Encyclopedia of Metagenomics

Living Edition
| Editors: Karen E. Nelson

Antibiotic Classes and Mechanisms of Resistance

  • Kimberly M. Carlson-Banning
  • Lynn ZechiedrichEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-6418-1_55-1


Antibiotic Resistance Efflux Pump Peptidoglycan Layer Antibiotic Class Trimethoprim Resistance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Definition of Antibiotics

Antibiotics are small molecules that stop bacterial growth or cause bacterial death, depending on concentration.

Synonyms for Antibiotics


Since their discovery, antibiotics have helped millions of people overcome previously lethal bacterial infections, and these drugs are considered among the greatest of medical achievements. Both natural and synthetic antibiotics are used to treat or prevent bacterial infections in humans and domesticated animals. In animal husbandry, antibiotics are also used to promote rapid growth of the animal. Bacteria and fungi produce antibiotics to communicate with each other and to establish themselves in or to survive different ecological niches (Hibbing et al. 2010; Watve et al. 2001).

Antibiotics are small molecule compounds that vary widely in their structures (Fig. 1). The widespread use of these compounds has led to bacteria acquiring and sharing genes that cause resistance to antibiotics (Davies and Davies 2010). Bacteria harboring antibiotic resistance genes are found around the globe, and some bacteria are resistant to all currently prescribed antibiotics (Boucher et al. 2009). Antibiotic research and development is needed to help maintain the efficacy of our current drug supply and identify new ways to treat patients with bacterial infections recalcitrant to current therapies. Whether we overcome the challenges posed by the spread of antibiotic-resistant bacteria remains to be seen, but understanding how antibiotics affect bacteria and how antibiotic resistance mechanisms work is a reasonable place to begin.
Fig. 1

Diversity of antibiotic structures

After reading this review, the reader should have an understanding for the mode of action of the different antibiotic classes, how bacteria resist antibiotics, how bacterial ecology allows for the acquisition of resistance genes, how metagenomics can guide antibiotic drug development and help us understand antibiotic resistance mechanisms, and what considerations are needed to develop new antibiotics and preserve current antibiotic efficacy.

Overview of the Antibiotic Classes

Historically, antibiotics are divided into classes based on the cellular function they inhibit (Fig. 2). These cellular processes (and the antibiotic classes that affect them) include cell wall synthesis (β-lactams, cephalosporins, carbapenems, glycopeptides, and lipopeptides), DNA synthesis (quinolones and fluoroquinolones), RNA synthesis (rifamycins), protein synthesis (aminoglycosides, chloramphenicols, tetracyclines, macrolides, pleuromutilins), and tetrahydrofolate synthesis (sulfonamides and trimethoprim).
Fig. 2

Schematic of major cellular processes inhibited by antibiotics

Processes inhibited by antibiotics include cell wall synthesis, DNA synthesis, RNA synthesis, protein synthesis, and tetrahydrofolate synthesis. Classes that only inhibit gram-positive classes are indicated. *Only gram-negative bacteria have an outer membrane.

This list is oversimplified but serves the purpose of this review. Reviews on drug action and drug resistance mechanisms are listed in Table 1. The antibiotics discussed below were chosen because they represent the major drug classes prescribed globally (Table 1). Our aim is to acquaint readers with the general mechanism and major cellular target for each antibiotic class as a background for thinking about how metagenomic methods can advance the field.
Table 1

Antibiotics and their molecular targets

Cellular process affected

Antibiotic class

Primary molecular target

Recommended review

Cell wall synthesis



Wilke et al. 2005



Wilke et al. 2005



Wilke et al. 2005


Peptidoglycan terminus

Méndez-Álvarez et al. 2000


Cell membrane

Beiras-Fernandez et al. 2010

DNA synthesis


DNA gyrase and topoisomerase IV

Drlica et al. 2009


DNA gyrase and topoisomerase IV

Drlica et al. 2009

RNA synthesis


RNA polymerase β subunit

Aristoff et al. 2010

Protein synthesis


16S rRNA associated with 30S ribosome subunit

Ramirez and Tolmasky 2010


30S ribosome subunit

Nelson and Levy 2011


23S rRNA associated with 50S ribosome subunit

Bozdogan and Appelbaum 2004


23S rRNA associated with 50S ribosome subunit

Schlünzen et al. 2001


50S ribosome subunit

Schlünzen et al. 2001


50S ribosome subunit

Novak 2011

Tetrahydrofolate synthesis


Dihydropeteroate synthase

Sköld 2001


Dihydrofolate reductase

Sköld 2001

General Dissemination of Antibiotic Resistance

Bacteria constantly acquire DNA, and thus they can acquire antibiotic resistance-encoding sequences from surrounding organisms. The transfer of DNA occurs when free DNA, plasmids, transposons, or viruses enter bacteria (Alekshun and Levy 2007; Davies and Davies 2010). These mechanisms can transfer antibiotic resistance from nonpathogenic to pathogenic bacterial species (Davies and Davies 2010). It should be noted that not all bacteria tolerate DNA transfer, but the species that do, such as Bacillus, Pseudomonas, and Acinetobacter, are usually resistant to multiple antibiotic classes (Alekshun and Levy 2007; Boucher et al. 2009). The transferred foreign DNA may be maintained on a plasmid or may integrate into the chromosome. Many resistance genes are encoded on plasmids, termed R plasmids, which are rarely lost and are very stable (Alekshun and Levy 2007; Davies and Davies 2010). Some plasmids encode toxin-antitoxin systems that hold bacteria hostage by killing cells that lose the plasmids (Alekshun and Levy 2007). Below we discuss the essential bacterial pathways that antibiotics inhibit and how bacteria counter the effects of these drugs.

Cell Wall Synthesis Inhibitors and Resistance Mechanisms

β-Lactams, Cephalosporins, Carbapenems, Glycopeptides, and Lipopeptides

Cell wall structures differentiate gram-positive from gram-negative bacteria and provide bacteria structural integrity, allow them to adhere to surfaces, and communicate with other organisms in their ecological niche (Hibbing et al. 2010; Wilke et al. 2005). Gram-positive bacteria have a single cell membrane coated with a thick peptidoglycan layer decorated by lipoteichoic acid (Fig. 2). Gram-negative bacteria have a peptidoglycan layer nestled between two cell membranes, the inner membrane and the outer membrane, which has attached lipopolysaccharides. The additional cell membrane in gram-negative bacteria creates another physical barrier to small molecules and that is why developing antibiotics effective against them is challenging (Fischbach and Walsh 2009; Kohanski et al. 2010).

The peptidoglycan layer is a major antibiotic target. It is synthesized by linking peptidoglycan chains together using transpeptidases, also known as penicillin-binding proteins. While the overall peptidoglycan structure differs among different bacterial species, they all share a terminal d-alanyl-d-alanine group that the transpeptidases recognize (Wilke et al. 2005). β-Lactams are chemically similar to this d-alanyl-d-alanine group and bind well to transpeptidases. Once β-lactams bind to the active site of the transpeptidases, the enzyme is blocked from executing further peptidoglycan linkages. If enough transpeptidases are inhibited, the bacteria fail to maintain their cell wall and will then begin to degrade the peptidoglycan using hydrolases (Kohanski et al. 2010). With a weak peptidoglycan layer, the structural integrity of the bacteria is compromised; cell lysis and death occur from the inability to withstand common shifts in osmolarity (Wilke et al. 2005).

Resistance to β-lactams occurs when bacteria acquire plasmids encoding any of a diverse group of enzymes called β-lactamases. The genes can remain on the plasmid or can become incorporated into the bacterial genome. Synthesized β-lactamases are either bound to the cytoplasmic membrane or secreted into the periplasmic space in gram-negative bacteria or outside of the cell in gram-positive bacteria. β-Lactamases cleave the antibiotic β-lactam ring, making it ineffective. Inhibitors of β-lactamases, like clavulanic acid, are often used in combination with β-lactams but do not have antibiotic properties when used alone. Based on the structure of the β-lactams, scientists created cephalosporins and carbapenems. However, extended spectrum β-lactamases (ESBLs) that cleave cephalosporins and carbapenemases that cleave carbapenems confer resistance, and bacteria harboring these enzymes are found around the globe (Boucher et al. 2009; Wilke et al. 2005). Resistance to β-lactams and cephalosporins is also conferred in gram-negative bacteria by overexpression of efflux pumps such as the Escherichia coli AcrA-AcrB-TolC pump or the Pseudomonas aeruginosa MexA-MexB-OprM pump (Wilke et al. 2005). These pumps promote multidrug resistance by also affecting other antibiotics like the fluoroquinolones, macrolides, chloramphenicol, tetracyclines, oxazolidinones, and rifamycin (Nikaido 2009).

Glycopeptides are effective against many gram-positive bacteria but are unable to cross the outer membranes of gram-negative bacteria. This antibiotic class binds to the terminal d-alanyl-d-alanine peptidoglycan chain and blocks transpeptidases from recognizing and accessing their substrate. Bacteria can circumvent death from glycopeptides by changing the d-alanyl-d-alanine to a d-alanyl-d-serine or d-alanyl-d-lactic acid. Although glycopeptides still bind these substrates, the binding affinities are greatly reduced (Méndez-Álvarez et al. 2000).

Lipopeptides are a new class of antibiotics that target gram-positive bacterial membranes. Although aspects of their exact mechanism remain unclear, it is generally thought that lipopeptides, e.g., daptomycin, irreversibly insert into the bacterial membrane. Oligomerization of lipopeptides creates pores in the membrane, disrupting bacterial homeostasis by leaking out the cellular contents (Beiras-Fernandez et al. 2010). Resistance to lipopeptides has been reported, but the resistance mechanism is unknown (Fischbach and Walsh 2009).

DNA Synthesis Inhibitors and Resistance Mechanisms

Quinolones and Fluoroquinolones

Growing bacteria need to replicate and segregate their genetic material. They achieve these functions using a multitude of enzymes, two of which are the essential topoisomerases, DNA gyrase and topoisomerase IV. DNA gyrase, a tetramer of two GyrA and two GyrB subunits, underwinds DNA to allow replication initiation and prevents overwinding in front of polymerases to allow them to progress. Topoisomerase IV, also a tetramer, of two ParC and two ParE subunits, unlinks the replicated DNA to allow segregation and may also help relax overwinding in front of advancing polymerases. DNA gyrase and topoisomerase IV both cleave double-stranded DNA, pass double-stranded DNA through the break, and religate the break. Quinolones and fluoroquinolones stabilize the cleavage intermediate, which results in arrest of cell growth and cell death (Drlica et al. 2009). Hydroxyl radicals also accumulate upon quinolone or fluoroquinolone treatment, and removal of the enzymes that metabolize toxic reactive oxygen species increases drug lethality (Drlica et al. 2009; Kohanski et al. 2007). Both protein synthesis and aerobic conditions are required for first-generation quinolones to be effective. Later generations of fluoroquinolones are effective without these requirements, but can require higher drug concentrations to kill the bacteria under oxygen-deprived conditions (Drlica et al. 2009). Although the quinolones and fluoroquinolones block DNA synthesis, this is a by-product of the mechanism.

Fluoroquinolone-resistant bacteria typically harbor one or more mutations in the genes encoding DNA gyrase and topoisomerase IV (Drlica et al. 2009). These mutations appear to occur in a stepwise manner, building drug resistance as they accumulate. Chromosomally encoded efflux pumps are associated with quinolone and fluoroquinolone resistance. Three additional quinolone resistance mechanisms are acquired by bacteria from plasmids. These plasmids can encode qnr genes that produce QnrA, QnrB, and QnrS proteins, which act by reversibly binding DNA gyrase and topoisomerase IV to interfere with drug access to the targets. Aac (6′)-Ib-cr inactivates fluoroquinolones by attaching an acetyl group to the drug; this mechanism resists other antibiotic classes, like the aminoglycosides. The efflux pump, QepA, is also acquired through plasmid transmission (Drlica et al. 2009).

RNA Synthesis Inhibitors and Resistance Mechanisms


RNA polymerase synthesizes RNA, including messenger RNA (mRNA), ribosomal RNA (rRNA), and transfer RNA (tRNA). Bacterial RNA polymerase exists in two forms, the core and the holoenzyme. The core has five protein subunits, α2, β, β′, and ω; the holoenzyme forms when a σ-subunit binds to the core (Aristoff et al. 2010). The core is catalytically slow until the σ-subunit binds to RNA polymerase. The σ-subunit allows RNA polymerase to recognize specific DNA promoter regions. Numerous σ-factors exist that regulate transcription of specific genes for general “housekeeping” or in response to different cell stresses, e.g., heat, acidity, and changes in osmolarity. RNA polymerase synthesizes RNA in three main stages: initiation, elongation, and termination. During initiation, the holoenzyme binds to the DNA promoter and begins synthesizing RNA to form a DNA-RNA hybrid (Aristoff et al. 2010). In the elongation phase, RNA polymerase becomes stable and highly processive once it loses contact with the DNA promoter. Transcription is terminated either when RNA polymerase is physically inhibited by hairpins formed in the nascent RNA or when the transcription termination factor, Rho, promotes dissociation of the transcription complex.

Rifamycin inhibits transcription by inhibiting initiation, but it does not affect elongation or termination. Rifamycin binds tightly to the β-subunit of RNA polymerase, which is encoded by the rpoB gene. Bound rifamycin plugs the groove where RNA is transcribed and physically blocks the growing RNA chain (Aristoff et al. 2010). If rifamycin binds before transcription begins, then only small RNAs of a few nucleotides are made and the unstable RNA polymerase aborts transcription initiation. The binding site for rifamycin is located where RNA polymerase interacts with DNA, and it has been hypothesized that DNA damage observed with rifamycin is a direct consequence of DNA-drug interactions (Kohanski et al. 2010). Mutations in the β-subunit rpoB gene that result in reduced drug affinity readily occur, and attempts are being made to develop rifamycin derivatives that also bind to these resistant mutants (Aristoff et al. 2010). Whereas gram-negative bacteria are susceptible to rifamycin, this drug class is used against gram-positive bacteria and, in particular, against Mycobacterium tuberculosis, the causative agent of tuberculosis (Aristoff et al. 2010).

Protein Synthesis Inhibitors and Resistance Mechanisms

Aminoglycosides, Chloramphenicol, Tetracyclines, Macrolides, and Pleuromutilins

Because so many antibiotics target protein biosynthesis, it is prudent to describe this process in better detail (reviewed in Poehlsgaard and Douthwaite 2005). Making polypeptide chains that fold into functional proteins is essential to cell growth. Functional ribosomes are composed of two subunits, the 30S and 50S subunits, which are composed of rRNAs bound as ribonucleoproteins. Many bacteria have multiple rrs and rrl operons that encode the 16S rRNA and 23S rRNA that bind to the 30S and 50S subunits, respectively. Bacteria can mutate one or more of the rrs and rrl genes to prevent antibiotic association with these rRNAs without having to mutate every gene. Thus, they can use a heterogeneous pool of ribosomes for translation when exposed to antibiotics that inhibit protein synthesis. The 30S subunit is responsible for identifying the ribosomal binding sequence on the mRNA to begin translation and to bind the correct tRNA specified by the genetic code. The 50S subunit is responsible for forming the peptide bond between amino acids when synthesizing the growing polypeptide chain (Fig. 2).

Just as RNA polymerase synthesizes RNA, ribosomes also translate mRNA in three phases: initiation, elongation, and termination. Initiation occurs when the mRNA is sandwiched between the 30S and 50S subunits, which are already bound to other initiation accessory proteins. Both the 30S and the 50S subunits have three important sites where tRNAs interact with the ribosome: the aminoacyl acceptor site (A site), the peptidyl binding site (P site), and the exit site (E site). The P site is located between the A and E sites. Once the initiation complex is formed, an N-formylmethionyl-tRNA is bound to the ribosomal P site and polypeptide synthesis can begin. Next, elongation factor Tu delivers a charged amino-tRNA to the vacant A site. The A site also confirms the fidelity of the bound tRNA. When both the P and A sites in the ribosome are occupied by the correct charged amino-tRNAs, the P site tRNA transfers its amino acid to the A site tRNA and creates a peptide bond between the two amino acids. The now uncharged tRNA in the P site leaves that site and enters the E site, thus making room for the peptidyl-tRNA in the A site to translocate to the newly emptied P site. The now vacated A site is then ready to accept another amino-tRNA to begin the process again. Translation is terminated at stop codons using release factors that dislodge the ribosome from the mRNA and release the new polypeptide chain.

The numerous steps involved in protein biosynthesis allow for many ways to inhibit this process and introduce fidelity errors in protein synthesis that result in bacterial death; however, a few rrs and rrl genes easily mutate to escape antibiotic-mediated inhibition (Poehlsgaard and Douthwaite 2005). Aminoglycosides and tetracyclines affect functions of the 30S subunit. Before aminoglycosides bind their ribosome target, they must be actively taken up by cells that have a functional electron transport chain. Thus, anaerobes are not susceptible to these antibiotics (Ramirez and Tolmasky 2010). Additionally, because of a synergistic effect, aminoglycosides are often administered with other antibiotics, e.g., β-lactams, most likely because membrane damage from β-lactams increases permeability to aminoglycosides (Ramirez and Tolmasky 2010). Aminoglycosides bind to various α-helices of the 16S rRNA associated with the 30S subunit to induce conformational changes in the A site of the ribosome that eliminate the proofreading capabilities of the ribosome to remove erroneous tRNAs (Kohanski et al. 2010). Misreading the mRNA can introduce early termination codons that result in formation of truncated proteins. Some aminoglycosides, e.g., spectinomycin, can inhibit elongation by interfering with the stability of peptidyl-tRNA when bound to the A site. Bacteria use a plethora of aminoglycoside-modifying enzymes, including acetyltransferases, nucleotidyltransferases, and phosphotransferases, that are both chromosomally encoded and plasmid encoded. All of these modifying enzymes reduce the net positive charge of the antibiotics, rendering them unable to bind the 30S subunit (Ramirez and Tolmasky 2010).

Tetracyclines block access of aminoacyl-tRNAs to the ribosome by reversibly binding to the A site. In gram-positive bacteria, tetracycline resistance is predominately mediated by plasmids with tetM and/or tetS genes that encode proteins that bind to ribosomes to induce conformational changes that prevent tetracycline binding or subsequent dissociation from the ribosome (Nelson and Levy 2011). A primary tetracycline resistance mechanism in gram-negative bacteria is tetracycline efflux. Ribosomal protection proteins and efflux-mediated tetracycline resistance are found in both gram-negative and gram-positive bacteria. Tigecycline, the most recent tetracycline derivative released to the market and the only member of the new glycylcyclines antibiotic class, was designed to avoid interaction with the tetracycline efflux pump while maintaining the ability to inhibit ribosomal function (Nelson and Levy 2011). Tigecycline use in the clinic is promising, although it does have some toxicity issues and resistance has been found in Acinetobacter species (Boucher et al. 2009).

Oxazolidinones, chloramphenicol, and macrolides inhibit the 50S subunit. Oxazolidinones inhibit translation initiation by binding to the 23S rRNA of the 50S subunit before it can complex with the mRNA-associated 30S subunit. It has been suggested that oxazolidinones block N-formylmethionyl-tRNA from binding the P site to begin protein biosynthesis. If the 70S ribosome has already formed, oxazolidinone binding inhibits the translocation of the growing peptide chain from the A site to the P site. Point mutations in the rrl gene have been correlated with oxazolidinone resistance, and mutations in multiple rrl genes in gram-positive bacteria increase resistance in a clinically relevant manner (Bozdogan and Appelbaum 2004).

Chloramphenicol and macrolides prevent peptide chain elongation. Chloramphenicol reversibly binds to domain V of the 23S rRNA and inhibits aminoacyl-tRNAs from binding to the A site. In addition to drug efflux, chloramphenicol resistance is conferred predominately by chloramphenicol acetyltransferases also known as CATs. CATs attach an acetyl group to the antibiotic, which prevents chloramphenicol from binding to the 50S subunit. Macrolides, such as erythromycin, also reversibly bind to domain V of the 23S rRNA, but they plug the groove where the new polypeptide chain normally extends. Macrolide resistance is mediated by methylation of an adenine residue of the 23S rRNA by the action of Erm methyltransferases, which block macrolide binding to the ribosome. A macrolide efflux pump, encoded by the mef genes, extrudes macrolides that are 14- and 15-membered lactone rings to cause resistance. In addition, mutations in the 23S rRNA and some 50S subunit proteins also confer macrolide resistance (Schlünzen et al. 2001).

The newest antibiotic class, the pleuromutilins, inhibits the 50S subunit by binding to domain V of the 23S rRNA. Pleuromutilins interrupt tRNA binding at both the P and A sites, and they inhibit fMet-tRNA binding for translation initiation (Novak 2011). Pleuromutilins are effective against both gram-negative and gram-positive bacteria. These drugs are currently used as a topical therapy, and clinical trials for systemic use are underway. Mutations in 23S rRNA rrl genes have been observed in clinical isolates. Additionally, VgaA, a likely transporter, was identified in pleuromutilin-resistant bacteria (Fischbach and Walsh 2009). In vitro studies to select for resistant mutants revealed that mutations in the L3 ribosomal protein confer resistance to select pleuromutilins, but these mutations have not yet been found in clinical isolates.

Tetrahydrofolate Synthesis Inhibitors and Resistance Mechanisms

Sulfonamides and Trimethoprim

Bacteria must synthesize folic acid for growth because they cannot acquire it from the environment. Bacteria use many enzymes to synthesize folic acid and then convert it into tetrahydrofolate (THF). THF is a common cofactor used to transfer carbons to other metabolites and is required for the biosynthesis of some nucleotides. Sulfonamides target dihydropteroate synthase (DHPS) and trimethoprim targets dihydrofolate reductase (DHFR). Both sulfonamides and trimethoprim competitively bind to their respective enzyme targets, and mutations in either protein reduce antibiotic affinity. These two antibiotics are often used together to block THF biosynthesis (Sköld 2001). Drug-resistant DHPS genes, sul1 and sul2, account for most clinical sulfonamide resistance, while numerous dfr genes result in trimethoprim resistance. These resistance genes are transferred among bacteria on plasmids and transposable elements. In the case of trimethoprim resistance, mutations in the DHFR promoter that increase gene expression have been reported in the clinic (Sköld 2001).

Additional Bacterial Responses to Antibiotics

Acquisition of plasmids, inactivation of antibiotics, and mutation in genes encoding drug target proteins or rRNA all can be costly in terms of evolutionary fitness, especially if additional energy is required to synthesize new enzymes or other detrimental mutations occur (Andersson and Hughes 2010). Therefore, bacteria often use other tactics to reduce toxic effects caused by exposure to antibiotics without acquiring new genes or mutations (Andersson and Hughes 2010). A major tactic, in the absence of new resistance genes or time to mutate, is to reduce the ability of the drug to find its target (Nikaido 2009). Bacteria can prevent or slow the entry of antibiotics and other environmental toxins by multiple ways: (i) alter membrane permeability, (ii) decrease transport into the cell, (iii) increase transport out of the cell, and (iv) reduce the concentration of proteins that make membrane pores (porins). These also affect other toxic molecules, such as detergents, dyes, heavy metals, and acids (Nikaido 2009).

Antibiotics and Bacterial Ecology

Gene transfer of antibiotic resistance genes among bacteria highlights the importance of identifying the species that coexist in relevant biological niches (Davies and Davies 2010). Antibiotics are not just used by physicians in the clinic. Bacteria themselves use antibiotics to dominate niches or to invade new niches (Hibbing et al. 2010). Antibiotic resistance mechanisms may provide ways for bacteria to ignore signals secreted by neighbors attempting to dominate or invade (Fajardo and Martinez 2008; Yim et al. 2007). The presence of antibiotics can also stimulate bacterial evolution. Sublethal antibiotic concentrations promote fidelity errors in bacterial replication, transcription, and translation (Allen et al. 2009; Fajardo and Martinez 2008). For example, as mentioned above, bactericidal antibiotics induce oxidative stress, which promotes DNA damage (Kohanski et al. 2010). When the cells repair the DNA damage, genetic mutations may arise, potentially affecting gene function or promoter regulation (Allen et al. 2009; Kohanski et al. 2007). In another example, aminoglycosides promote mistranslation, which can result in aberrant proteins that fail to produce necessary metabolites. Therefore, it is important to study bacterial ecology if we are to understand which species produce antibiotics and which species express resistance genes to these antibiotics (Fajardo and Martinez 2008).

Identifying New Antibiotics and Resistance Mechanisms with Metagenomics

Metagenomics offers a way to explore bacterial ecology in greater depth without culturing bacteria. Not all bacteria, including many that are human pathogens, grow under laboratory conditions. Culture-independent strategies are needed to determine which bacteria occupy different niches, including those in eukaryotic hosts, soil, water systems, wastewater treatment plants, and others (Davies and Davies 2010). Identifying how antibiotic resistance genes flow from one environment to another would allow an understanding of how resistance genes flow among pathogenic and nonpathogenic species. In addition, the metabolic pathways needed for the spread of these resistance genes or production of antibiotics may also be uncovered (Schmieder and Edwards 2012).

“Functional metagenomics” and “sequence-based metagenomics” will provide answers to these ecological questions. Functional metagenomics utilizes DNA libraries constructed from environmental DNA (eDNA) cloned into a surrogate host organism, such as E. coli. These libraries can then be screened for antibiotic activity or antibiotic resistance. New long-chain N-acylated amines and isonitrile functionalized indole antibiotics have been discovered using such screens (Banik and Brady 2010). Two major drawbacks to this strategy exist. If the surrogate host lacks the codon preference needed to correctly synthesize the protein leading to antibiotic resistance or if the posttranslational modification systems are inadequate, then important genes might be missed. The other potential drawback is that some antibiotic resistance genes may function only under certain environmental conditions, such as specific temperatures, acidity, or nutritional availability (Banik and Brady 2010).

Sequence-based metagenomics also utilizes DNA extracted from the environment. Typically, the environmental sample is first fractioned by size to separate free DNA from eukaryotic cells, bacteria, and viruses. All free and extracted DNA is pooled to represent all DNA found in the whole community and is then sequenced. While sequence-based metagenomics removes the requirement of cloning into appropriate surrogate hosts, it still relies on having reference genomes and resistance genes for comparison. Luckily, numerous initiatives to sample bacterial environments will continue to improve sequence-based approaches (Schmieder and Edwards 2012).

Using metagenomics to identify new antibiotics or antibiotic resistance mechanisms should help facilitate the development of therapies that specifically eradicate unwanted pathogens without harming beneficial microbial communities (Banik and Brady 2010). Such an approach would stand in stark contrast to the current use of broad-spectrum antibiotics, which leads to dramatic shifts in bacterial populations following therapy (Schmieder and Edwards 2012). Understanding the genes required by bacteria to become virulent, such as the lipopolysaccharide and exopolysaccharide biosynthesis pathways, should allow a tremendous advancement in the quest for improved therapies. Finally, species-specific antibiotics should be reconsidered. For example, a more probing search for such antibiotics could be carried out in natural antibiotic producers, such as the soil-dwelling Actinomycetes (Watve et al. 2001).

Challenges to a metagenomics approach exist. Not only is sampling all niches difficult, but the generation of genome sequence data requires new analysis methods and ways to make the data available to others. To measure significant stability of or shifts in bacterial populations, environmental sampling should be repeated over time and potentially coupled with additional studies (Aminov 2009; Hibbing et al. 2010). For example, how do environmental fluctuations in pH, temperature, oxygen, or pollution impact the microbial community? Which environmental conditions promote production of antibiotics? How do we detect antibiotic production with current chemical detection methods that require higher concentrations? What if the compounds are too unstable for analysis? Continued improvement of these approaches is needed.

Considerations for New Antibiotic Development

To avoid a potential “post-antibiotic era,” we must preserve the existing antibiotic arsenal and develop new antibiotics that are effective against multidrug-resistant bacteria. Achieving these goals requires new, rapid, culture-free methods for diagnosing bacterial infections. In addition to identifying which species are present, these diagnostic measures must also determine which antibiotic resistance mechanisms are present. Implementing these measures will be the most immediate method to curtail the global problem of antibiotic resistance by allowing:
  • Appropriate antibiotic use

  • Species-specific antibiotic use

  • Prevention of biofilm formation

  • Disruption of existing biofilms

  • Prevention of polymicrobial infections

  • Treatment of existing polymicrobial infections

  • Use of appropriate combination therapy

  • Use of probiotics when possible

  • Avoidance of unnecessary broad-spectrum antibiotic use

  • Prevention of spread of antibiotic resistance mechanisms

To continue preserving antibiotics, long-term approaches to reduce the spread of antibiotic resistance will entail basic science research in many areas. Research is needed to better understand bacteria, including how they metabolize substrates, respond to stresses, evolve, become virulent, and inhabit or invade ecological niches (Schmieder and Edwards 2012). Because model organisms may differ in key aspects important for the development of antibiotics and understanding resistance, wild isolates need to be studied and more model organisms need to be established. As more is learned, drugs that affect these processes can be developed. Developing antibiotics that are narrow spectrum do not kill but only block growth, prevent virulence, or are recycled from drugs for other purposes which are all excellent approaches to preserve our current antibiotic supply (Fischbach and Walsh 2009).


In this brief review, we highlighted the major cellular processes targeted by antibiotics and some of the myriad ways bacteria counteract antibiotics. There appear to be far more ways to resist antibiotics than there are antibiotics, and the acquisition of bacterial resistance outpaces our understanding of how resistance occurs. The merging of ideas from ecologists, evolutionary biologists, bioinformaticists, medicinal chemists, biochemists, and other researchers has addressed questions not previously recognized to be relevant for combating bacterial infections. Together, such a multidisciplinary approach can lead to a better understanding of the spread of antibiotic resistance and continued success in treating bacterial infections.



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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Kimberly M. Carlson-Banning
    • 1
  • Lynn Zechiedrich
    • 1
    Email author
  1. 1.Department of Molecular Virology and Microbiology, Verna and Marrs McLean Department of Biochemistry and Molecular Biology, and Department of PharmacologyBaylor College of MedicineHoustonUSA