http://informahealthcare.com/mbyISSN: 1040-841X (print), 1549-7828 (electronic)

Crit Rev Microbiol, Early Online: 1–14! 2014 Informa Healthcare USA, Inc. DOI: 10.3109/1040841X.2013.875982

REVIEW ARTICLE

Antibiotrophs: The complexity of antibiotic-subsisting andantibiotic-resistant microorganisms

Yvon Woappi1, Prashant Gabani1, Arya Singh2, and Om V. Singh1

1Division of Biological and Health Sciences, University of Pittsburgh, Bradford, PA, USA and 2Department of Computer Science, Texas State

University, San Marcos, TX, USA

Abstract

Widespread overuse of antibiotics has led to the emergence of numerous antibiotic-resistantbacteria; among these are antibiotic-subsisting strains capable of surviving in environmentswith antibiotics as the sole carbon source. This unparalleled expansion of antibiotic resistancereveals the potent and diversified resistance abilities of certain bacterial strains. Moreover,these strains often possess hypermutator phenotypes and virulence transmissibility competentfor genomic and proteomic propagation and pathogenicity. Pragmatic and prospicientapproaches will be necessary to develop efficient therapeutic methods against such bacteriaand to understand the extent of their genomic adaptability. This review aims to reveal theniches of these antibiotic-catabolizing microbes and assesses the underlying factors linkingnatural microbial antibiotic production, multidrug resistance, and antibiotic-subsistence.

Keywords

Antibiotic-production, antibiotic-resistance,antibiotic-subsistence, antibiotrophs,extremophiles, gene-transfer, multi-drugresistance, systems biology

History

Received 1 October 2013Revised 6 December 2013Accepted 12 December 2013Published online 4 February 2014

Introduction

Bacterial survival has been optimized by fast reproduction

cycles, frequent genomic interchange and swift metabolic

adaptability. This metabolic flexibility can trigger the forma-

tion of secondary metabolites (e.g. antibiotics and toxins) that

are not essential for the growth and reproduction of the

organisms that produce them. An antibiotic has been defined

as an organic compound produced by one microorganism to

inhibit the growth of another; however, this definition does not

reflect non-microbial sources (e.g. plants). For any one

antibiotic, there is a specific group of microorganisms

comprising its inhibition spectrum, meaning they are sensitive

to the antibiotic at therapeutically possible dosage levels

(Canton & Morosini, 2011). However, the most common

antibiotics and respective microorganisms (i.e. bacteria and

fungi) in nature, as summarized in Table 1, may enforce long-

term selective pressure for the emergence of resistance,

generating another branch of extremophiles – antibiotic-

resistant extremophiles (ARE) (Gabani et al., 2012; Hawkey

& Jones, 2009; Helling et al., 2002; Kajander & Ciftcioglu,

1999; Nikaido, 2009).

The bacterial spectrum can be divided into five central

metabolic groupings: (i) antibiotic producers, (ii) antibiotic-

resistant, (iii) both antibiotic producer and resistant, (iv) non-

resistant, and (v) non-antibiotic-producing. The cellular

mechanisms for biosynthesis of secondary metabolites, i.e.

antibiotics, and the molecular genetics of the respective

microorganisms have been well studied over the years

(Helling et al., 2002; Nikaido, 2009). However, the metab-

olism of unmetabolized drugs from the extensive use of

antibiotics in humans and animals has yet to be understood.

Prolonged exposure to residual antibiotics under both in vivo

and in vitro conditions produces microorganisms that, under

selective pressure, evolve into AREs (Gabani et al., 2012).

Antibiotic resistance in bacteria could be defined as the

microbial ability to sustain and multiply in the presence of

antibiotics (Aminov & Mackie, 2007), which has raised

global concern due to its devastating impacts, such as spread

of infections across continents and prolonged illness. The

rapidity with which many resistances have appeared after the

introduction of new antibiotics suggests that resistance genes

were already present in nature prior to human use of

antibiotics. Exclusively antibiotic-resistant strains have been

identified and their swift resistance adaptation patterns have

been strongly linked to horizontal gene transfer (HGT)

(Canton & Morosini, 2011; Liebert et al., 1999). The

intensifying relevance of resistant pathogens has, however,

refocused contemporary studies toward resistance mechan-

isms, leaving a relatively small amount of research investigat-

ing natural antibiotic production and its links to evolving

intercellular communication toward resistance (Martin et al.,

2005). Hence, an understanding of antibiotic production

and resistance acquisition is more relevant today than ever

before.

Over the past several decades, the methods of pathogenic

eradication have proven largely inefficient and unrealistic.

In fact, they have promoted microbial propagation and have

Address for correspondence: Om V. Singh, University of Pittsburgh,Divison of Biological and Health Sciences, 300 Campus Drive,Bradford, PA 16701 USA. E-mail: ovs11@pitt.edu, ovs11@yahoo.com

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Table 1. Biosynthesis of secondary metabolites, i.e. antibiotics, in most common bacterial and fungal origin*.

Bacterial originSecondary metabolites

(i.e. antibiotics) Fungal originSecondary metabolites

(i.e. antibiotics)

Amycolatopsis lactamdurans Cephamycin C Cephalosorium acremonium Cephalosporin CBacillus licheniformic Bacitracin Penicillium chrysogenum,

P. griseofulvin, P. urticaePenicillins, Griseofulvin, Patulin,

respectively.Bacillus subtillis Bacillin, Subtillin Aspergillus nidulans PenicillinErwinia chrysanthemi (Dickeya dadantii) Indigoidine Acremonium chrysogenum CephalosporinLysobacter lactamgenus Cephabacin Cercospora kikuchii CercosporinMicromonospora sp. Micromonosorin Cochliobolus carbonum HC-toxinNocardia uniformis Nocardicin A Pseudallescheria boydii PseudallinPseudomonas aureofaciens Pyrrolnitrin Mucor ramannianus RamycinStreptomyces antibioticus Actinomycin, Oleandomycin Carpenteles brefeldianum GriseofulvinStreptomyces griseus Indolmycin, Streptomycin,

CandicidinCordyceps militaris Cordycepin

Streptomyces kanamyceticus Kanamycin Giberella baccata Baccatin AStreptomyces fradiae Neomycin Nectria radicicola, Monosporium

bonordenRadicicol

Streptomyces albinogen Puromycin Chaetomium aureum, C. trilaterale OosporeinStreptomyces sioyaensis Siomycin C. cochliodes Chetomin, Orsenillic acidStreptomyces lavendulae Streptothricin Edothia parasitica DiaporthinStreptomyces cinnamonesis Monensin Neurospora crassa SpermineStreptomyces veneguelae Chloramphenicol Lambertela corni-maris, L.

hicoriaeLambertellin

Streptomyces verticillatus Mitomycin Mollisia caesia, M. gallens MollisinStreptomyces caelestis Celesticetin Blennoria sp. CitrininStreptomyces cacaoi Polyonins L & M Pestalotia ramulosa RamulosinStreptomyces spinosus Spinosad Candida albicans MycobacillinStreptomyces hygnoscopicus Rapamycin Achorion gypseum AchoricineStreptomyces pencetius Avermectin Aspergillus giganteus Alpha-SarcinStreptomyces erythrea Erythromycin A. amstelodami, A. proliferans, A.

restrictus, A. variecolor, A.nidulans, A. flavipes, A. humi-cola, A. niger, A. velutinus, A.oryzae

Amodins A&B, Proliferin,Restrictosin, Variecolin,Cordycepin, Flavipin,Humicolin, Jawaharene,Velutinin, Hydroxyaspergillicacid, respectively.

Streptomyces thermotolerans Carbomycin A. fumigatus Helvonic acid, Fumigallin,Trypacidin

Streptomyces peucetius Daunorubicin Beauveria bassiana OosporeinStreptomyces argillaceus Mithramycin Cephalosporium cellulens,

C. salmosynnematumSellenin (Cellulenin),

CephalosporinsStreptomyces natalensis Pimaricin Cephalosporium sp. CephalothecinStreptomyces ambophaciens Spiramycin Clavariopsis aquatic CitrininStreptomyces fradiae Tylosin Dendrodochium toxicum DendrodochinStreptomyces coelicolor Actinorhodin Fusidium coccineum FucidinStreptomyces clavuligerus Cephamycin C Paecilomyces persicinus, P. var-

ioti, P. brefeldianum, P. fre-quentans, P. cyaneum, P.canescens, P. albidum, P. nota-tum, P. paxilli,

Cephalosporin N, Variotin,Brefeldin, Frequentin, Cyanein,Canescin, Albidin,Xanthocillin, Nordin,respectively.

Streptomyces maritimus Enterocin Oospora aurantia, O. colorans, O.virescens

Oosporein, Virescin, respectively.

Streptomyces roseofulvum Frenolicin Cephalosporium sp. SynnematinStreptomyces lincolnensis Lincomycin Fusarium lateritium, Fusarium sp. Locabiotal, Chlamydosporins,

respectively.Streptomyces coelicolor MethylenomycinStreptomyces rimosus TetracyclinStreptomyces pristinaespiralis PristinamycinStreptomyces alboniger PuromycinStreptomyces glaucescens TetracenomycinStreptomyces cattleya ThienamycinStreptomyces sp. NovobiocinStreptomyces sp. P-8648 ViridogriseinThermophilic actinomycetes Thermomycin, Thermocyridin,

Refcin (anthracin)

*Data collected from multiple articles available at http://www.ncbi.nlm.nih.gov/pubmed and http://www.scopus.com/home.url using key words forbacteria and fungal origin antibiotics.

2 Y. Woappi et al. Crit Rev Microbiol, Early Online: 1–14

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resulted in more cases of multi-drug-resistant strains (MDR)

(Nakata & Tang, 2008, Sahoo et al., 2010, Magiorakos et al.,

2012). Combating MDR with proficient, pragmatic strategies

will be necessary to put a halt to the expansion of resistance

and to develop adequate therapies. In this review, we assess

the underlying factors linking natural microbial antibiotic

production, multidrug resistance, and antibiotic subsistence.

We also present promising approaches to combat nosocomial

pathogens and panresistant strains.

Perspectives of antibiotic catabolism and origin ofresistance

The ethnopharmacolic focus drastically changed in the 20th

century as microorganisms with various antibiotic-producing

capabilities were identified (Goldberg et al., 1999; Rahmati

et al., 2002). It eventually became apparent that, in nature,

actinomyces and bacteria undertake the vast majority of

antibiotic synthesis. Currently, over 80% of clinically used

antibiotics are derived from soil-dwelling bacteria, and the

benefits have been manifested through their applications in

surgical transplants, everyday infections treatment, and as

chemotherapeutic agents and agrochemicals (Besier et al.,

2007; Effmert et al., 2012; Woappi et al., 2013).

The appearance of antibiotic-resistant microbes within

health care centers was the first indication of an evolving

microbial resistance. This paved the way for the development

of several synthetic and semisynthetic antibiotics, such as

Prontosil (reviewed by Barr, 2011; Foster & Woodruff, 2010).

In the 1950s, numerous strains of MDR were identified in

hospitals and clinics around the world. This was driven by the

exposure of pathogens to sub-inhibitory antibiotic levels,

which increased the clinical demand for more potent

antibiotics and abruptly halted the search for natural anti-

biotics. The research refocus was almost entirely centered on

designing novel synthetic antibiotics, with the hope that their

chemical compositions would be foreign enough to nature to

prevent bacteria from developing resistance.

In 1959, a promising synthetic antibiotic, methicillin, was

designed and introduced in clinics and hospitals worldwide.

A chronicle of these occurrences was elegantly presented and

reviewed (Foster & Woodruff, 2010). Such antibiotics were

further complemented by the advent of quinolones, but this

approach was again disappointingly interrupted with reported

cases of nalidixic acid-resistant strains, then extremely drug-

resistant strains (XDR) such as vancomycin-resistant enter-

ococci (VRE), penicillin-resistant Streptococcus pneumonia

(PSRP), and eventually totally resistant strains (TDR), notably

methicillin-resistant Staphylococcus aureus (MRSA) (Canton

& Morosini, 2011; Magiorakos et al., 2012; McAdam et al.,

2012; Tenover, 2006). Over half a century later, TDR strains

remain the leading cause of nosocomial infections in the

world (Maal-Bared et al., 2013), confirming the ineffective-

ness of synthetic and semisynthetic antibiotics as a long-term

solution against antibiotic resistance.

The overproduction, overuse and misuse of antibiotics

have made it commonplace for microbial populations to be in

contact with sub-therapeutic levels of antibiotics in the

environment. These sub-inhibitory exposures have allowed

strains possessing intrinsic antibiotic resistance traits to

gradually adapt and develop mechanisms for voiding anti-

biotic-induced toxicity, thus progressively improving fitness

cost. It is now required to deal with antibiotic metabolizers

and panresistant strains – microbes, which have been exposed

to all known clinical antibiotics and have demonstrated

resistance to every single one of them (Dhar & McKinney,

2007). These bacteria reveal a new cohort of resistant

microorganisms, as they differ from the naturally occurring,

primeval antibiotic-resistant microbiota.

Emergence of antibiotrophs

The commonality of antibiotic resistance in microorganisms

over the past several decades reveals the frightening tenacious

pliability of microbes, including pathogens. The World Health

Organization (WHO), the Centers for Disease Control (CDC),

and private groups such as the Infectious Disease Society of

America (IDSA) have recognized antibiotic resistance as a

pandemic (Anderson, 1999; Magiorakos et al., 2012; Robicsek,

2005). Dantas et al. (2008) isolated microbes that were

resistant to a plethora of antibiotics and capable of catabolizing

non-synthetic, synthetic, and semi-synthetic antibiotics,

including amphenicols, at concentrations 50 times higher

than what is considered normal resistance threshold. The

isolates not only escaped the cytotoxic effects of the peptides,

but also were able to catabolize and subsist under them in an

environment free of alternative carbon source. Recently,

numerous strains of Salmonella featuring antibiotic-subsisting

abilities were isolated (Barnhill et al., 2010), and chloram-

phenicol-subsisting isolates were identified later in Asia (Xin

et al., 2012). The variety of bacteria adapting to proliferate

under harsh environmental conditions, e.g. extreme dosages of

antibiotics lethal to normal microorganisms, could be referred

to as ‘‘antibiotic-resistant extremophiles (AREs)’’ (Gabani

et al., 2012). Here we propose the term antibiotrophs, from

the Greek anti (against), bio (life) and trophe (food), to

depict microorganisms capable of subsisting in environments

containing abnormally elevated antibiotic concentrations or

antibiotics as the sole carbon source.

Antibiotrophic niches

Microorganisms (i.e. bacteria and fungi) possessing resistance

and catabolic capacities against specific antibiotics and/or bio-

chemicals within unusual microenvironments (Barnhill et al.,

2010; Dantas et al., 2008; Frank-Petersise et al., 2011; Gabani

et al., 2012; Singh & Walker 2006; Xin et al., 2012) can be

referred to as antibiotrophs. Anthropocentric activities have

undoubtedly been the paramount catalysts in the development

of this resistant cohort. Increases in intercontinental travels,

farming, and soil exchange within human settings have

exposed these strains – along with the rest of the resistance-

bearing microbial flora in nature – to human therapeutics

(Baquero et al., 2013; Barbe et al., 2004; Canton & Morosini,

2011; Falagas & Billiziotis, 2007). Through these exposures,

antibiotrophs likely developed metabolic enzymes while

retaining their unique catabolic competence (Figure 1).

The absence of alternative nutritional carbon-resources in

environments with high human presence is quite rare

and was therefore believed to be a poor driving criterion for

the emergence of antibiotic-subsisting bacteria. However,

DOI: 10.3109/1040841X.2013.875982 Antibiotrophs: The complexity of antibiotic-subsisting 3

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subsistence on antibiotics as a sole carbon source has been

shown to be the central benchmark of their existence

(Maruyama et al., 2006; Nybom et al., 2008; Xin et al.,

2012). The antibiotrophic grouping is evidently much larger

than originally anticipated, and embodies microorganisms

capable not only of subsistence, but also of MDR gene

transmission, antibiotic detoxification, and even antibiotic

production (Barnhill et al., 2010, Xin et al., 2012, Walsh

et al., 2013, Martinez & Rojo, 2011) (Table 2). They

principally differ from most resistant microbes by their

ability to both neutralize and catabolize antibiotics for

nutrition and cellular homeostasis (Barnhill et al., 2010;

Martinez, 2006; Romero et al., 2011; Xin et al., 2012). This

cohort certainly incorporates microorganisms able to subsist

on abnormally elevated antibiotic gradients, whether present

as the sole carbon sources or not.

In past, studies have revealed the diversified microbio-

sphere upsurge in the evolutionary development of new

antibiotic resistant microorganisms (Dhar & McKinney, 2007;

Gabani et al., 2012; Magiorakos et al., 2012; Singh & Walker,

2006). A prominent antibiotrophic niche has been studies

within the veterinary cohort (Barnhill et al., 2010). Dantas

et al. (2008) observed higher antibiotrophic activity in urban

soils compared to soil obtained from farmlands, with most

isolates belonging to the Proteobacteria, Antinobacteria and

Bacteroidetes phyla, with Burkholderiales, Pseudomonadales

and Enterobacteriales representing the most populous orders.

Health care centers, clinics, and agricultural environments are

locations likely harboring the most elevated populations of

these microbes. Given their resistance, antibiotrophs’ gen-

omic profile likely possesses an enhanced degree of trans-

missibility and a widespread pathogenic spectrum (Hawkey &

Jones, 2009; Maal-Bared et al., 2013).

Mechanisms driving antibiotic resistance inantibiotrophs

The paramount mechanisms underlying the development of

antibiotic resistance include gene mutations and the acquisi-

tion of exogenous genetic material, such as plasmids which

contain a variety of resistance genes (Baquero et al., 2013;

Martinez & Rojo, 2011; Rice, 2012). Most genes involved in

antibiotic resistance possess auxiliary functions in bacterial

species. Many antibiotics naturally produced by microbes

Figure 1. Schematic illustrating four centralanthropocentric hubs of the antibiotic-subsisting resistance (not to scale).Commensal, industrial, and waste sites pro-vide an abundant nutritional source forantibiotrophs; the latter eventually find theirway to human communities via farm manuretranslocations, hospital visits, and industrialwaste dumping.

Table 2. Microbial species possessing antibiotic resistant and subsisting abilities.

AntibiotrophicMicroorganisms/family Mechanism of degradation Subsistence characteristics Reference

Streptomyces* MDR efflux pump Tetracycline producer Barnhill et al., 2010;D’Costa et al., 2011

Salmonella enterica* Veterinary associations Barnhill et al., 2010Burkhodelriales N/A Fenitrothion degradation D’Costa et al., 2011Enterobacteriales Inactivation by beta-lactamases Elevated antibiotic resistanceActinomycetales Ribonucleic acid mutations Elevated antibiotic resistanceRhizobiales N/A Elevated antibiotic resistancePseudomonadales N/A Elevated antibiotic resistance Zhongli et al., 2001Sphingobacteriales Inactivation by beta-lactamases Elevated antibiotic resistance Chopra et al., 2003;

D’Costa et al., 2011Sphingosinicella microcystinivorans Microcystin degradation by

HydrolysisElevated antibiotic resistance Chopra et al., 2003

Citrobacter sp. Erythromycin degradation bybeta-lactamases

Antibiotic Inactivation Foster & Woodruff, 2010

*Several orders; N/A: not available

4 Y. Woappi et al. Crit Rev Microbiol, Early Online: 1–14

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have been shown to be involved in microbial survival

pathways (e.g. streptomycin) (Martinez & Rojo, 2011;

Meroueh et al., 2003). Therefore, it can be assumed that in

nature, the function of antibiotics goes beyond inhibiting the

growth of the competing microbial flora, and that many genes

responsible for antibiotic resistance also have metabolic roles

in the survival of the microorganism. In Providencia stuartii,

intrinsic chromosomal acetyltransferases are involved in

aminoglycoside resistance, but their primary role, prior to

the introduction of aminoglycosides in clinics, was to

acetylate peptidoglycan for structural modifications (Barlow

& Hall, 2002; Goldberg et al., 1999). Some of the mechan-

isms underlying the process of antibiotic resistance acquisi-

tion are elaborated below.

Horizontal gene transfer

Horizontal gene transfer (HGT) is the process by which genes

from one species of organism are transferred to another

species. In bacteria, HGT mostly occurs with genes located on

plasmids. Transformation (acquisition of exogenous DNA

often located in the environment), conjugation (acquisition of

DNA directly from another bacteria), and bacteriophage

transduction (acquisition of DNA via viral infection) are

major modes of HGT. It has been widely accepted that

plasmids can harbor a vast variety of antibiotic resistance

genes. Modern biotechnology and refined therapeutics for

blocking HGT can allow us to halt the spread of antibiotic

resistance genes such as R plasmids, which have been known

to include genes for resistance to chloramphenicol, tetracyc-

line, aminoglycosides, and sulfonamides as well as other

classes of antibiotics (Hammami et al., 2009; Islam et al.,

2012). The R plasmids, originally found in organisms that

produced antibiotics, have found ways to naturally transform

pathogenic bacteria (Kopmann et al., 2013).

In plasmids, the resistant genes are components of

transposons, which are able to insert themselves in the

middle of any DNA sequence (Liebert et al., 1999). It has

been reported that a plasmid-mediated quinolone resistance

gene, qnrA1, was present on a mobile plasmid and was able to

spread to other species of bacteria that were under the

selective pressure of fluoroquinolones and b-lactam anti-

biotics (Chowdhury et al., 2011). Cantas et al. (2012)

confirmed that in Aeromonas hydrophila, the R-plasmid

pRAS1 carrying resistance genes TcR, TmR, and SuR was

transferred to other species of bacteria by conjugative transfer.

In E. coli, the IncF plasmids, carrying the blaCTX-M-14 gene

responsible for ceftazidime and defotaxime resistance, are

known to spread via HGT (Kim et al., 2011). Several other

plasmid-encoded genes, such as b-lactamases, are known to

have been acquired by pathogenic bacteria via HGT (Meroueh

et al., 2003). It has been suggested that the frequency of

conjugative transfer of resistance genes in nature is several

magnitudes higher than under laboratory conditions (Tenover,

2006). In addition to conjugative transfer, in Streptococci,

Meningococci, and related genera, the exchange of genetic

material occurs mainly via transformation (Springman et al.,

2009). In Acinetobacter sp. ADP1, it was shown that the strain

was exceptionally capable of acquiring DNA from its

environment (Barbe et al., 2004).

MDR efflux pumps

The evolution of MDR efflux pumps in the development of

pathogenic antibiotic resistance has raised concerns (Poole,

2005). MDR efflux pumps are a common way that microbes

expel physiological substrates, non-antibiotic substrates, and

antibiotics outside the cell (Brown et al., 1999; Liang et al.,

1995). Five different protein-based efflux pumps have been

identified: (i) the multidrug and toxic compound extrusion

(MATE) (Brown et al., 1999), (ii) the adenosine triphosphate

(ATP) binding cassette (ABC) (Springman et al., 2009), (iii)

the small multidrug resistance (Paulsen et al., 1996), (iv) the

major facilitator superfamily (Marger & Saier, 1993), and (v)

the resistance nodulation cell division (Saier et al., 1994).

It has been thought that MDR efflux pumps originally evolved

in antibiotic-producing microbes to exocytose the antibiotics

from their cytoplasm as well also evade other naturally

produced toxic molecules, thereby allowing the microbe to

survive in its ecological niche (Brown et al., 1999; Rahmati

et al., 2002). Helling et al. (2002) reported that the natural

function of efflux pumps in E. coli was to remove metabolic

products and toxins and to buffer the organism against surges

in pools of potentially toxic metabolites. In addition, there

have been studies confirming the role of efflux pumps in cell-

to-cell signaling, such as quorum sensing (Rahmati et al.,

2002). The HGT of MDR efflux pumps is now being thought

of as an important mechanism by which many pathogenic

bacteria have become resistant to a wide range of antibiotics.

It is believed that MDR efflux pumps have auxiliary

physiological roles including the expelling of toxic endogen-

ous metabolites as well as exogenous chemicals. The

observation that most MDR efflux pumps are chromosomally

encoded indicates that they did not appear due to the

widespread use of antibiotics (Nikaido, 2009). This is

exemplified by the acrB gene of E. coli, which is used for

protection against bile salts and other detergents abundant in

the E. coli microenvironment (i.e. the intestinal tracts of

vertebrates) (Zeibell et al., 2007). In P. aeruginosa, which

lives mainly in the soil, the MDR efflux pumps are involved

in pumping toxic compounds produced by other soil micro-

organisms (Kang & Gross, 2005). These pumps have also

been reported to secrete secondary metabolites produced by

plants, as well as toxic metals such as Co2+, Ni2+, Cd2+, and

Zn2+ (Goldberg et al., 1999).

Effects of mutations

Overall, antibiotic resistance in bacteria is influenced by the

colony’s physiological status. It is believed that the first few

cells that start a colony ultimately determine the final status of

the colony at the end, as all cells within a colony are clones of

each other. Similarly, if a population of bacteria is exposed to

antibiotics and a few survive, their genome will ultimately

determine the characteristics of the future colonies they

generate. In such instances, when a bacterial population is

exposed to antibiotics, a population is always left behind.

This strategy used by most bacterial populations is now

thought to be a way by which bacterial populations generate

strains able to survive extreme changes in their environment

(Dhar & McKinney, 2007). This phenomenon, termed the

founder effect, is thought to give rise to antibiotic-resistant

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populations of bacteria when they are exposed to antibiotics

produced by naturally occurring bacteria. This effect is

different from what is known as persistence, in which cells

may survive the first treatment of antibiotics, but are still

sensitive to the antibiotic and will be killed with a second

treatment (Kumarasamy et al., 2010). The founder effect,

on the other hand, has been linked to the ability of microbes

to go through gain-of-function mutations (hypermutator

phenotype) and acquired resistance.

Many bacterial species possess a special phenotype

termed the hypermutator phenotype, which allows bacteria

to quickly adapt by mutating their genomes, allowing them

to survive in a quickly changing environment. Kenna et al.

(2007) reported that P. aeruginosa contained a mutS gene

that allowed it to swiftly adapt to antibiotic treatments in

cystic fibrosis (CF) patients. In addition to P. aeruginosa,

isolates of H. influenza and S. aureus from CF patients have

a high proportion of mutators. Small colony variants of

S. aureus have been isolated from a variety of drug-resistant

chronic infections including CF (Besier et al., 2007).

A thymidine-dependent SCV isolated from CF patients has

been shown to be a hypermutator and antibiotic-resistant

(Besier et al., 2008).

The majority of naturally occurring mutants have defects in

the methyl-directed mismatch repair (MMS) system proteins

(Oliver et al., 2004). Several other genes encoding beta-clamp

proteins, mutH, mutL, and mutU, have also been studied

(Chopra et al., 2003). In Bacillus anthracis, the knockouts of

mutY and mutM combination resulted in high mutation rates,

but mutY and mutM single knockouts were weak mutants

(Zeibell et al., 2007). In addition to mut genes, the DNA

adenine methyltransferase (Dam) genes play a role in repair

mechanisms (Nikaido, 2009). Organisms lacking Dam are

hypersensitive to DNA-damaging agents and reactive oxygen

species (Zaleski and Piekarowicz 2004), while organisms with

this hypermutator phenotype can acquire antibiotic resistance

if faced with stresses such as high antibiotic levels.

Risks of an antibiotic-subsisting resistance

The unsettling concept of antibiotic subsistence subsequent to

antibiotic resistance has been examined by several groups

(Barnhill et al., 2010; Lee et al., 2008; Walsh et al., 2013;

Xin et al., 2012). As explained above, the acquisition of

resistance is a natural phenomenon that can serve to maintain

balance within the microbiome. The problem, however,

presents itself when the resistance is acquired by strains

whose pathogenicity affects humans or animals and crops

closely associated with humans. Furthermore, contemporary

classifications fail to properly categorize resistant strains, and

often encompass ‘‘intrinsic’’ MDR strains and ‘‘acquired’’

MDR strains alike, even though a strong genomic distinction

distinguishes the two (Magiorakos et al., 2012). This leads to

a distorted theoretical approach, since hypermutator charac-

teristics often alter therapeutic targets (Chopra et al., 2003,

Lee et al., 2008). We must be aware that ‘‘intrinsic’’ MDR

strains are principally resistant gene propagators within the

microbiome (i.e. the totality of microbes), as they generally

represent antibiotic-resistant populations present prior the

introduction of antimicrobials in clinics (Allen et al., 2010).

‘‘Acquired’’ MDR strains, however, are usually derived

moieties whose resistant abilities were obtained through

HGT, this includes a series of pathogenic strains possessing a

cutting-edge antibiotic-resistant profile (Thomson & Amyes,

1992; Wright, 2005).

Antibiotrophs are likely the result of perpetual gene

interchange, and typical methodologies for antibiotic resist-

ance inhibition may prove particularly inefficient against this

subset of resistant microbes. This is made evident by the

concept of ‘‘co-resistance’’ as described by Canton et al.

(2011), and by the realization that certain bacteria not only

resist antibiotics they are exposed to, but can also derive an

advantage from that environment (Canton & Morosini, 2011).

It is expected that future findings will reveal several TDR

strains as antibiotrophs.

One promising discovery is the identification of peptides

with metabolic-hindering properties (Rajgarhia & Strohl,

1997). This is unexpectedly the case for tetracycline, whose

polyketide origins have revealed anti-catabolic properties

against nearly 600 antibiotic-subsisting isolates (Barnhill

et al., 2010). Although one of the earliest antibiotics

introduced in clinic, tetracycline was one of the latest

antibiotics to have a clinical case of resistance reported

against it. In contrast, recent findings analyzing the evolution

of antibiotic resistance have demonstrated drastically

increased rates of vancomycin, nalidixic acid, and strepto-

mycin resistance (Arias & Murray, 2012; Robicsek et al.,

2005). An inventory of antibiotics commonly metabolized

and subsisted on by antibiotrophic strains is summarized

in Table 3.

Secondary metabolites’ influence on exaptation also plays

a central role in the localization of microbial niches, as the

effects of cell-to-cell signaling through quorum sensing can

enable natural microbial dispersions (Martinez, 2006). Within

the microbiosphere, antibiotics can serve as warning signs,

and can induce biofilm formations in neighboring microbial

populations (Tsui et al., 2011). Such metabolites can also

serve as chemoattractants that appeal to certain antibiotrophs,

concomitantly selecting strains needed in specific micro-

environmental milieus (Romero et al., 2011; Woappi et al.,

2013; Zhang et al., 2011). Hence, human commensals, health/

research centers and agricultural/farm soils, again, are

attractive niches for these microorganisms, as they can readily

gain access to the elevated antibiotic concentrations common

in those environments.

Catabolic conduits

A microbe’s ability to catabolize extreme antibiotic levels

requires its genomic adaptation to stretch beyond the mere

procurement of MDR pumps. Their potential swarming

motility and chemoattractant patterns are revealed by their

appeal toward elevated antibiotic gradients in microfluidic

devices, which also provide insights about their probable

pathogenic mode of action (MOA) (Hawkey & Jones, 2009;

Martinez & Rojo, 2011; Zhang et al., 2011). In actuality,

antibiotrophs may necessitate ‘‘intake pumps’’ – modified

efflux pumps driven by mechanisms analogous to the

phosphotransferase system (PTS), but used to ingest extra-

cellular antibiotics – while possessing expulsive efflux pumps

6 Y. Woappi et al. Crit Rev Microbiol, Early Online: 1–14

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only for antibiotics they cannot metabolize, or for concentra-

tions surpassing their intake threshold (Figure 2). For this

reason, proton motive force protein such as secF, seen in the

potentially prominent antibiotroph order Burkholderiales, in

concert with antibiotic-metabolizing genes may be red flags

for antibiotrophism (Chopra et al., 2003; Hawkey & Jones,

2009). Furthermore, molecular and genomic elements

involved in the regulation of carbon and nitrogen utilization

should be investigated (Martinez & Rojo, 2011; Qu & Spain,

2011).

Antibiotic production versus antibiotrophism

The origins of microbial antibiotic production stemmed from

the diversification of prehistoric biomes. Antibiotic resistance

arose afterwards as a self-protective mechanism against

Figure 2. Hypothetical antibiotic-metaboliz-ing pathway of ciprofloxacin, a second-generation fluoroquinolone frequentlydegraded by antibiotrophs. Subsistence onantibiotics is enabled by phosphatases andhydrolases capable of efficient antibioticdeactivation and degradation inter and intra-cellularly; degraded antibiotics are consumedas carbon source and excess contents areexpelled via MDR efflux pumps.

Table 3. Antibiotic inventory frequently subsisted on by antibiotrophs.

Most-often degraded (High MIC) Reference Often degraded (Low MIC) Reference

Erythromycin (120 mg/ml) Frank-Petersise et al., 2011 Rifampin (40 mg/l) Foster & Woodruff, 2010;Singh & Walker, 2006

Ampicilin (41 mg/ml) Barnhill et al., 2010 Tetracylcline (51 mg/ml) Barnhill et al., 2010Clavulanic acid (41 mg/ml) Cefepime (51 mg/ml)Sulfisoxazole (41 mg/ml) Florfenicol (51 mg/ml)Trimethoprimb (41 g/ml) Amikacin (51 mg/ml)Kanamycin (1 g/l) Dantas et al., 2008; Barnhill et al., 2010 Ceftiofur (51 mg/ml)Vancomycin (1 g/l) Levofloxacin (1 g/l) Aminov & Mackie, 2007Penicillin G (1 g/l) Dantas et al., 2008 Sulfisoxazole (1 g/l)Ciprofloxacinb (1 g/l) Sulfamethizole (1 g/l)Mafenide (1 g/l) Clindamycin (20 mg/ml)Trimethoprim (1 g/l) Novobiocin (20 mg/ml) Chowdhury et al., 2011Carbenicillin (1 g/l)Chloramphenicol (1 g/l)Sisomicin (1 g/l)Amikacin (1 g/l)Daptomycin (1 g/l) Chowdhury et al., 2011Rifampicin (1 g/l)Trimethoprimb (51mg/ml)Vancomycin (51mg/ml)

b¼ cited both as highly degraded and as least degraded; NA¼Not Available.

DOI: 10.3109/1040841X.2013.875982 Antibiotrophs: The complexity of antibiotic-subsisting 7

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microbes’ own metabolites, and as a superficial protective

mechanism against extraneous environmental toxins (Davies

& Davies, 2010; Tenover, 2006; Wright, 2005). The presence

of resistant genes was mostly trivial in antibiotic-producing

microbes. Over time, however, the antibiotic resistance

genome has acquired elements that often enable it to confer

virulence (Baquero et al., 2013; Martinez, 2012). It has been

found that MDR efflux pumps, for instance, originated in

microbes that produced antibiotics and parvomes (Allen et al.,

2010; Dhar & McKinney, 2007). Streptomyces rimosus, a

tetracycline producer, possesses MDR efflux pumps, which it

uses to expel antibiotics (Petkovic et al., 2006). More recently,

the coexistence of antibiotic production and resistance

functions has been confirmed by studying the gene nexus

within antibiotic-producing cassettes (D’Costa et al., 2011;

Islam et al., 2012; Nikaido, 2009). This presents a pertinent

concern, as it reveals some of the antibiotic-producing

microbiota to be part of the antibiotrophic strains, with

virulence transmissibility and pathogenicity competence

(Gabani et al., 2012; Gillings, 2013; Palmer & Keller, 2010;

Singh & Walker, 2006; Torres-Cortes et al., 2011).

The implications of antibiotic production and antibiotic

subsistence raise some interesting questions. Could certain

antibiotrophic strains be self-sufficient under stressful condi-

tions by producing antibiotics they can also digest? Are

antibiotrophs catabolically restricted to exogenous metabol-

ites? Genomic mining and metabolic mapping can provide an

enormous amount of information relevant to such queries.

Furthermore, traditional molecular cloning approaches

through the insertion of specific resistant cassettes upstream

from a macrolide promoter may provide a swift method of

determining minimal genomic requirements and mechanisms

underpinning antibiotic production, molecule transportation,

and subsistence acquisition in several resistant strains

(Bergstrom et al., 2004; Chowdhury et al., 2011;

Kumarasamy et al., 2010; Torres-Cortes et al., 2011).

Therefore, in addition to catabolic patterns, the use of

molecular determinants is necessary to accurately describe

subsistence in bacteria. Studies analyzing catabolic behaviors

in resistant strains, for instance, have shed light on the scarcity

of truly, solely, antibiotic-subsisting bacteria (Walsh et al.,

2013), emphasizing the need for genomic and systems biology

in characterizing subsistence.

Bioinformatics of antibiotic resistance

Global in silico approaches, precise transcriptomics (i.e.

global study of mRNA/transcripts) and advanced metage-

nomic systems (i.e. global gene profiles of uncultivable

bacteria) can now enable us to identify members of the

antibiotroph subset based on specific molecular profiles.

Consequently, instead of looking for the mere ability to

subsist in carbon-free environments under elevated antibiotic

concentrations, we can mark specific genomic elements as

strong indicators of antibiotrophism. By doing so, it is

possible to establish solid foresight strategies and to accur-

ately anticipate possible expansions and transmutations within

the microbial resistome (i.e. antibiotic resistance genes).

The identification of the SG11 integron and secF gene

in several antibiotic-subsisting isolates, for instance, has

enabled microbiologists to tag commonly recognized gene

clusters as probable antibiotic-catabolizing elements

(Barnhill et al., 2010; Kopmann et al., 2013; Tsui et al.,

2011). Another example is L-tryptophan, whose degradation

in antibiotic-producing microbes unleashes its indole func-

tional group and subsequently confers antibiotic resistance

(Lee & Collins, 2012). Such mechanisms reinforce the

pleiotropic characteristics of subsistence and indicate a

potential presence of auxiliary antibiotic-subsisting genes

camouflaged within ordinary antibiotic-resistant clusters

(Canton & Ruiz-Garbajosam, 2011).

Furthermore, comparative proteomic (i.e. global study of

proteins) analysis could help reveal the MOA of several

antibiotrophic strains. The application of PM47 treatment, as

demonstrated by Wenzel & Bandow (2011), has shown

distinctive proteomics markers underlining antibiotic-resistant

MOA in several species. Another comparative proteomic

study reveals bacteria resistant to different antibiotic drugs

with distinct mechanisms of action, along with an overview of

the proteins possibly related to the resistance process (Lima

et al., 2013). Analogous gene-specific approaches would

provide an extremely dynamic scaffold for antibiotrophic

genomic mining, which could enable us to determine whether

genes, in synergy with antibiotic-inducing elements such as

S12 ribosomal proteins, are concrete indicators of subsist-

ence. These uncharacteristic arrangements can readily be

assessed through pyrosequencing if performed with primers

hypersensitive to subsisting genes (Table 4).

Proteogenomic expression profiles are increasingly

important in the search for functional biomolecules (i.e.

metabolites) that may have potential uses in eliminating

antibiotic resistance. The vast amount of data produced from

genome and proteome data sets needs to be analyzed, and one

must understand the analytical platforms that have been used

to obtain the data and the statistical principles. The current

infrastructure of bioinformatics allows the generation, storing,

analysis, and interpretation of these data sets. In general, data

interpretations of antimicrobial drugs in terms of genomics

and proteomics have been rendered through three major

bioinformatics approaches: (i) mathematical modeling (i.e.

data mining, statistical analysis, genetic algorithms, and graph

matching); (ii) computation search alignment techniques (i.e.

comparing new proteomes and metabolomes against the set

of known proteins and metabolites); and (iii) a combination

of critical mathematical modeling and search techniques.

Among the search tools, there are a number of databases

of antibiotic peptides treating microbial infections

(e.g. ANTIMIC, PhytAMP, APD2 and CAMP) that provide

an overview of antibiotic resistance (Brahmachary et al.,

2004; Chowdhury et al., 2011; Thomas et al., 2010;

Wang et al., 2009).

The antibiotic resistance gene database (ARDB) unifies

most of the publicly available information on antibiotic

resistance (Liu & Pop, 2009). The antimicrobial drug

database (AMDD) provides a comprehensive platform with

the potential to help analyze antimicrobial agents and develop

new candidates to overcome drug resistance (Danishuddin

et al., 2012). Developments in the Internet have allowed

researchers to have immediate access to information in almost

every scientific field. Table 5 summarizes a list of Internet

8 Y. Woappi et al. Crit Rev Microbiol, Early Online: 1–14

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resources that may be useful to practitioners and scientists

with research interests in antimicrobial resistance (adopted

and modified from (Falagas & Karveli, 2006).

Challenges and future perspectives

Our dependence on antibiotics for agriculture and disease

treatment is higher today than it has ever been. Nonetheless,

we concurrently face the challenge of an unprecedented,

evolving microbial resistance. Unlike most microorganisms

and pests, our story is intertwined with that of bacteria.

The symbiotic relationship that exists between humans and

microbes will prevent us from eradicating several microbial

strains, even if hypothetically feasible. Not by virtue of

coincidence, human commensal is a frequent recipient

of pathogenic traits (Marshall & Ochieng, 2009). This is

seen in ESBL-producing E. coli, a pivotal mediator of

resistant gene interchange between environmental micro-

organisms, commensals, and nosocomial pathogens (Kurihara

et al., 2013; Sengupta et al., 2013). The combination of HGT

and gene mutations allows such microbes to quickly generate

advantageous variances and to produce strains with swift

antibiotic resistance propensities.

Although a general consensus on the description of

antibiotic-subsisting microorganisms is provided in this

review, it is important to halt bacterial evolution and develop

a next generation of antibiotics that would quickly eliminate

resistant strains, while subsequently voiding their genomic

content to prevent its acquisition by nearby microbes.

Recently identified antibacterial reagents capable of evicting

antibiotic-resistant plasmids from a cell, such as apramycin,

may prove particularly appealing for this approach (Denap

et al., 2004). In addition, it has been recognized that the mass

production of antibiotics has generated an array of logistic

challenges that have resulted in their overuse and misuse. As

noted by the CDC, the unmonitored dumping and distribution

of ineffective antibiotics in developing nations provides an

enormous nutritional bank for antibiotic-resistant microbes,

and is a major driving factor for the expansion of the pan-

resistant resistome (Okeke et al., 1999). Although inconveni-

ent, an approach averse to modern antibiotics will need to be

introduced within the next decade. Ingenuity and foresight

should be encouraged in the planning of the next therapeutic

models. The use of bacterial repellents, for instance (i.e.

biotoxic and microtoxic inhibitors), may be a better thera-

peutic strategy than the current bactericidal approach. Such

cytotoxin neutralizers can prove particularly effective since

they do not threaten colony viability and hence do not activate

resistance-favorable mutations, ultimately decreasing the

propagation of resistant genes (Baquero et al., 2013;

Williams & Hergenrother, 2008; Williams et al., 2011).

Multiple microbial metabolic mechanisms for drug toler-

ance reveal an ongoing evolution towards extremophiles,

tolerating environments that are otherwise lethal to a normally

occurring bacterium in nature. The limited research on

naturally occurring extremophiles has not allowed us to

fully understand the particularities of their niches. However,

in-depth studies of antibiotic-resistant organisms that fall into

Table 4. Prospective molecular elements conferring subsistence.

Molecular agent(s) Host Mode of action (MOA) Reference

SGI1 integron Salmonella enterica Genomic island carrying resistancegene cassettes

Barnhill et al., 2010

Sul1 Salmonella (*) Gene conferring sulfonamideresistance

L-tryptophan S. aureus Degradation-dependent indole aidsefflux pump functioning

Lee & Collins, 2012

L-arginine Streptococcus sp., Escherichia coli,Klebsiella sp

Ferton reaction suppression andcatalase activation

Zhao-Lai et al., 2012;Lee & Collins, 2012

CTX-Ms Enterobacteriaceae b-lactamase-driven hydrolysis Thomson & Amyes, 19922NI nitrohydrolase Nocardia mesenterica, Pseudomonas

Fluorescens, Streptomyces eurocidicusHydrolytic denitration Qu & Spain, 2011

secF Burkholderiales Protein translocation throughproton motive force

Barnhill, 2010; Kazuya et al., 2011

MlrAMlrBMlrCMlrD

Sphingomonas/Sphingomonadaceae Hydrolysis. MCLR transport Kormas & Lymperopoulou, 2013;Borgia et al., 2012

NDM-1 Enterobacteriaceae Carbapene degradation Borgia et al., 2012CbrA Pseudomonas aeruginosa Sensor kinase driving metabolic

switching in swarmer cellsJin et al., 2002

OPH Pseudomonas sp. Organophosphate degradation Singh & Walker, 2006pehA Burkholderia caryophilli Gene responsible for polygalactur-

onase expressionglp A&B Pseudomonas sp. Invovlved in commensalism

adaptationstet(S) Staphylococcus aureus, Bacillus sp. Gene driving tetracycline-efflux

transporter expression andcatalysis of Na+ and K+

Falagas & Bliziotis, 2007;Lee & Collins, 2012

mphAmphBmphBM

E. coliE. coliS. aureus

Macrolide inactivation Wright, 2005

*Several orders.

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DOI: 10.3109/1040841X.2013.875982 Antibiotrophs: The complexity of antibiotic-subsisting 11

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the extremophile category (i.e. antibiotrophs) would help us

locate thriving properties of many other extremophiles and

resistant bacterial strains. In addition, it would be advanta-

geous for future studies to be consistent with terminologies

such as subsistence, antibiotic-catabolism, antibiotrophism,

and sole-carbon source utilization. This will aid facilitate the

analytical correlation between various subsisting gene acqui-

sition patterns, and will improve surveillance culture

screening.

To fully understand the spectrum of this subsistance-based

resistance, the focus should also be orientated towards

nosocomial environments. The novel antibiotic arsenals and

well-known antibiotics associated with resistant strains could

be administered solely through compact portable drug pumps

(PDP) attached to patients. Studies have suggested, ‘‘anti-

biotic cycling,’’ which involves the periodic replacement of

antibiotics with alternative classes of compounds in an

attempt to reduce the selection pressure for resistance

(Masterton, 2005). However, this does not provide a

long-term solution, since the complete eradication of multi-

drug-resistant strains is practically impossible. An equally

promising and currently used approach is the combinations

of various antibiotics with different modes of action.

One demonstration of this strategy resulted in great success

with clavulanic acid and related compounds in combination

with b-lactam antibiotics (Jariyawat et al., 1999). However,

microbial strains resistant to this mechanism have been found,

and recent studies have reported clavulanic acid as one of the

most readily catabolized antibiotics when screened against

antibiotrophic strains (Barnhill et al., 2010).

As microbiosphere ‘‘cleaning machines’’, the unique

metabolism observed in antibiotrophs also has some valuable

and practical potential. Through gene manipulation, non-

pathogenic antibiotrophs can be engineered for pharmaceut-

ical, agricultural, and clinical uses. Their chemoattractant

patterns could be employed to identify hotspots of antibiotic

outflow, while their genomic profiles could help hone

CRISPR interference and could serve as substrates for the

next generation of molecular cloning applications.

Acknowledgements

The authors thank Institutional assistance for making this

research possible.

Declaration of interest

The authors report no conflicts of interest.

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