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Record W2802949894 · doi:10.1093/af/vfy003

Bacterial resistance to antibiotic alternatives: a wolf in sheep’s clothing?1

2018· article· en· W2802949894 on OpenAlexaff
Benjamin P. Willing, Deanna M. Pepin, Camila Schultz Marcolla, Andrew J. Forgie, Natalie E Diether, Benjamin C. T. Bourrie

Bibliographic record

VenueAnimal Frontiers · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAntibiotic resistanceAntibioticsBiologyBacteriocinBacteriaAntimicrobialResistance (ecology)BiotechnologyMicrobiologyGeneticsEcology

Abstract

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Substantial pressure to reduce antibiotic use has necessitated the development of antibiotic alternatives. However, relatively little consideration has been given to the development of resistance to these alternatives. Whether we come up with antibiotic alternatives that are bacteriocidal or inhibitory, bacteria will continue to adapt and evolve. Some antibiotic alternatives support the development of antibiotic resistance necessitating caution. There are opportunities to optimize antibiotic alternative effectiveness as well as to minimize the development of resistance mechanisms. With the growing concern of antibiotic resistance (Aminov and Mackie, 2007; Zaman et al., 2017), there has been a strong push to reduce the use of antibiotics in animal production systems (Van Boeckel et al., 2015; Ventola, 2015). Many antibiotic alternatives have been developed, with varying degrees of success in improving health outcomes and growth performance (Gresse et al., 2017). These alternatives use very different approaches to regulate both commensal and pathogenic bacterial populations. Antibiotic alternatives such as phage and bacteriocins have very clear mechanisms of antimicrobial activity (Figure 1), whereas others, such as essential oils/phytosterols, have less defined modes of action. Irrespective of mode of action, there has been insufficient attention given to the ability of bacteria to develop resistance to these antibiotic alternatives. Considering the development of resistance will be essential in finding long-term solutions. In this review, we present what is known about the ability of bacteria to become resistant to these antibiotic alternatives, and more importantly, identify where they contribute to antibiotic resistance. Prudence is required, as avoiding further contribution to antibiotic resistance is necessary. This review is not exhaustive but is intended to give a good representation from different classes of antibiotic alternatives. In particular, we focus on phage, essential oils, direct-fed microbials and bacteriocins, metals and minerals, and organic acids. Some consideration is given to their application, effectiveness, and modes of action. (A) Phage interact with specific receptors to inject DNA into the bacterial cell, causing viral proliferation and cell lysi (i). Essential oils (EOs) disrupt efflux/influx, membrane receptors and stability (ii). Copper disrupts bacterial lipids, proteins, and DNA through oxidization (iii). Bacteriocins cause cell wall lysis, disrupt the plasma membrane structure (pore formation), and interfere with DNA function (iv). (B) Bacterial resistance to phage is conferred through either blockage/removal of the receptor or cutting of phage DNA in the cell by CRISPR/CAS (i). Bacteria form aggregates to minimize cell surface exposure to EOs, thus preventing membrane associated disruptions (ii). Glutathione chelates Cu+, ATPase efflux system exports Cu+/Cu2+, and siderophores sequester Cu2+ to prevent it entering the cell (iii). Modifications of the cell wall and membrane affect fluidity and charge, impairing bacteriocin binding (iv). Bacteriophages are viruses that can infect and kill bacteria. In the environment, there is a constant arms race between bacteria and phages: as bacteria develop resistance mechanisms, new phages emerge. Bacteriophages are highly specific, which makes them intriguing antibiotic alternatives as they are less likely to affect commensal bacteria. Although, bacteriophages have not yet been widely adopted in animal production systems, they have been shown to be effective in controlling pathogenic bacteria in feed animals. Research has shown potential for phages to control colonization of Campylobacter jejuni (Carrillo et al., 2005), and Salmonella (Borie et al., 2008; Bardina et al., 2012), while decreasing mortality in chickens during Escherichia coli infection (Huff et al., 2002; Huff et al., 2006). Phages have also been effective in reducing Salmonella shedding in pigs (Saez et al., 2011) and reducing shedding of E. coli O157:H7 in sheep (Bach et al., 2009; Raya et al., 2011). However, efforts targeting E. coli O157 in cattle have proven to be less successful (Rozema et al., 2009; Rivas et al., 2010; Stanford et al., 2010). While phages present potential for the control of pathogenic bacteria, there are significant considerations still required regarding their implementation in animal production. As with antibiotics, bacteria are capable of developing resistance to phage infection utilizing systems such as the Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) system as a pseudoimmune system, or the abortive infection system to kill infected cells before the phage can spread (Labrie et al., 2010). Additionally, bacteria can alter their cell surface to remove or block the receptor to which the phage binds (Labrie et al., 2010), which can impact virulence or colonization factors (Cryz et al., 1984). For example, the occurrence of phage-resistant C. jejuni has been noted; however, all isolates exhibited decreased ability to colonize the cecum of broiler chickens (Carrillo et al., 2005). As resistance to multiple phages can be difficult for bacteria to develop, the use of phage cocktails which target different receptors is recommended. This has been shown to result in superior reduction of bacterial cells with fewer incidence of resistant strains and is commonly used in studies examining phage treatment (Huff et al., 2002; Carrillo et al., 2005; Rivas et al., 2010). Another factor to consider in the use of phages is the characteristics of the phages themselves. Phages can be both lytic and lysogenic in nature, with only lytic phages being appropriate for phage treatment. This is due to the fact that lysogenic phages do not always result in lytic infection, leaving some bacteria alive with the phage genome inserted into their own. Additionally, lysogenic phages are capable of contributing to the transfer of antibiotic resistance and virulence genes across bacterial populations (Wagner and Waldor, 2002; Balcazar, 2014). Because of these factors, in addition to utilizing cocktails of phages to prevent the development of resistance, it is important that all phages to be used for treatment or prophylaxis in animal production be thoroughly tested to ensure purely lytic infections can occur with their use. Unlike phage, metals including Copper (Cu2+/Cu+), Zinc (Zn2+), and Silver (Ag+), and nonmetal elements, such as Iodine (I2), have been used in animal production for their broad-spectrum antibacterial activity and low generation of resistance (Aarestrup and Hasman, 2004; Murdoch and Lagan, 2013; Wang et al., 2016). Copper, zinc, and silver disrupt bacterial protein functions, generate reactive oxygen species, and cause damage to bacterial DNA (Rosen, 2002; Xiu et al., 2014). Although iodine’s antimicrobial activity is not well understood, there is indication that it works by reacting with unsaturated fatty acids in the lipid bilayer of the cell wall to cause leaks, as well as inactivating nuclear materials through coagulation (Murdoch and Lagan, 2013). As a result of their broad-spectrum antimicrobial activity, it was believed that generation of bacterial resistance to Cu2+, Zn2+, Ag+, and I2 should be low (Martínez-Abad et al., 2012; Murdoch and Lagan, 2013; Wang et al., 2016). Copper and Zinc salts are commonly added to animal feeds in concentrations above dietary requirements because of their antimicrobial activity, which results in reduced infection and improved animal growth. Similarly, Zinc Oxide added to pig diets has been effective in reducing post-weaning diarrhea (Mazaheri Nezhad Fard et al., 2011; Pieper et al., 2012; Holman and Chénier, 2015; Vahjen et al., 2015). Additionally, copper has been determined to be an effective antimicrobial for udder washes, proving active against a panel of bacteria and yeasts associated with bovine mastitis (Reyes-Jara et al., 2016). The antimicrobial properties of copper and zinc when added to feed have created a selective pressure for bacteria that contain resistance to these heavy metals (Mazaheri Nezhad Fard et al., 2011). High inclusion rates alter the gut microbiome, however, many bacteria have developed resistance, with both zinc- and copper-resistant enterococci identified from the gut microbiome of pigs (Mazaheri Nezhad Fard et al., 2011; Pieper et al., 2012; Vahjen et al., 2015). Bacterial resistance genes to zinc and copper are located on mobile genetic elements, often plasmids, which are transferable between bacteria (Aarestrup and Hasman, 2004; Mazaheri Nezhad Fard et al., 2011; Richard et al., 2017). More importantly, bacteria resistant to copper and zinc have indicated increased resistance to antibiotics, as an increased dose of dietary zinc oxide in weaned pigs increased tetracycline and sulfonamide resistance genes (Mazaheri Nezhad Fard et al., 2011; Vahjen et al., 2015). This increase in resistance is likely due to mechanisms of cross-resistance or coresistance: when microbes use the same resistance mechanism to defend against different antimicrobials such as an efflux pump, or when the genes responsible for resistance are linked closely and are transcribed or transferred together (El Behiry et al., 2012; Vahjen et al., 2015; Reyes-Jara et al., 2016). The genes associated with resistance to copper and zinc have been found on the same plasmids that contain antibiotic resistance genes, and the selective pressure of these metals can result in the sharing of antibiotic resistance among bacteria (Mazaheri Nezhad Fard et al., 2011; Yin et al., 2017), as depicted in Figure 2. The selective pressure of copper results in the uptake of foreign plasmids by enterococci, conferring copper resistance genes as well as antibiotic resistance genes (coresistance). Silver and iodine have been used for many years as antimicrobial agents for wounds and external infections because of their broad-spectrum activity against bacteria and low development of resistance (Martínez-Abad et al., 2012; Murdoch and Lagan, 2013; Kalan et al., 2017). Iodine and silver are active antimicrobial ingredients used in both human and animal wound care products (Burks, 1998; Murdoch and Lagan, 2013; Kalan et al., 2017), and iodine has commonly been used as an udder wash (Tremblay et al., 2014). Extracellular polymeric substances found in biofilms contain functional groups capable of binding metal ions, like silver, and protect against antimicrobial agents such as iodine (Kang et al., 2014; Tremblay et al., 2014; Xiu et al., 2014). Other defenses include mechanisms against oxidative stress, protein/DNA damage repair mechanisms, and metal efflux pumps (Gupta et al., 1999; Tremblay et al., 2014; Xiu et al., 2014). However, studies have shown that silver is capable of penetrating and killing biofilms (Heidari Zare et al., 2017; Kalan et al., 2017; Lemire et al., 2017) and multidrug-resistant pathogens (Kalan et al., 2017). Recent research has indicated that silver resistance is due to the Sil operon that resides on plasmid pMG101 identified in Salmonella enterica serovar Typhimurium, which when transferred to E. coli, conferred silver resistance (Woods et al., 2009; Asiani et al., 2016). Plasmid pMG101 also contains resistance genes to a list of antibiotics, including ampicillin, chloramphenicol, tetracycline, streptomycin, and sulphonamide, suggesting that the transfer of pMG101 between bacteria under the selective pressure of silver may also result in sharing of other antibiotic resistance (Woods et al., 2009). However, incidence of silver resistance remains low (Woods et al., 2009; Kalan et al., 2017) which may indicate that plasmid pMG101 is restricted to particular species or is difficult to transfer or be maintained by other bacteria (Woods et al., 2009). Up until 2013, no known generation of bacterial resistance to iodine had been identified, and studies looking at repeated iodine use over time did not indicate any increase in resistant bacteria (Murdoch and Lagan, 2013). Mastitis-associated bacteria have shown to produce biofilms to survive treatment with low concentrations of iodine (Tremblay et al., 2014). Using sublethal concentrations of nonoxinol-9 iodine complex on Staphylococcus aureus strains specific to mastitis resulted in the development of resistance, although the mechanisms of tolerance are unknown (El Behiry et al., 2012). Although other research has indicated cross-resistance of antibiotics with other biocides (El Behiry et al., 2012), currently there is no known cross-resistance with iodine and antibiotics (El Behiry et al., 2012; Murdoch and Lagan, 2013). Given the challenges with feeding high dose metals, in particular, bacterial resistance and environmental effects of run-off, metal nanoparticles have gained attention as an alternative (Yin et al., 2017). Metal nanoparticles such as silver, copper oxide, and zinc oxide are of particular interest for their antimicrobial properties and suitability as feed additives (Beyth et al., 2015). Technological advances have decreased the cost of synthesizing nanoparticles and made their inclusion in livestock diets more feasible in recent years (Fondevila et al., 2009). The mode of action for antimicrobial metal nanoparticles is not completely elucidated; potential mechanisms include cell membrane disruption, generation of reactive oxygen species, and disruption of protein structure (Beyth et al., 2015). The increased surface area to volume ratio of smaller particles, as well as properties such as shape, can all contribute to an increased bactericidal activity compared to their corresponding metal ions (Gautam and Van Veggel, 2013; Rudramurthy et al., 2016). Zinc oxide nanoparticles have been demonstrated as effective bactericidal agents against antibiotic resistant S. aureus and Staphylococcus epidermidis (Ansari et al., 2012). Silver nanoparticles have also been shown to be effective against bacterial and fungal species, including some important pathogens (Rudramurthy et al., 2016). While in many respects metal nanoparticles may be a promising tool, use of this technology could also generate bacterial resistance. Strain-specific minimum inhibitory concentrations of nanoparticles in E. coli and S. aureus have already been identified, demonstrating that varied resistance to nanoparticle antimicrobial mechanisms exist naturally in the bacterial population (Ruparelia et al., 2008). There is also the risk of accumulation of nanoparticles in livestock tissues particularly if these products are used over long time periods, and the implications for animal health and food safety are not yet completely understood (Fondevila et al., 2009; De Jong et al., 2013; Adeyemi and Faniyan, 2014). Prior to use, it will be necessary to determine if interaction between a specific nanoparticle and biological tissues results in undesired degradation by-products, inflammation, or oxidative stress (Gautam and Van Veggel, 2013; Rudramurthy et al., 2016). Metal nanoparticles may be able to confer similar or improved benefits as antibiotic alternatives in livestock; however, more work needs to be done to fully understand their antimicrobial mechanisms, and impacts on tissues and the environment before they can be readily used in livestock production systems. acids have been used in the food as and for many and more have gained interest as feed additives for livestock et al., 2014). Some organic acids that have been tested include and The mode of action for organic acids into their antibacterial in the and into bacterial decreasing cell et al., a of organic acids to pigs or broiler has been shown to E. coli and increase growth performance et al., 2014; et al., 2014). Similarly, the addition of or in a Salmonella infection decreased Salmonella in at and of and 2015). These effects on pathogens that organic acids could be a promising alternative to however, results are In a different inclusion resulted in no on of broiler chickens compared to a control in et al., is still organic acids can growth performance and animal health across different livestock production or if their is on external In feed the of organic acids required to pathogens on feed and for example, bacteria in may be more resistant In their in on factors such as where low more to and functional et al., may also by acids to the in their form and preventing or before the products their et al., 2014). the to the use of organic acids is their ability to tolerance in bacteria. This tolerance can result in the ability to exposure to as low as et al., bacteria can increase tolerance to more et al., Bacterial species, such as naturally low as well as fatty acids as of their of the and can with these systems et al., This stress can increase in the or in to increased virulence in both Salmonella and pathogenic E. coli et al., tolerance has also been shown to increase shedding of E. coli O157:H7 in and et al., can also bacterial resistance to and which could have implications for food safety and et al., resistance to these other may also to bacterial resistance to other antimicrobial alternatives such as metal ions or further decreasing the of to animal oils from the and of contain complex of known for their and and 2016). The in essential oils can both bacterial and by with cell wall and lipid which in the can to cell et al., 2017). as with antibiotics, is that over time bacteria may adapt and become resistant to the active have the antibacterial activity of essential oils and on both pathogenic and gut commensal bacteria. bacteria are to an of essential oils at concentrations from to et al., 2015). activity was in different essential oils by on pathogenic S. enterica and on the essential oils from had the selective antibacterial activity against pathogenic bacteria with activity on species et al., 2017). Essential oils have been shown to multidrug-resistant bacteria of their antibiotic resistance et al., 2012). properties have also been against multiple strains of from cattle with are to together on C. by and membrane et al., 2017). Similarly, essential oils are to disrupt the cell membrane due to the less such as and found in essential oils et al., 2017). In this the antimicrobial mode of action of essential oils may be specific to or the result of The effectiveness of essential oils against E. coli O157:H7 and S. is on the of active et al., 2017). cause of concern from an of S. enterica infections to The concentrations of S. enterica to develop resistance to active et al., 2013). Bacterial resistance mechanisms essential oils include selective membrane and et al., 2016). although in may have a significant cost on the bacteria in a environment et al., 2017). the use of essential oils and long-term studies are to understand the resistance is a have good potential as an alternative to antibiotics in animal both as growth and as treatment for bacterial infections et al., 2017; et al., 2017). of the active be tested in to determine an effective dose can be Additionally, their may to but for can et al., 2015). new to essential oils with either metals, antibiotics, has gained attention to strains of bacteria and reduce bacterial resistance et al., 2017; et al., 2017; et al., 2017). The of in with other environmental may be a and more effective to growing of bacterial resistance. or have been as alternatives to antimicrobial growth in livestock production. The effectiveness of direct-fed microbials as growth and antimicrobials is highly et al., but such as improving feed and reducing potential pathogens and diarrhea occurrence have been in livestock species et al., 2013; et al., 2015; et al., 2015; et al., 2015). The strains for use as be for the of antimicrobial resistance genes that could be transferred to pathogenic bacteria in the Antibiotic in strains from the human gut and products was by and all strains had shown resistance to a of antibiotics et al., of a that can reduce E. coli and Salmonella growth in resistance to antibiotics, including tetracycline, chloramphenicol, streptomycin, and et al., 2012). and of resistance with similar can be used as a to the risk of transfer from to pathogens et al., 2008). direct-fed strains produce fatty which can reduce gut and growth et al., 2013). However, in studies found that can develop to which is associated with increased resistance to other and increased virulence et al., et al., and as promising that or antibiotic is the use of bacteriocins or et al., 2015). Bacteriocins are by bacteria and and 2002; et al., that in mechanism of action, antimicrobial mechanisms, target cell receptors et al., and bactericidal et al., 2005). Bacteriocins can the of a in a environment et al., regulate gut et al., 2010), and of the et al., 2009). The mechanisms by which bacteriocins their bactericidal and effects include cell wall and plasma membrane disruption, of protein with DNA and and of cell et al., 2015; et al., 2017). Bacteriocins can be used to such as mastitis by in et al., to food and to the of strains et al., 2005; et al., 2013; et al., 2016). However, resistance to bacteriocins are et al., 2017). mechanisms of bacteriocin resistance in bacteria include cell wall and of the cell membrane which affect membrane fluidity and impairing bacteriocin ability to to bacterial These mechanisms are similar to of resistance to antibiotics, and this concern regarding the development of cross-resistance et al., 2014). the of system, impairing the binding of bacteriocins to the cell but this resistance is by a reduction in growth compared to the et al., 2017), that the development of resistance to bacteriocins may increase and of resistant strains et al., 2016). Some bacteriocins have been for improved and stability et al., and their use as agents is a developing area of research and 2012). However, there are currently only a products for use et al., 2016). is clear that there is into the development of antibiotic alternatives to support and animal production. As we with these it is important to resistance mechanisms in that these can be importantly, some of these antibiotic alternatives, such as zinc oxide, can contribute to increased antibiotic resistance and should be For other antibiotic alternatives, such as phage and bacteriocins, the potential contribution to antibiotic resistance is less but should be The of more specific antibiotic alternative such as and bacteriocins, is as they do not affect commensal new phage will always be as a result of the constant arms race between bacteria and any used be but we and ensure that we are not a with a in (Figure Antibiotic alternatives may be a in many antimicrobial alternatives target the post-weaning found in such as these have strong antibacterial is an at the of and Research in the of a in at of which at the of was with an research on and antibiotic and animal to microbes regulate in to and resistance. is a at the of in the of and under the of The focus of research is impacts the development of the Salmonella infection resistance, and in broiler production. has also done work the minimum inhibitory of different metals on multidrug-resistant is a in the of and at the of under the of is on the gut microbiome, a of and developing to the gut microbiome to the of systems that are less on antibiotic use. is a in the of and at the of under the of research on the impact of on health with particular interest in their effects on the gut microbiome and is a in the of and at the of by and research is on the interaction between gut microbiome, and in is a in the of and at the of As a is by at the of and at in The focus of research is the impact of on and fatty research the and of bacteriophages for their potential use in phage

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0040.001
Insufficient payload (model declined to judge)0.0120.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.244
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations38
Published2018
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