily since as part of the MRSA designation--methicillin-resistant staphylococcus aureus, which emerged less than a decade after the initial development of methicillin and is now endemic in hospitals, with a 2006 survey indicating the rate of occurrence at 46.3 per 1000 patients, and a major source of nosocomial mortality (Barber

1961, Jarvis and others 2006).

The creation of wider variety of types of penicillins, such as methicillin but also ampicillin and amoxicillin, was facilitated by the isolation of 6-aminopenicillianic acid which allowed for the creation of semi-synthetics for use against Gram-negative bacteria

(although susceptibility remained variable in practice) (Rolison and Stevens 1961).

Amoxicillin was particularly important due to its activity against Helicobacter pylori, which is implicated in the development of gastric cancers, and its ability to be used to

6 treat pregnant women and young children (George and others 1990, Deeks and others

1999). Later in the 1970s some extended-spectrum penicillins were developed with resistance to some beta-lactamases, extending the range of uses for penicillins further, although some chromosomal beta-lactamases can still render them ineffective and MRSA is unaffected by them. These drugs include piperacillin and tircacillin (Zaffiri and others

2012).

Fluoroquinolones, developed in the 1980s from precursor quinolones, are broad- spectrum antibiotics used for a wide variety of infections--to the level of beta-lactams-- and are able to address both Gram-positive and Gram-negative infection (Hooper and

Wolfson 1991). Quinolones were developed in the 1960s as a modification of the anti- malarial drug chloroquine, which contained nalidixic acid, an antibiotic precursor with activity against Gram-negative organisms--one of the first antimicrobials with any consistent activity against them (Hooper 1998). Subsequent modifications to quinolone structure and side chains to create the fluroquinolone class, with its first approved member norfloxacin in 1986, allowed for some limited action against Gram-positive organisms, which was then improved upon further with second-generation fluoroquinolones ciprofloxacin and ofloxacin, broad-spectrum antibiotics against Gram- negative organisms (Pseudomonas aeruginosa of particular note, as it is commonly a problem re: nosocomial infections) with increased additional Gram-positive action and less issues of absorptivity (Applebaum and Hunter 2000). Third and fourth generation variants to further broaden the spectrum of action have since been developed, and fourth generation are capable of addressing complex infectious issues like MRSA and mixed aerobic-anaerobic infection (Ambrose and Owens 2000). Resistance development,

7 including to the newer types of fluroquinolones, has been detected in an increasing variety of Gram-negative organisms, mostly due to modification of target enzymes through mutation of the genes encoding them (Dougherty and others 2001).

Carbapenams were developed in the 1970s from olivianic acid produced by

Streptomyces clavuligerus to address the need for beta-lactamase resistant antimicrobials, but were not widely used clinically until the development of the semisynthetic imipenem in 1984 due to chemical instability issues (Miyadera and others 1983). One later derivative circa 1989, meropenem, is a drug of choice for nosocomial infections and multiresistant organisms (Mohr 2008). Doripenem was developed in 2007 and, similarly, is active against MRSA and vancomycin-resistant enterococci, and both are considered current-use drugs of last resort, although two different instances of enzymes deactivating carbapenams (carbapenamase from Klebsiella pneumoniae detected in 1990 and a metallo-beta-lactamase variant from Enterobacteriacea found in 2009) have been detected, indicating resistance is beginning to emerge against these last-line drugs

(Arnold and others 2011, Pillai and others 2001).

Vancomycin was discovered in 1958 isolated from Streptomyces orientalis in soil, but not widely used until the emergence of MRSA due to its high levels of ototoxicity and nephrotoxicity; it was generally seen as a drug of last resort (Griffith 1981). During the 1980s and 1990s vancomycin use for treating MRSA, colitis, and meningitis as responses to resistance developed to the conventional methods of treating these illnesses increased 1100-fold (Kirst and others 1998). During that period, resistance to enterococci and vancomycin-resistant Staphylococcus aureus emerged and the effectiveness of

8 vancomycin as a last-resort drug has therefore become more of a complex issue

(Cosgrove 2004).

Linezolid, an oxoazolidinone still considered effective against MRSA, was developed in 2000 (Ford and others 2001). Its early precursor, cycloserine, was used in the 1950s as part of component therapy for tuberculosis, but searches for other oxoazolidinones throughout the 1970s and 1980s were discontinued due to the hepatotoxicity of the compounds and the class was only re-examined in the 1990s

(Epstein and others 1955, Slee and others 1987).

The most recent naturally-produced antibiotic, as we stand today, is daptomycin, synthesized from the fermentation of the actinomycete Streptomyces roseosporus. It is considered a lipopeptide antimicrobial, the first and so far only of its class, a class that acts on Gram-positive bacteria by depolarizing the cell membrane (Cottagnoud 2008). It is able to act on complex resistant bacteria such as VRE and MRSA, although as of 2008 resistance to daptomycin, while still rare, had been detected (Montero and others 2008).

Given the rapid emergence of resistance to new antibiotics and the continuing problem of multiresistant bacterial infections, particularly in hospital settings, continuing development of new compounds is necessary. Based on history, these compounds yet to be discovered are likely to be modifications in the chemical structures of existing classes with enhanced ability to compensate for resistance mechanisms or new compounds synthesized from the environment, especially from actinomycetes in soils.

1.2 ANTIBIOTICS OF INTEREST

Aminoglycosides

Aminoglycosides are pseudo-oligosaccharides and cationic compounds used against Gram-negative infections, and are nephrotoxic and ototoxic to mammals. Some, such as amikacin, are used for multidrug-resistant Gram-negative nosocomial infections.

Their primary mode of action is in protein synthesis inhibition or by causing mistranslation during protein synthesis (Karasawa and Steyger 2011). Primarily, they bind to the A-site of 16S16S RNA, preventing protein synthesis (Fourmy and others

1996). They are also capable of interacting with other RNAs due to the presence of multiple positive charges and conformational flexibility; they can displace metal ions to disrupt the function of RNA (Kawamoto and others 2008). Aminoglycosides are also able to bind to ferric iron (FeIII) and complex with it, forming FeII-aminoglycoside compounds, which lead to the formation of reactive oxygen species that can rise to toxic levels and subsequently trigger cell death mechanisms (Sha and Schacht 1999).

Beta-lactam antibiotics

Beta-lactam antibiotics are amino-acid based, derivatives of 6-aminopenicillianic acid. One basic beta-lactam antibiotic, penicillin, is constructed from a tripeptide: cysteine, valine, and a metabolic intermediary of lysine, and differs from standard polypeptide assembly because it uses a modular metabolic pathway where the order of molecules is set by embedded mRNA templates in the correct order and the tRNA requires the use of carrier proteins in each module to carry out their specific functions.

Three modules for selecting an amino acid, activating it, and inserting it into the protein chain are present. Special enzymes synthesize the nonstandard amino acids necessary and also regulate other parts of the assembly process; beta-lactam antibiotic biosynthesis is therefore quite different than biosynthesis of other proteinaceous compounds, in which

10 tRNA brings appropriate amino acids to an mRNA template to form peptide chains from a standard pool of amino acids (Clardy and others 2009). The beta-lactam ring structure is necessary for the antimicrobial activity of the drug to be active. They are not directly bacteriocidal, but rather attach to penicillin binding proteins in the bacterial cell wall, which prompts the cell wall to auto-lyse; thus, they interfere with the cell’s ability to form a peptidoglycan cross-link (Wright 1999) Beta-lactam antibiotics are typically used against Gram-positive bacteria and Gram-negative cocci (except in the case of broad- spectrum penicillins), as many Gram-negative rod bacterial types contain beta-lactamase that renders typical antibiotics of this class ineffective by cleaving the beta-lactam ring and also have a significantly thinner layer of peptidoglycan (Farrar and Newsome 1973).

Gram-positive bacteria can also become resistant to beta-lactam antibiotics through modifications of the target penicillin binding proteins; this is a mechanism used by species such as MRSA (Mulligan and others 1993). Beta-lactam antibiotics can be narrow, extended, or broad-spectrum; natural penicillin is narrow-spectrum. Ampicillin and amoxicillin are extended-spectrum aminopenicillins and contain a positively-charged amino group, which does not convey resistance to beta-lactamase but does increase uptake through porin channels (Bush and Johnson 2000). Broad-spectrum antipseudomal penicillins, such as azlocillin and mezlocillin, can, unlike other varieties, be effective against gram-negative rods, and have a cyclic urea substitution in the amino acid side chain. They are still not effective for use against bacteria that produce beta-lactamase

(Tan and File 1995).

Chloramphenicol

Chloramphenicol is a broad-spectrum antibiotic used for both Gram-positive and

Gram-negative infections and is particularly effective against brain infections due to its ability to cross the blood-brain barrier and accumulate in cerebrospinal fluid; it is commonly used to treat bacterial meningitis, particularly Haemophilus influenzae meningitis, in patients with allergies to more common antibiotics such as penicillins. It is also used to treat rickettsial infections and tetracycline-resistant cholera (Yunis 1998).

Chloramphenicols are bacteriostatic and reversibly inhibit protein synthesis in bacteria by targeting and binding to several peptides of the 50S subunit of the bacterial ribosome

(Skold 2011). It also binds to the“V domain”, or peptidyl transferase center, of 23s rRNA, the area where the active site of protein folding reactions are located (Chowdhury and others 2002). of Chloramphenicols are not often used when other antibiotics can be substituted due to their high levels of toxicity, particularly hematoxicity associated with suppression of the bone marrow’s ability to carry out mitochondrial protein synthesis, which is generally reversible once treatment ends but can in rare cases develop into aplastic anemia, leading to increased susceptibility to infection and potential for death through hemorrhage (Yunis 1998). Chloramphenicol administration leads to “gray syndrome” in babies whose livers cannot process chloramphenicol and so experience a buildup during treatment. This syndrome is associated with ashen grey skin, cyanosis, and cardiovascular collapse, and so use of chloramphenicols, while not recommended for most conditions for adults, cannot be used for treating infants under any circumstances

(McIntyre 2004). Chloramphenicols are banned for use in food-producing animals in the

United States and Canada, but are used to treat infections in pets such as cats or dogs and

12 are considered the most effective treatment for chlamydia in koalas. Dogs undergoing treatment excrete approximately 55% of administered chloramphenicol in urine, 5-10% of which is still in active form (United States Pharmacopeial Convention 2007).

Lincomycin

Lincomycin is part of the lincosamide class of antibiotics, which also includes clindamycin. It is naturally produced by the soil bacteria Streptomyces lincolnensis

(Skold 2011). Lincomycin is a narrow-spectrum antibiotic used for Gram-positive bacterial infections (with the exception of enterococci, which it is not effective against) and is particularly potent against anaerobic bacteria and protozoa. It can also reduce the production of toxins by streptococcal species. Clinically, lincomycin is not used as widely as clindamycin, which is broader-spectrum and has been shown to be effective against some MRSA varieties, but it is still sometimes used for upper respiratory infections in cases where patients are allergic to beta-lactam antibiotics (Spizek and

Rezanka 2017). It inhibits protein synthesis through inhibition of peptidyl transferase through binding to the 50S subunit of the bacterial ribosome in a mechanism similar to that of macrolide antibiotics, although they are not structurally similar (Skold 2011).

Macrolides Macrolide antibiotics are a class of compounds containing 14, 15, or 16- membered macrolactam rings with otherwise varied structures and originate as soil bacterial compounds; the first-discovered macrolide antibiotic, erythromycin, was isolated from Streptomyces erythraeus. Macrolides are used for the treatment of streptococcal and pneumococcal infections for patients unable to take penicillins, as drugs of choice for diptheria and legionellosis, and in long-term low-dose administration for immunomodulation of chronic diseases such as cystic fibrosis and asthma (Shinkai

13 and others 2008). They are bacteriostatic antibiotics that arrest growth through inhibition of protein synthesis through binding to the 50S site of the bacterial ribosome. Ribosome

“stalling” is observed in bacteria exposed to macrolides; that is, they target specific sites to arrest translation and so are specific to individual proteins and contexts. Macrolide binding to the ribosome creates changes in the peptidyl transferase center to disrupt peptide bond formation and “in general, inhibit translation by making certain combinations of the PTC substrates problematic for the drug-bound ribosome and arresting translation when such substrates are encountered” (Kannan and others 2014).

Sulfonamide

Sulfonamides are bacteriostatic compounds and were some of the earliest antibiotics, having been established as effective against bacterial infection as early as the

1930s (Laub 1986). They promote the inhibition of folate synthesis and so contribute to the inhibition of bacterial synthesis of DNA, RNA, and protein, as folate is a necessary cofactor for metabolite synthesis. They also competitively inhibit the enzyme dihydropterate synthetase, which produces a precursor of folate (4-aminobenzoate) in bacteria , which are unable to use dietary folates and must synthesize their own (Kalkut

1998). While sulfonamides are broad-spectrum antibiotics with activity against both gram-positive and gram-negative species, they are typically used in conjunction with other antibiotics, such as the synergistic combination of sulfamethoxazole, the most widely used sulfonamide, with trimethoxazole (bactrim); both chemicals together enhance folate inhibition processes more than separately (Kalkut 1998). Other sulfonamides, such as sulfadoxine, are used in conjunction with anti-parasite drugs such as pyrimethamine, for the treatment of malaria (White 1996). Used in isolation, resistance

14 to sulfonamide drugs is common, with bacteria using mechanisms such as increased 4- aminobenzoate production, mutant forms of dihydropterate synthetase, efflux pump systems, or decreased permeability to sulfonamides to escape danger caused by these drugs (Huovinen 2001).

Tetracycline

Tetracyclines function by inhibiting protein synthesis through blocking the ability of the ribosomal A site to accept aminoacyl-tRNA, halting translation during the elongation step. They are broad-spectrum antibiotics that can be used against both gram- positive and gram-negative bacteria, as well as protozoan parasites and some atypical organisms such as rickettsia (Chopra and Roberts 2001). Their use for veterinary purposes is common, as they are low-cost in addition to being able to treat a wide range of conditions, including some reported auxiliary effects on tumors and bone absorption.

In countries where the practice is still legal they are used at subtherapeutic levels as growth promoters in animal husbandry. Variants such as oxytetracycline and chlorotetracycline are more common than tetracycline for use as growth promoters

(Daghrir and Drogui 2013). Tetracycline is produced through enzymatic processes from the components malonamyl-COA and eight two-carbon fragments, in a mechanism similar to the synthesis of fatty acids (Clardy and others 2009).

Vancomycin Vancomycin is designated as an actinobacteria-derived glycopeptide antibiotic and is used for treatment of MRSA and other severe Gram-positive infections, including those in infants; it is notable in that it still retains activity against nearly all Gram-positive pathogens after fifty years of clinical use (Marsot and others 2012). It is a bacteriocidal antibiotic that inhibits cell wall synthesis through the blocking of transglycosylase and

15 transpeptidase activity and by binding to peptidoglycan at the D-alanyl-D-alanine dipeptide, causing lytic cell death (Kahne and others 2005). Vancomycin can only be used against Gram-positive organisms as it cannot penetrate the outer membrane of

Gram-negative bacteria to reach its targets (Munita and Arias 2016).

1.3 HOW ANTIBIOTIC RESISTANCE IS ACQUIRED

During consistent exposure to an antibiotic in a bacterial environment, not all susceptible bacterial strains may be killed immediately, particularly in cases where the concentration of antibiotic is low. Some cells may be able to mutate and continue surviving in the environment, including reproducing and passing on those mutations to subsequent cells. This selection is referred to as selective pressure, in which antibiotics selectively enrich antibiotic resistant bacteria. Recent studies have indicated that the rise in antibiotic resistance is more complex, however; even in the absence of selective pressure, in some populations antibiotic resistant bacteria can become dominant (Luo and others 2005). Additionally, a number of antibiotic resistant gene pools have been documented in commensal foodborne bacteria, environmental samples, and samples not exposed to antibiotics, and they have been demonstrated to be capable of transmitting those genes to other organisms. Of particular note, this has been demonstrated in baseline comparisons of feral vs. organically raised swine resistance to chlorotetracycline (with feral swine having significantly less CTC resistant-bacteria detected despite neither population being administered antibiotics) (Stanton and others 2011). Another study analyzed the gastrointestinal tracts of newborn babies, whose gastrointestinal tracts became rapidly colonized with bacteria, including antibiotic resistant bacteria from the day after birth onwards, demonstrating that in human GI tracts, initial populations of

16 antibiotic resistant bacteria are independent from exposure to antibiotics or foodborne sources, including breast milk, and colonization may result from environmental exposure

(Zhang and others 2011). Multi-drug resistance in aquaculture environmental, feed, and fish samples have also been demonstrated, with the corresponding antibiotic resistance determinants being stable in the absence of selective pressure in some cases (Huang and others 2015). Indications appear to be that the use of antibiotics in the food system and in medicine and restrictions thereof are not sufficient as cause and solution to the problem of antibiotic resistance.

Horizontal gene transfer is any transfer of genetic material between cells other than through transmission from parent to offspring. It is a primary force behind acquired antibiotic resistance, as it involves the uptake of foreign DNA into the host bacterial cell.

Bacteria can acquire new DNA through horizontal gene transfer via transformation, phage-mediated transduction, or conjugation. This is particularly relevant in the study of environmental microbes, such as those in soil, which may share a local environment with antibiotic-producing microbes with intrinsic immunity to prevent cell suicide. Similarly, bacteria producing antimicrobials such as nisin may lead to protective mechanisms in their neighbors; both of these are suggested origins of antibiotic resistance genes (Munita and Arias 2016).

Most antibiotic resistance is not acquired through transformation, uptake of exogenous DNA through the cell membrane by competent bacteria. Transduction, the transfer of genetic material through infection of bacteria by a bacteriophage, either involves lysis of the cell after infection or incorporation of donor DNA into the host genome; recent studies have indicated that this type of horizontal transfer may play a

17 larger role in the spread of antibiotic resistance than previously thought, although study of this, particularly in regards to environmental antibiotic resistance, is still limited

(Balcazar 2014). Conjugation, which uses mobile genetic elements such as plasmids and transposons to transmit foreign DNA, represents the most common pathway by which antibiotic-resistant nosocomial infections arise, particularly in the body during antibiotic treatment. It is also frequently how antibiotic resistance is transmitted in other contexts

(Munita and Arias 2016). For example, horizontal gene transfer through conjugation by quorum sensing is implicated in the expansion of biofilms in Lactococcus lactis (Wang

2009).

Transposons are mobile genetic elements with four different classes which contain transposase, an enzyme which allows for insertions and excisions of DNA on a site-specific basis. Class I transposons only require one protein for transposition and include insertion sequences as well as compound transposons that contain insertion sequences. Class II are more complex, and include insertion sequences with inverted repeats; the transposition of this class is replicative and requires two protein sequences.

Class III are bacteriophages, and class IV are any transposons that do not fall fully into other categories/mixed mechanism transposons (Brown and Evans 1991).

Integrons can also efficiently transfer antibiotic resistance genes through their ability to use mobile gene cassettes to recruit open reading frames. They consist of the enzyme integrase and a target DNA sequence, and interact with resistance gene cassettes which have a corresponding target sequence. Integrase mediates the progression of the target sequence being inserted. They can be carried on plasmids (Radstrom and others

1994). For example, genes in the IMP family which convey resistance to beta-lactam

18 antibiotics, are associated with class 1 integrons, elements located on plasmids and transposons that have spread rapidly through Gram-positive and Gram-negative strains both (Gillings 2008). Other enzymes of this type are associated with plasmids and mobile elements as well; extended-spectrum beta-lactamases, for example, convey resistance to most Enterobacteriacea and transfer resistance to both penicillins and cephalosporins through mobile elements that can be taken up by phage-like sequences and plasmids

(Poirel and others 2005). There is often a biological cost to the maintenance of resistance, although further mutations after resistance is acquired may mitigate this, allowing the bacterial population to remain resistant to antibiotics without as much metabolic impact (B Normack and S Normack 2002). Other persistence mechanisms, such as toxin-antitoxin systems, may also facilitate resistance mechanisms being retained in the bacterial population.

Plasmids are mobile genetic elements that are able to conjugate between organisms that are not closely related, unlike phages, and can convey selective advantages to new host cells. After sequencing, a large amount of recently-acquired foreign DNA is found in many bacterial genomes--often antibiotic resistance, but also virulence factors and mechanisms for biodegradation of other compounds (B Normark and S Normark 2002). Plasmids also allow for the interaction of bacteria with eukaryotes, such as in the case of nitrogen fixation by rhizobia. Plasmids contain a set of mobility genes for DNA replication and can be conjugative, mobilizable, or nonmobilizable. The classification is based on whether the genes for membrane-associated mating pair formation complex (a protein secretion channel that conveys DNA paired with an enzyme, relaxase, to be transferred) are carried by the plasmid (conjugatable/self-

19 transmissable), utilizes this mechanism from another genetic element (mobilizable), or can do neither, and only transfer its genetic information via transduction or natural transformation (Smillie and others 2010). They can be vehicles for transposons or integrons.

1.4 MECHANISMS OF ANTIBIOTIC RESISTANCE

Mechanisms of resistance can include modifications to decrease uptake, reduce affinity towards the antibiotic, development of efflux systems to eliminate the antibiotic from the bacterial cell, or changes in metabolic pathways. Resistance to a particular antibiotic can be done using multiple mechanisms and bacterial strains are not limited to using one pathway at once; for example, in the case of fluroquinolones, resistance can express itself as mutations of the target site, efflux pump systems that exclude the fluoroquinolones from the cell, or changes in the target site, and fluroquinolone-resistant bacteria are capable of using two or three of these mechanisms. However, there are differences in structurally-different bacteria in how resistance is expressed, as well, particularly when it comes to differences between Gram-positive and Gram-negative organisms; for example, Gram-positive and Gram-negative organisms are both able to be resistant to penicillins but while Gram-negative organisms tend to express this in the form of producing beta-lactamase to inactivate the antibiotic, Gram-positive organisms instead tend to have modifications in the target site penicillin-binding proteins. The structural difference due to the presence of the outer membrane probably makes access to the binding sites more difficult for penicillins, which require porins to enter the inner membrane, and so inactivation through beta-lactamase is more efficient, whereas Gram- positive organisms, lacking an outer membrane, are not able to effect this control over the

20 entry of penicillins and so have evolved different capabilities. Thus, when discussing resistance mechanisms, it is worth noting that some mechanisms are more efficient for use by certain types of bacteria and so they have evolved to be the dominant pathways

(Munita and Arias 2016).

A common acquired resistance mechanism is the production of enzymes that inactivate or destroy the antibiotic. Those that primarily inactivate tend to affect major cellular processes such as acetylation, phosphorylation, and adenylation, such as the aminoglycoside modifying enzymes, carried on mobile genetic elements, that modify hydroxyl or amino groups on the aminoglycoside and cause steric hindrance that reduces the affinity of aminoglycoside for the target bacteria (Wilson 2014). Another example of this is alteration of chloramphenicol through chloramphenicol acetyltransferases, which attaches an acetyl group to chloramphenicol and makes it unable to bind to its ribosomal target; low-level resistance is conveyed with type B of this enzyme, while higher-level is conveyed with type A, and both are found in both Gram-positive and Gram-negative organisms (Schwarz and others 2004).

Beta-lactamase is an example of a resistance mechanism which functions by destroying the antibiotic in question; penicillins require an intact beta-lactam ring to be biologically active, and many bacteria produce the enzyme beta-lactamase which cleaves the ring, rendering penicillins inactive. It was first detected in Escherischia coli strains in the

1940s, but has since been detected in many other species and can be spread through plasmid-mediated diffusion to bacteria that were not previously resistant (Abraham and

Chain 1940, Bush and Johnson 2000). Inhibitors of the beta-lactamase enzyme such as sulbactam and clavulanic acid taken in conjunction with penicillins can help mitigate the

21 spread of resistance and are often used in conjunction with extended-spectrum penicillins.

However, over 1,000 types of beta-lactamases have been recorded, with varying types of activity and utility in the presence of added compounds such as tazobactam and clavulinic acid. For example, metallo-beta-lactamases, which use zinc as a cofactor, are not inhibited by clavulinic acid, although they are inhibited by chelating agents such as

EDTA (Queenan and Bush 2007).

Membrane modifications are another common type of acquired resistance; antibiotic targets tend to need to reach intracellular targets or those in the inner membrane, and so many bacteria, particularly Gram-negative types, have modifications that decrease the uptake of antibiotics. Outer membranes of Gram-negative bacteria act as a natural barrier, and convey inherent resistance to some types of antibiotics even without acquired resistance; for example, vancomycin is unable to penetrate the outer membrane.

Changes in permeability/differential expression of porins of the outer membrane affect most hydrophilic antibiotics, including beta-lactams and tetracyclines, primarily as the porins they use to access the inner membrane tend to be water-filled (Pages and others

2008). Porin alterations manifest themselves in the form of changes in levels of porins expressed, what porins are expressed, or hindrance of porin function, although none convey a high level of resistance alone and are generally paired with other mechanisms of resistance (Nikaido 2003).

Efflux pumps affect resistance alone or in conjunction with other mechanisms and the ability to eliminate toxic compounds from the interior of a cell has many purposes beyond just antibiotic resistance conveyance. These pumps are present in both gram- positive and gram-negative organisms and were first described in the context of an E. coli

22 cell capable of expelling tetracycline which expressed the tet gene (McMurray and others

1980). Genes for encoding efflux pumps can be on mobile genetic elements (common for tet) and can be transferred to other organisms, or can be on the chromosome of the particular bacterial species conveying intrinsic resistance, and a wide range of antibiotic compound classes can be expelled through efflux, including beta-lactams, polymyxins, and fluoroquinolones. The five different families of efflux pumps vary in energy sources needed, what they are able to expel, structure, and what organisms they can be expressed in (Poole 2005). An example of the basic mechanism of operation of these pumps is

AcrAB-TolC, found in E. coli and used for transporting tetracyclines, choloramphenicol, and several other antibiotics in addition to bile salts and disinfectants out of the cell through a series of rotating conformational changes in AcrB, which has two binding pockets, before being finally excreted through TolC (Du and others 2014).

Bacteria are also able to evade antibiotic action by changing the structure of the site it targets to reduce affinity or protecting that site. Target site modification is a protection mechanism against almost all types of antibiotic compounds and is particularly common in pathogens, and may be expressed as enzymatic changes to the target site, point mutations, or replacing the target entirely (Munita and Arias 2016). Enzymatic changes include additions of groups; for example, erm genes convey resistance to macrolides and lincosamides by mono- or dimethylating a key adenine residue in domain

V of the 50s ribosomal subunit of 23rRNA that results in impaired ability of macrolides and lincosamides to bind to that target region (Leclercq 2002). Modification through point mutations affect antibiotics that target cell functions such as DNA replication or

RNA polymerization, such as in the case of resistance to fluoroquinolones where mutated

23 forms of DNA gyrase and topoisomerase IV enzymes (through chromosomal mutations in the genes that encode their production) are able to avoid inhibition by fluoroquinolone and therefore inhibition of DNA synthesis, although mutation has to reach significant levels over time to fully convey resistance and not just a slight change in the MIC

(Hooper 2002). There are also a limited amount of mutations that can develop and still allow the cell to function as normal; the enzymes in question still must be able to carry out their intrinsic functions while being changed enough to alter the affinity for an antibiotic. Often, changes in the function of the protein will occur, and there is the potential for the mutated bacteria to be outcompeted by others in its environment as soon as the stressor of the antibiotic is removed (B Normack and S Normack 2002). Bacteria can also evolve new structures that function like targets for antibiotics but do not have the same affinities; most notably this is the mechanism by which S. aureus is resistant to methicillin. An exogenous gene incorporated by some S. aureus, mecA, encodes for

PBP2a, which is a penicillin binding protein with low affinity to penicillins. Unlike standard penicillin binding proteins produced by S. aureus and others, and PBP2a still functions as an enzyme for transpeptidation and transglycosylation of peptidoglycan as normal (Hiramatsu and others 2013). The rapid spread of MRSA may be in part due to compounds like sasX, a virulence determinant surface protein in MRSA which promotes increases nasal colonization and allows S. aureus to survive in blood longer, as well as promotes biofilm formation, allowing increased spread of the pathogen (Li and others

2012).

Protection of the target site rather than modification of it is generally an adaptation carried on mobile genetic elements; two of the most common examples of this

24 mechanism are the genes tet(M) and tet(O), which are found in several different plasmids and as part of conjugative transposons. One of the ways in which the target site can be protected is competition; tet(M) competes directly for the binding site of tetracycline on the ribosome and can dislodge and fully displace it, while also altering the geometry of the binding site on the ribosome so that re-binding of the antibiotic can no longer occur.

1.5 PERSISTENCE OF ANTIBIOTIC RESISTANCE

Initial fitness costs to the cell to take on antibiotic resistance-conveying plasmids mean that, in the absence of other compensatory factors and once the stressor of the antibiotic is removed from the local environment, nonresistant bacteria may outcompete these mutants. For example, efflux pump adaptations can cause imbalances in cell metabolism that slow growth (Sanchez and others 2002). However, compensatory factors exist in many cases, allowing bacterial cells to maintain resistance in the absence of selective pressure and spread that resistance further. Often, compensatory mutations for the loss of fitness are sufficient for mutant cells to remain competitive , and have been observed in both clinical and in vitro analyses (Bjorkman and others 2000, Nagaev and others 2001). In some cases they have been shown to increase the fitness of the cell rather than restore it to its previous level, such as the fitness benefit of the gyrA mutation in

Campylobacter (Luo and others 2005). Other mechanisms by which antibiotic resistance genes persist in bacterial cells include toxin-antitoxin systems, chromosomal integration, or cross-selection. Toxin-antitoxin systems increase the competitiveness of cells that take up plasmids by poisoning cells that fail to do so; a toxin-antitoxin complex comprised of a stable toxin and unstable antitoxin is incorporated into the cell as a component of a plasmid, with continual replenishment of the antitoxin compound by the plasmid. If the

25 plasmid is not maintained, the antitoxin degrades the toxin is liberated, poisoning the cell from within. This mechanism, used by pathogens such as E. coli and Shigella flexneri, encourages the uptake of plasmids in the bacterial population (Hayes 2003).

Chromosomal integration of antibiotic resistance-conveying genes allows for more stable incorporation of these genes through transposon-mediated transposition (Harmer and others 2014). Cross-selection also allows for the maintenance of resistance in the absence of selective pressure; antibiotic resistance genes that also convey resistance to heavy metals or sanitation agents may be kept by bacteria if those compounds are present in the bacterial environment (Wang 2009).

1.6 SOILS

The continuing spread of antibiotic resistance even after changes have been made in use in clinical and veterinary settings implies other reservoirs exist that have not been fully analyzed, chiefly the environment. Environmental pressures in the form of pollutants and other contaminants--including antibiotic residues, but not limited to them-- appears to induce important changes in bacterial communities that could lead to transferable resistance (Knapp and others 2017). Additionally, intrinsic resistance within environmental bacteria may be a source of important transferable resistance genes. Two resistance genes originating from environmental bacteria Kluyvera and Shewanella

(CTX-M beta-lactamase and qnrA) have been found to be highly genetically similar to resistance genes in clinical pathogens (Poirel and others 2002, Poirel and others 2005); this phenomenon, therefore, has been observed. At the same time, much of the bacterial diversity of the environment has not been widely analyzed yet for the existence of antibiotic resistance, and so information about where antibiotic resistance genes may

26 exist in the environment, with the potential to transfer those genes to clinically-relevant bacteria, is incomplete. Soils have a high level of microbial diversity and many species with intrinsic resistance and natural antibiotic production, in addition to being indicators of environmental pollution and substances exposed to chemicals and drugs used in plant/animal production, and so are an area of analyzing the environmental resistome worth analyzing further.

Soil is considered to be, broadly, loose material on the Earth’s surface capable of supporting life. It is made up of a varying amount of organic matter, usually about 5% in total, and is 45% minerals, 25% air, and 25% water; the topsoil is considered the most biologically and chemically active and contains the most organic material, while the subsoil below it has minimal organic material and is heavily comprised of minerals and is sometimes brightly colored due to oxide content. Soil organisms are generally able to utilize these minerals (Orgiazzi and others 2016).

Primarily soil bacteria belong to the phyla Proteobacteria, Firmicutes,

Actinobacteria, and Cyanobacteria, with some small contributions from others such as

Acidobacteria. Overall, 15,000 species of soil bacteria are known out of an estimated >1 million, representing 2800 genera. Environmental factors play a role in the diversity of bacteria in any given soil, such as temperature and available nutrients (Orgiazzi and others 2016). One study indicated that the overall diversity of bacterial populations in soil appears to be heavily related to the soil’s pH rather than decided by factors related to latitude and geography, unlike animal or plant microbial populations, with the highest level of diversity and richness found in neutral soils and negative effects on diversity of population as the soil became more acidic (Fierer and Jackson 2006). Soil microbes are

27 able to fix nitrogen and are the engines of decomposition of organic matter including complex compounds such as tough hemp fibers or spilled oils. They exist either as independent organisms or in symbiotic relationships with other organisms in the soil environment (Orgiazzi and others 2016).

While a high level of diversity exists in the soil microbial population, much of it is not analyzable by traditional means; an early molecular study of soil identified 40 high- level groups within the bacterial domain, 50% of which were unknown using previous methods. Approximately 1% of the total soil bacterial population can be cultured; all culture-based studies of soil bacteria, therefore, are incomplete pictures of the diversity present even though useful information about function and metabolism can be gained through it. The soil environment is highly complex, and its specific conditions in many cases cannot be replicated to create a suitable environment, particularly because lack of exact knowledge about some unculturable bacteria means that specific needs for micronutrients, helper colonies, pH, pressure, etc. may not be known. Most methods to overcome this center around analyzing bacterial populations via gene analyzation methods (16S rRNA analysis, full DNA sequencing, and other metagenomic methods), although modified culturing methods such as cocultures, mixed cultures, and biotechnological solutions like laser microdissection and high-throughput microbioreactors are occasionally used to enhance the amount of bacteria that are culturable (Pham and Kim 2012). Single-cell genomics is also used to study soil bacteria, as the isolation of single cells, sequencing and amplification, and subsequent reconstruction of their genome allows for more examination of metabolic properties of

28 the bacterium in question even in cases where culturing is not possible (Killham and

Prosser 2015).

16S rRNA methods are based on the premise that 16S rRNA is the most evolutionarily conserved of the three rRNA genes in bacterial species and so can be used to identify unknown bacteria as well as be used as a component in metagenomics to estimate microbial diversity independent of culture. The amplified 16S sequence is compared to existing sequences in a database (Rajendhran and Gunasekaran 2011).

Metagenomics methods, more broadly, involve the sequencing of the full genome present in extracted DNA and then comparing gene fragments present to available databases to obtain information about the overall DNA profile or about a specific sequence of interest; they can also be used to identify a specific sequence of interest for the purpose of designing primers to screen for that sequence in metagenomic libraries or desired environmental samples. 16S rRNA can be used as part of the method to give information about evolutionary history of the organism. Full sequencing can also give information about the broader functionality of an organism that cannot be cultured, such as genes coding for nitrate reductase or hydrogenase. Modern sequencing methods tend to involve highly technically complex machinery that sequences DNA through single- molecule sequencing synthesis that uses cleavable fluorescence tags to detect when new bases are added, reversible dye-terminator sequencing with a similar single base identification method, or other older methods like pyrosequencing. The sequencing process is generally observed through fluorescence/optical detectors and software allows for the comparison of the sequences found to genomic databases (Abbasian and others

2015).

1.7 SOIL ANTIBIOTIC PRODUCTION AND RESISTANCE Gene clusters that would indicate the ability of soil microbes to produce antibiotics are common throughout the soil biome, although study is limited due to a number of factors including: adsorption of antibiotics onto soil particles, nutrient limitations, and the production of secondary metabolites by soil bacteria (Laskaris and others 2010). Actinomycetes in soil are the source for a wide range of antibiotics, such as streptothricin, streptomycin, and tetracycline, and according to one study roughly one fourth of the total actinomycete population in a soil environment can be expected to produce antibiotics. The frequency of production of particular types varies widely--five percent would be expected to produce streptomycin, while vancomycin would be produced by one out of every hundred thousand bacteria in the Actinomycetes family present in the soil environment (Clardy and others 2009).

Antibiotic resistance in soil is generally found at high levels, which may be indicative of the natural antibiotic production by soil bacteria, influence of antibiotics present in the environment (such as in animal feces or wastewater), or both. A study of

480 Streptomyces isolates from various soil environments indicated average resistance to seven to eight antibiotics, and all were resistant to at least one, with resistances detected to all twenty-one antibiotics used in the study (D’Costa and others 2006).

Extensive resistance can be found even in undisturbed soils e.g. those not expected to be altered by human influence on the environment. One metagenomic study of such a soil in a remote area of Alaska indicated that it contained a diverse sampling of beta-lactamases (Monier and others 2011). However, it may be important to note that such intrinsic resistomes may be differentiated from acquired resistance through analysis; at least one study of farm and garden soils indicated that at higher doses the resistant

30 population size dropped sharply, and suggested this may be a method of differentiating weaker intrinsic resistance from acquired resistance that is adapted to higher doses of antibiotic (Esiobu and others 2002). Even so, intrinsic resistance mechanisms can be a starting point for mutations with higher levels of transferability and impact.

One study of 95 soil samples that had undergone 16S profiling indicated that there were 110 resistance genes detected with resistance against all 12 antibiotics studied, although over half of the sequences were not previously identified. Most notably, 16 resistance genes were found that had 100% nucleotide identity shared with resistance genes sequenced from clinical isolates and also contained transposons or integrons; that is, it is strongly implied that recent horizontal gene transfer had taken place between the soil bacteria and pathogenic bacteria of clinical interest, reinforcing the importance of quantifying the resistome that exists in soil, although a necessary caveat is that several of the soil samples studied were from urban and farm environments and so the potential also exists that the clinical samples impacted the soil antibiotic resistome studied (Forsberg and others 2012).

1.8 AUGMENTATIONS TO SOIL

Addition of manures and composted materials to soils raises the amount of microbiological diversity and total amount of biomass carbon, improves crop yield, and replenishes soils that have been overworked. However, the success and safety of these augmentations is variable; manures in soils can also be a reservoir for enteric pathogens such as E. coli O157:H7 and Listeria spp. The ability of these pathogens to survive depends heavily on factors such as type of manure, method of application, and processing of manure (Sharma and Reynnells 2016). Organizations such as the USDA National

Organic Program prohibit the application of uncomposted animal manures sooner than 90 days from harvest and require that composts be cured for 45 days (7 CFR 205.203) for example. One study on greenhouse addition of horse manures and poultry litters found that E. coli strains present in poultry litter-augmented soils appeared more able to resuscitate after initial dessication stress than unamended soils, likely in part due to the higher available amount of nitrogen and other nutrients for the bacteria to utilize as compared to unamended soils (Whyte and others 2014). This may be a particularly relevant observation for commercial potting soils, as poultry litter is the most commonly used manure augmentation for these products.

The presence of some trace metals in soils has a strong correlation with abundance of overall resistance, particularly in the cases of copper and zinc; primarily this has been studied at pollutant levels, but even at non-elevated levels tetracycline resistance genes tetA, tetB, tetC, tetE, and tetG are detected and code for efflux pumps that are also exporters of these metals. At weak levels, variance in normal amounts of metals found in soil appears to correlate with overall levels of antibiotic resistance

(Knapp and others 2017).

The bases of commercial soils are created using natural composting methods-- they are not comprised of soil that has been simply dug up. Composting is a microbial decomposition process that breaks down organic materials, such as lawn waste, manure, food scraps, or forest waste, to convert them to a humus-like product high in carbon and other nutrients that is used as an addition to soil or, in the case of potting soils, used as a substitute for soil. Effective composting requires highly particular conditions of nutrients, including a sufficient moisture level, and oxygen, which are then acted upon by bacteria

32 and fungi in the compost environment and broken down for use in energy. Done correctly, microbial and parasite populations are highly reduced by composting due to the buildup of heat generated by the metabolic processes of the microorganisms present.

Temperatures in a ‘hot compost’ setup can reach up to 77°C (Haug 1993). Additionally, proper composting techniques, over time, can reduce the amount of antibiotic residue present in animal feces due to the incomplete absorption by the animal’s body; for example, one study showed a 99% reduction in chlorotetracycline after 30 days of composting at 55°C (Arikan and others 2009). Accordingly, proper composting techniques may play a key role in reducing the development of antibiotic resistant bacteria in commercial soils, particularly soils augmented with manures.

Other common additions to commercial soils in addition to manures are perlite, peat, and potassium sulfate (designated as ‘sulfate of potash’ in most ingredient lists).

Perlite, a superheated volcanic glass used in soils for improving aeration and improving drainage, is also shown to help detoxify soils by binding heavy metals such as cadmium

(Vasquez and Carpena-Ruiz 2005). Peat, which is moss of the genus Spaghnum that has been partially carbonized, is used for improving the water retention of soil as well as adding carbon and nutrients, preventing soil packing, buffering pH, and preventing buildup of salts. It, like perlite, can be used to detoxify soils; the celluloses that primarily make up the moss have a number of functional groups that can bind to metals such as lead (Lee and others 2013). Both are worth noting given the association of metal pollution with the development of antibiotic resistance in soils. Potassium sulfate provides necessary potassium to plants to aid in water intake and metabolism of sugars and is used to raise the pH of soil (Bakhsh and others 1986).

Chapter 2: Project Background and Rationale

The increase in antibiotic resistant pathogens is a major threat to human health, with approximately 23,000 annually killed by untreatable bacteria in the United States alone (Frieden 2013). Control strategies implemented thus far primarily focus on reduction in direct antibiotic uses in clinical settings and food animal production, which has only had a modest impact on the overall prevalence of antibiotic resistance.

Numerous studies have demonstrated that selective pressure due to the presence of antibiotics is not solely responsible for the spread and maintenance of mobile gene elements conferring antibiotic resistance (Wang 2009). In fact, studies of infant gut microbiota have shown up to 108 CFU/g of antibiotic resistant bacteria shortly after birth despite no administration of antibiotics (Zhang 2011).

The continuing spread of antibiotic resistance even after changes have been made in the uses of antibiotics in clinical and veterinary settings implies the presence of additional risk factors yet to be understood and mitigated. Environmental pressures in the form of pollutants and other contaminants--including antibiotic residues, but not limited to them-- appears to induce important changes in

34 bacterial communities that could lead to transferable resistance (Knapp and others 2017).

Additionally, intrinsic resistance, such as immunity genes from antibiotic-producing bacteria in the environment may be a source of important transferable resistance genes.

Furthermore, data from multiple studies have illustrated the close relationship between antibiotic resistance genes found in environmental as well as clinical isolates. For instance, two resistance genes originated from environmental bacteria Kluyvera and

Shewanella (CTX-M beta-lactamase and quinolone resistance determinant QnrA encoding genes) have been found to share high homology with resistance genes in clinical pathogens

(Poirel and others 2002, Poirel and others 2005). Due to the diversity of microorganisms in the environment, particularly the difficulty in culture recovery of soil bacteria, so far there is still very limited knowledge regarding soil microbiota, particularly the profiles of antibiotic resistance, and their potential roles in antibiotic resistance ecology. Recent advancement in culture independent techniques, such as high throughput DNA sequencing, is changing our understanding of the soil microbiology.

Soils are highly diverse; 15,000 species of soil bacteria are known out of an estimated >1 million, representing 2800 genera. Primarily soil bacteria belong to the phyla Proteobacteria, Firmicutes, Actinobacteria, and Cyanobacteria, with some small contributions from others such as Acidobacteria (Orgiazzi and others 2016).

Actinomycetes in soil are the source for a wide range of antibiotics, such as streptothricin, streptomycin, and tetracycline. According to one study, roughly one fourth of the total actinomycete population in a soil environment can be expected to produce antibiotics (Clardy and others 2009).

Metagenomic methods have allowed for the study of antibiotic resistance genes in the soil, although generally found in moderate abundance. This may be indicative of the presence of intrinsic immunity genes from the antibiotic producing strains, or the presence of resistance genes in surrounding bacteria in responding to selective pressure by antibiotic residues naturally produced by soil bacteria, from environmental sources

(such as in animal feces or wastewater), or other environmental co-selective factors, etc.

A study of 480 Streptomyces isolates from various soil environments indicated average resistance to seven to eight antibiotics, and all were resistant to at least one, with resistances detected to all twenty-one antibiotics used in the study (D’Costa and others

2006). Extensive resistance can be found even in undisturbed soils e.g. those not expected to be altered by human influence on the environment. One metagenomic study of such a soil in a remote area of Alaska indicated that it contained a diverse sampling of beta-lactamases (Monier and others 2011).

Unlike soils from agricultural or isolated sources, commercial compost, manure, and potting soil mixes have not been studied. Given that they are enriched sources, often containing added manures, minerals, or fertilizers, analysis of antibiotic resistance genes present in commercial soils can provide insights into soil augmentation’s effects on antibiotic resistance genes and the overall environmental resistome. Because animal feces are rich in antibiotic resistance genes. Data on resistome of commericial soils can potentially help understand the effectiveness of composting on reduction of antibiotic resistance genes and whether commericial soils being a significant vehicle spreading antibiotic resistance gene and resistant bacteria to both contacting humans and the environment. Therefore the objective of this study was to conduct a pilot investigation for the profiles of microbiota and resistome of commercial augmented soils.

Chapter 3: Materials and Methods

Soils. Fifteen different commercial soils were obtained from local stores and used for analysis. They were as follows (level of detail in ingredients varies by type and manufacturer, although manufacturer names have been omitted for privacy reasons):

SO: Ingredients are sphaghnum peat moss, composted organics, yard waste, organic bark from fir/pine, and horticultural charcoal.

BPO: Ingredients are soils, perlite, coconut fiber, hydrolized feathermeal of turkey, turkey litter, and sulfate of potash.

SPS: Ingredients are composted pine bark, sphagnum peat moss, limestone, perlite, potassium sulfate, potassium nitrate, ammonium phosphate, urea, and sulfate of potash.

MN: ingredients are humus from peat, composted forest products, compost, manure, and pelleted poultry litter.

MMM: ingredients are compost, from any of the following sources: forest products, yard waste.

STS: ingredients are peat, composted forest products, sphagnum peat moss, and age rice hulls.

MGO: ingredients are sphagnum peat moss, composted bark, and pasteurized poultry litters.

CIT: ingredients are sand, perlite, processed forest products, sphagnum peat moss, wetting agent, soluble potash, and fertilizer comprised of polymer-coated ammonium nitrate, ammonium phosphate, calcium phosphate, and potassium sulfate (total nitrogen

0.06%).

MOO: ingredients are food waste and green waste (grass clippings, etc)-based compost and a cow manure blend that comprises approximately a quarter of the total weight. The manure is not pasteurized.

PP: ingredients are soils, sphagnum peat moss, wetting agent, and vermiculite.

OH: ingredients are composted green waste, perlite, wood shavings, and peat moss.

BG: ingredients are compost, bark, sphagnum peat moss, perlite, earthworm castings, controlled release fertilizer, and a proprietary silicon formulation.

ESP: ingredients are peat humus, sphagnum peat moss, perlite, earthworm castings, and a proprietary blend of 11 different mycorrhizae strains.

MGM: ingredients are processed forest products, sphagnum peat moss, coir, perlite, wetting agent, soluble potash, and fertilizer comprised of polymer-coated ammonium nitrate, ammonium phosphate, calcium phosphate, and potassium sulfate (total nitrogen

0.21%).

HOR: ingredients are sphagnum peat moss, composted forest products, perlite, fine sand, and pasteurized poultry litter.

Additionally, to serve as a control six non-commercial soils were obtained from the following locations: a dry, grass-free roadside area on a university campus (Columbus,

Ohio), a personal garden with no recent manure application (Westerville, Ohio), a grassy area at the edge of a commercial parking lot (Westerville, Ohio), a heavily wooded area

(Columbus, Ohio), a personal garden with no manure application (Columbus, Ohio), and the same personal garden with recent manure application (Columbus, Ohio). These samples are abbreviated CR, G, PL, W, NG, and YG, respectively.

Samples were kept at refrigeration temperature (4ºC) for storage purposes throughout.

Supplies of samples BPO and MGM were depleted before DNA sequencing and so were used solely for culture-based methods.

Plating and phenotypical analysis of resistance. Five g of each sample was added to

45g of saline (0.85% concentration) and massaged by hand for two minutes before further dilution; 500ul of 100 dilution in stomacher bag was added to 4.5ml saline for 1/10 dilution and a serial dilution was performed down to 10-6. One hundred ul of each dilution was spread-plated onto plate count agar (PCA) augmented with 0.1% cycloheximide for the prevention of mold and yeast growth. Plates were inverted and incubated for 48 hrs at 30ºC and then colony counts were taken. The study was conducted in duplication.

PCA plates with 1% cycloheximide were divided up into 60-square grids. Using sterile toothpicks, individual colonies from incubated plates were transferred to each grid using a three-stab method. Two hundred and fourty total individual colonies were taken from each sample. Inoculated grid plates were inverted and incubated for 48 hrs at 30ºC and growth/no growth assessments were made for each grid square. For non-commercial soil samples, the same method was followed and 60 total individual colonies were taken. The study was conducted in duplication.

PCA agar plates supplemented with antibiotics were prepared following procedures described previously (Zhang et al, 2011), with the following antibiotics: ampicillin

(16g/L), tetracycline (100g/L), erythromycin (100g/L), and lincomycin (16mg/L)- supplemented agars were prepared. All media also include 0.1% cycloheximide as mold inhibitor.

Antibiotic-supplemented plates were divided into 60-square grids, as above, and colonies from incubated grid plates were individually transferred onto antibiotic-containing grid plates using sterile toothpicks. Antibiotic plates were incubated for 48 hrs at 30ºC and growth/no growth assessments were made for each grid square.

Gram-staining of colonies that showed multiple resistances to antibiotics was conducted on a limited basis to get an overall idea of gram-positive/gram-negative and colony morphology properties.

PCR.

DNA amplification was performed using a BioRad MyCycler thermocycler (Bio-Rad

Laboratories, Hercules, CA) with the following reagent mix for each sample: 14.6μl deionized water, 2μl 10x standard taq reaction buffer (New England BioLabs, Ipswitch,

MA), 1μl 25mM MgCl2 (New England BioLabs, Ipswitch, MA), 0.8μl dNTP (120μl water and 20μl each 2-deoxyguanosine 5’ triposphate, 2-deoxycytidine 5’ triphosphate 2- deoxyadenosine 5’ triphosphate, 2-deoxythymidine 5’ triphosphate mix (New England

BioLabs, Ipswitch, MA)), 1μl forward primer, 1μl reverse primer, 1μl taq DNA polymerase (New England BioLabs, Ipswitch, MA), 1μl extracted sample DNA.

For primer aac3(Id), which has a Tm of 68°C for forward primer and 69.6°C for reverse primer, a standard 3-step PCR was performed, with initial denaturation at 95°C for 3 minutes, followed by a 33-cycle process with 95°C denaturation for 30 seconds, an annealing step at 64°C for 30 seconds, and an extension step at 68°C for 45 seconds,

41 followed by a final extension step at 68°C for 5 minutes. For primer catB6, which has a

Tm of 68.3°C for forward primer and 68.5 for reverse primer, a standard 3-step PCR was performed, with initial denaturation at 95°C for three minutes, followed by a 33-cycle process with 95°C denaturation for 30 seconds, an annealing step at 63°C for 30 seconds, and an extension step at 68°C for 45 seconds, followed by a final extension step at 68°C for 5 minutes. For macB primer, which has a Tm of 75.6 for forward primer and 74.9°C for reverse primer a modified two-step PCR was performed due to its high melting temperature, with initial denaturation at 95°C for 3 minutes, a 33-cycle process with 95°C denaturation for 30 seconds and a combined annealing and extension step at 70°C for 80 seconds, followed by a final extension step at 70°C for five minutes and a hold temperature of 10°C.

Gel electrophoresis

Gels with 1.5% agarose were prepared for gel electrophoresis, following standard protocol.

Gels were placed in an Embi Tec Run One electrophoresis cell (Embi Tec, San Diego,

CA) and the cell was filled up to the line with 1XTAE buffer. 6ul of a 1kb DNA ladder

(10x loading buffer pre-added) was added to the first lane in all gels. Ten ul of 10x loading buffer was mixed with each sample as well as positive and negative controls. 7ul total mixture was loaded into each well.

The electrophoresis was conducted at 100V, and gel was staining in 0.5ug/ml ethidium bromide in distilled water and destaining with distilled water following standard procedures,

Gel imaging was done using a Biorad Universal Hood II ChemiDoc XRS molecular imager (Biorad, Hercules, CA) using UV transillumination and slow lens control. Images were acquired with Quantity One 1-D analysis software (Biorad, Hercules, CA) and printed using a dye sub photo printer (Mitsubishi, Tokyo, Japan).

DNA sequencing

DNA sequencing was conducted by the Biomedical Genomics Core at Nationwide

Children’s Hospital (Columbus, OH). Extraction of DNA was performed using a

QIAamp DNeasy PowerSoil kit (Quiagen, Hilden, Germany) according to its included protocol. DNA concentration and purity was assessed before sending for sequencing using a Spectronic Genesys 5 spectrophotometer (Thermo Scientific, Waltham, MA).

Extracted DNA from all soil samples was pooled before sequencing.

Processing of sequencing data was done using Trim Galore! software (Babraham

Bioinformatics, Cambridge, UK) and quality and reads filters were applied (option: -q 28

–fastqc –paired –stringency 6). Low quality reads (phred score lower than 28) and short reads (read length below 75 bp) were removed. The quality of sequencing reads was then checked by FastQC (version 0.11.5) implemented in Trim Galore! Filtered reads were then mapped to a customized The Comprehensive Antibiotic Resistance Gene Database

(CARD) using Vmatch (version 2.2.5), allowing one mismatched amino acid per read and alignment length >=25 amino acids (options “-showdesc 60 -dnavsprot 11 -l 25 -h 1).

The abundance of resistance genes was then calculated by normalizing hit numbers to

16S rDNA reads number per sample (Li 2017).

Primer design. Antibiotic resistance genes in relatively high abundance in pooled sample by metagenomics were further subjected to PCR assessment for their prevalence in

43 individual soil samples. Three primers were designed to detect the presence of relevant genes in each individual sample. Protein ID numbers obtained from sequencing analysis were used to search for genes using the National Center for Biotechnology Information’s

(NCBI) protein database. Using NCBI records of DNA sequences that corresponded to the proteins in question, the ‘primer-BLAST’ tool was used to design custom primers.

Primers selected for consideration would result in PCR fragment of approximately 200-

300 base pairs in length. All primers designed were checked using DNAStar Primer

Select software (DNASTAR Inc., Madison, WI) for hairpin loops and amount of dimers, with only those under 10% being kept for consideration. Three primers that fit all relevant criterion were sent to Sigma Aldrich (St. Louis, MO) to be synthesized.

Chapter 4: Results

Basic soil data.

Figure 1. Log CFU of soil samples spread plated on PCA agar and incubated for 48 hours at 30°C The highest bacterial colony counts were detected in MOO, OH, and MGM samples, and the lowest colony counts were detected in PP and HOR soil mixes, as well as the moderately-low MN.

Figure 2. Log CFU for noncommercial samples spread-plated on PCA agar and incubated for 48 hrs at 30ºC. There was less variation in initial microbial population present in noncommercial soil samples relative to commercial varieties, despite samples being taken from a variety of locations. Initial microbial population was lowest for YG, the garden soil which had been augmented with manure, although it also had the highest level of variance (log standard deviation 0.66). CR, a sample that was dusty, fine-grained, and light in color and was most visually dissimilar to all other noncommercial samples, showed a slightly higher microbial population, but was not as dissimilar as might be expected. It did not follow the same pattern as observed in the visually dry commercial soil samples.

Table 1: pH of commercial soil samples as determined by handheld pH meter

Sample PH

ESP 7.2

HOR 6.5

SPS 6.4

PP 5.5

MGO 6

BG 6.1

MMM 6.7

MN 6.6

OH 6.2

STS 6.5

CIT 6.3

MOO 7.6

SO 6.7

Highest pH was observed in sample MOO, expected due to cow manure’s ability to raise soil pH due to minerals such as calcium and magnesium present in the manure (Zhang

1998). Mycorrhizae in sample ESP grow more optimally at high pH and so soil pH may have been adjusted upwards to accommodate this.

Table 2: pH of noncommercial control soils as determined by handheld pH meter

Sample pH

CR 6.5

PL 6.3

YG 6.2

W 6

G 6.5

NG 6.2

No control samples exhibited a pH higher than 6.5, unlike 7 of 13 commercial samples

(table 1), indicating that augmentation may alter pH in general.

250

200

150 A 100 L E Numberofcolonies 50 T

Sample

Figure 3. Growth of colonies on antibiotic-containing PCA plates (A: Ampicillin, L: Lincomycin, E: Erythromycin, T: Tetracycline) after 48 hrs incubation at 30°C, commercial samples. All soil samples followed a similar pattern of growth, in that ampicillin and lincomycin- containing plates showed considerably less suppression of colony growth than plates containing erythromycin or tetracycline. No apparent correlation between pH levels of the soil and associated soil diversity with levels of antibiotic resistance appear to be present in these samples.

For samples grown on PCA agar, the total percentage of resistance to each antibiotic was

66% for ampicillin, 77% for lincomycin, 15% for erythromycin, and 9% for tetracycline.

It should be noted that gram-negative bacteria would not be affected by lincomycin so the high level of resistance may indicate the antibiotic was ineffective due to intrinsic insensitivity associated with the particular bacterial type. In the meantime, many gram- negative bacteria produce beta-lactamase.

Figure 4. Growth of colonies on antibiotic-containing PCA plates (A: Ampicillin, L: Lincomycin, E: Erythromycin, T: Tetracycline) after 48 hrs incubation at 30°C, noncommercial samples. Noncommercial samples exhibited a somewhat different pattern of resistance to commercial soils, most notably in the low-to-no erythromycin resistance present; only sample NG shows any notable erythromycin resistance, and three out of the six exhibit zero. The two others with any detectable erythromycin resistance, interestingly, are the other samples taken from home gardens, although their levels are very low. Further research could establish if this is a consistent effect. While pH has a strong effect on microbial diversity in soils, this does not appear to mean higher rates of antibiotic resistance given that the soil sample with the highest level of resistance to three or more antibiotics is NG, whose pH is lower than that of most other noncommercial soil samples

(Table 2).

Figure 5. Multidrug resistance detected in colonies on antibiotic-containing PCA plates incubated for 48 hrs at 30°C, commercial samples. For the majority analyzed, resistance to two antibiotics out of four was most common; generally, this represented resistance to both ampicillin and lincomycin, probably indicating in part the proportion of Gram-negative organisms being dominant. SO, markedly compositionally different than the others, may have more Gram-positive organisms or susceptible to beta-lactam Gram-negatives. Likewise, samples ESP, MGM,

MMM, and HOR may contain more Gram-positive organisms; unlike SO, they also exhibited a high level of colonies resistant to no antibiotics. Samples SPS, MGO, and

CIT had notably higher levels of multiresistance (resistance to four antibiotics) as compared to all others, and may be an appropriate place of focus for further analysis.

Bacterial profiles of soil samples.

Figure 6. Main bacterial phyla represented in pooled DNA after deep sequencing; phyla containing more than 50 bacteria present in soil sample only are represented. Metagenomic sequence analysis identified a total of 59 phyla were in the pooled soil sample, representing 2118 different genera, with the vast majority of bacteria present belonging to the phylum Proteobacteria. Bacteria belonging to this phylum are Gram- negative and encompass both pathogens such as Salmonella and bacteria with nitrogen fixing capabilities. Acidobacteria and Bacteriodetes were also well-represented; both are commonly found in soil, and like Proteobacteria, Bacteriodetes are Gram-negative organisms. Acidobacteria are mostly unculturable bacteria and so their general metabolic and structural characteristics are not well-quantified (Quaiser and others 2003).

Figure 7. Main bacterial classes represented in pooled DNA after deep sequencing; only classes containing more than 100 reads in soil samples are illustrated. A total of 158 classes of bacteria were represented in the sequenced pooled DNA, primarily alphaproteobacteria, betaproteobacteria, and gammaproteobacteria, all belonging to the dominant phylum Proteobacteria (fig. 6); alphaproteobacteria include

Rhizobium and other bacteria that work in conjunction with plants as well as the pathogen

Rikketsia. Betaproteobacteria include nitrogen-fixing bacteria as well as the pathogens

Neisseria gonorrhea and Neisseria menningitides. Gammaproteobacteria encompass several major pathogens, such as Salmonella, Escherischia coli, and Vibrio cholerae

(Brenner and others 2005).

Resistome of soil samples.

Metagenomic sequence analysis of the pooled soil sample also identified the profile of antibiotic resistance genes. 53

160

140

120

100

20 Numberof resistance gene sequencehits 0

Antibiotic type

Figure 8. Antibiotic resistance gene sequence hits in pooled soil sample. Aminoglycoside resistance predominated in pooled soil samples, with genes encoding resistance to macrolides and vancomycin also at elevated levels (Fig. 8).

Aminoglycosides as a class originate from various Streptomyces species and therefore the presence of high levels of resistance genes may therefore be related to intrinsic resistance due to antibiotic production by the species. Likewise, macrolides originate from

Saccharopolyspora erythraea and vancomycin from Amycolatopsis orientalis, both soil bacteria.

32,568, 973 total reads were detected during sequencing, 14,651 from 16S rRNA. The antibiotic resistance gene hits per 16S rRNA were 0.0233 and resistance gene percentage as percentage of total reads was 1.05x10-5.

Table 3: Predominant resistance genes present in deep sequenced DNA from pooled soil sample

Type Predominant genes # of hits NCBI protein reference #

Aminoglycoside AAC(1) 26 296245050

AAC(3)-Vla 25 157412102

AAC(3)-Id 49 38490045

Beta-lactam TEM-162 13 134154077

TEM-130 16 56311400

IMP-32 18 403309642

Chloramphenicol catB6 42 4210826

Macrolide macB 33 56385102

msrC 32 12659044

Quinolone qepA 4 374434363

Sulfonamide sul1 16 339021682

Tetracycline tetG 8 4585570

tet30 6 3860032

Vancomycin vanXB 11 AAB05628.1

vanSI 19 WP_011461302.1

Figure 9. 16S PCR amplification of 16S rRNA gene fragment with DNA extracted by soil kit. Using DNA extracted by the soil kit for PCR using the 16S rRNA primer pair, 10 of 13 samples exhibited an amplification band with the expected size. This result implies that the soil kit was successful at extracting DNA from soil. Successful extractions were used for subsequent testing with custom primers for antibiotic resistance genes.

Table 4: Designed primers for DNA sequencing Sequence (5'->3') GC% Tm Product size aac(3)-Id + GCCCTGCTCGTCGATCTCTT 60.00 62.01 341 bp

- TCTGGCGGCGAGTTCCATAG 60.00 62.02 catB6 + GTCACCGGCATGACTGGGTA 60.00 61.90 313 bp

_ GGCCAGTTCCACCACTCCAT 60.00 62.14 macB + TGCTCGGCATCATCATCGGT 60.00 62.03 221 bp

- CGTGGCGGAAGCAACATAGC 55.00 62.31 Aac(3)-Id is an aminoglycoside acetyltransferase, NCBI reference number 38490045.

CatB6 is a chloramphenicol acetyltransferase, NCBI reference number 4210826. MacB is a component of the MacA-MacB efflux system, NCBI reference number 56385102.

Figure 10. 16S PCR amplification of 16S gene fragment aac(3)-Id in commercial soil samples. As illustrated in Fig. 10, a positive band with approximate size 341bp was observed for lanes 1, 2, 3, 6, and 10, corresponding to samples HOR, SPS, BG, MOO, and MN. SPS sample was further verified as positive through DNA sequencing. MN sample was also sequenced and showed 100% homology to gene aada7, a streptomycin 3”- adenyltransferase, and 98% homology to aac(3)-Id. The two sequences are 99% similar as verified by NCBI Blast and as such the primer may be able to detect both.

Figure 11. 16S PCR amplification of gene fragment aac(3)-Id in noncommercial soil samples.

Positive confirmation was made for one sample, G, with expected band at 341bp (lane 4).

Sample YG (lane 5) shows the correct band at 341bp but also a second band at approximately 500bp.

Figure 12. 16S PCR amplification of gene fragment catB6 in commercial soil samples. One positive result, CIT, was identified among all samples, with detected band at approximately 310 bp as expected although DNA sequencing confirmation of positive result was unsuccessful. Noncommercial soil samples did not test positive for this gene

Chapter 5: Discussion

As illustrated, half of commercial soil samples (fig. 1) tested had higher initial bacterial counts than noncommercial controls (fig. 2). MOO samples were confirmed by the manufacturer to be non-pasteurized with approximately 25% cow manure, which would be in keeping with a high initial microbial count. OH contained no manures and no particularly notable ingredients, though given that ‘green waste’ is a nonspecific term, properties of the plant materials or composting process may have impacted the level of microbial load. MGM, like CIT, contained a polymer-coated fertilizer mix, though unlike

CIT, had a moderately high level of added nitrogen (0.21%), which may contribute to ability of microbes in the mix to grow. PP was an extremely dry, bulky mix, similar to sawdust in consistency and with moisture control compounds added such that the water activity of the initial mix may have been too low to support high microbial loads.

Similarly, MN, a mulch and manure mix, was in large part made up of large, dry wood pieces as well as manure, an environment likely to be less supporting of microbial life than soil--but it still contained manure, and so showed slightly higher levels of growth.

Unlike other mixes, HOR mix contained sand, which created lighter soil for plants but was not a nutrient-positive addition for microbes (though without knowing the exact percentage of sand or examining it as a standalone factor it is difficult to quantify how much impact the sand addition is). It also contained pasteurized manure.

Other mixes do as well, but it is useful to contrast that with unpasteurized samples like

MOO.

Natural soil samples grown on PCA agar as reported in literature tend to have low to moderate initial microbial populations and in general significantly less than manures and somewhat less than potting soils (Chikere and Udochukwu 2014, Roth 2012).

A previous study has shown a high rate of tetracycline resistance in soils using culture-dependent methods, ranging from 47-98% of all bacteria studied, and additional high levels of resistance to ampicillin in dairy farm, dairy manure, and residential garden soils (Esiobu and others 2002). This was not the observed pattern in cultured commercial samples in this study for tetracycline although high ampicillin resistance rates were in agreement; however, the concentration used in this study was higher than both the low

(35ug/ml) and high (170ug/ml) concentrations of tetracycline used by Esiobu et al. Other studies have shown culturable soil bacteria with more similar resistance patterns to the commercial soils studied, with high rates of resistance to ampicillin and high levels of susceptibility to tetracycline, attributed largely to the high levels of Gram-negative organisms as a proportion of the overall soil bacterial makeup, where beta-lactamase production is common (Nwosu 2001, Nwosu and Lapado 1999). However, these studies also indicated elevated levels of resistance to erythromycin in culturable soil bacteria, whereas studied samples were highly susceptible to erythromycin except in the case of sample MGO, which was 42% resistant (fig. 3). This pattern is even more distinct in the noncommercial samples.

Likewise, another study indicated 34.7% resistance to erythromycin and 10.2% resistance to tetracycline in soil samples that included compost samples. This is consistent with the 9% tetracycline resistance rate determined in this study but a higher rate of resistance to erythromycin than studied, 15% (Popowska and others 2012). These

62 discrepancies may speculatively be due to the variability in culturing methods for soil bacterial analysis.

The predominant types of antibiotic resistance indicated through deep sequencing are notable (fig. 8); in some respects they correlate well with a previous study of

Proteobacteria in soil that indicated moderate levels of chloramphenicol resistance, and low levels of tetracycline resistance (Forsberg and others 2012). However, beta-lactam antibiotic resistance hits were much lower in this study. By contrast, a study on the profile of unique resistance genes in cow manure showed that kanamycin and chloramphenicol resistances predominated (Wichmann and others 2014). Poultry manure analysis in one study showed predominantly quinolone and sulfonamide resistance (Mu and others 2015). However, it is important to note that deep sequencing data in this study was obtained through a pooled sample; not all of the studied commercial soils were augmented with manures, and some manures used were pasteurized, and so any alterations to the overall resistance profile of any given sample due to the presence of manures may be difficult to elucidate without sequencing that particular individual sample.

The number of ARGs per 16S rRNA, 0.0233, is comparable to previous studies indicating a range of 0.02 to 0.03 (Li and others 2015) or 0.002 to 0.02 (Pal and others

2016). This is as compared to studies of swine, cattle, and sheep feces which indicate elevated rates ranging from 0.75 to 3 ARG/16S (Gerzova and others 2015, Li and others

2015, Noyes and others 2016, Li 2017).

Aac(3)-Id was analyzed and confirmed in five commercial and one noncommercial control sample. Genes sharing 100% nucleotide identity have been described in previous studies as part of Salmonella genomic island 1 (SGI1), a chromosomal genetic island 43- kb in size that contains a resistance gene clusters encoding against ApCmFfSmSpSuTc

(ampicillin, chloramphenicol, florfenicol, streptomycin, spectinomycin, sulfonamides, and tetracycline).

Other aac(3)-I variants and related genes (such as aac(3)-IV) have been widely studied and reported in manures, but no data appears to yet exist for aac(3)-Id in soils and manures.

Aac(3)-Id as a gene fragment has also been found in Salmonella Newport, an emerging problem for bovine populations, with infection rates possibly up to 3.5% of all dairy herds, and viable Salmonella Newport is capable of surviving at detectable levels for up to 184 days in manure (You and others 2006). Sample MOO, which contained unpasteurized cow manure, tested positive for aac(3)-Id.

The positive result from noncommercial control soil, G, was manured using MOO two years previous to the study.

catB6 was found in one sample, CIT. A fragment sharing 100% homology was identified in literature as a cassette within the In31 integron, a functional close relative of catB5 that conveys chloramphenicol resistance. It is an acetyltransferase-encoding allele, and likely only conveys a low-level of resistance when not in the presence of other promoters such as lac. It has been identified as part of the pPAM-101 plasmid (Laraki and others 1999).

Despite only being found in the CIT sample, 42 copies of the gene were identified during deep sequencing, indicating that it is likely present at high levels in CIT. Despite the only ingredients within CIT differentiating it from other samples are that it contained both a wetting agent and a polymer-based fertilizer, neither of which have been linked to increased antibiotic resistance thus far, the sources of other ingredients may be different among soil samples. In fact, although no wetting agent information was provided by the manufacturer, a wetting agent would be expected to have some negative effect on the ability of Pseudomonas to produce biofilms, which are associated with increased rates of gene transfer (Teh and others 2015).

Commercial soils appear to be roughly comparable to other soils and sediments in terms of being reservoirs for antibiotic resistance genes. As such, this preliminary assessment is that they do not appear to represent a rich source for these genes as compared to compounds such as animal feces, which are also used to assist in the growth of plants.

Chapter 6: Future Directions

Future analysis of commercial soils to expand on this study should include further testing of genes present as indicated by deep sequencing to determine if any other genes in high abundance are present in multiple samples, particularly those genes associated with mobile genetic elements. Deep sequencing on individual samples should be done, as well as real-time PCR for quantification of levels of genes present. It should be determined if any more conclusive links between types of augmentation and particular resistance genes exist, such as through recreation of conditions for producing commercial soils with only one type of augmentation added at a time; similarly, mineral analysis of soil samples should be conducted to gain a fuller picture of the composition of the soils. Comparison analysis of manures in similar conditions should also be done as well as analysis of transferability of soil bacterial ARGs to crops. In general, more analysis of commercial soils in any direction is needed to more fully understand their place in the soil resistome.

The current picture is incomplete.

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