Antibiotics
Antibiotics and their derivatives are widely used in poultry farming for therapeutic and prophylaxis purposes against bacterial infections and as growth promoters. There have been great strides in improving the fermentation process involving the production of various types of antibiotics such as tetracycline, making them readily available at affordable prices to poultry farmers. The antibiotics used for growth enhancement are usually amended in the animal feed or supplied with the poultry drinking water at sub-therapeutic doses (Mund et al., 2017).
There are no conclusive studies that explain the mechanisms of antibiotic growth promoters’ effects in animal husbandry; however most studies have focused on the general results of their use. Some of the hypothesized mechanisms of action of these antibiotics on poultry include managing chronic infections and general health improvement, better intestinal colonization by the beneficial bacteria, higher secretion of vitamins and other growth factors, and increasing nutrient absorption capability of the gut wall. These factors may act in synergy or additively, resulting in the growth enhancement of antibiotic-fed chickens and other animals (Lekshmi et al., 2017).
In sub-Saharan Africa and more so in Kenya, the dispensing and use of most veterinary antibiotics are not regulated. Anyone can access these drugs from the many agrochemical retailers throughout the country (Irungu et al., 2007). Veterinary Medicine Directorate (VMD) is a recently formed agency mandated at regulating the manufacture, importation, exportation, distribution, and dispensing of veterinary medicine and other related animal products in Kenya still, nothing much has been done since its inception in October 2015 in Kenya gazette supplement number 174 (add citation from the VMD website or Kenyan Gazette).
The Republic of Kenya, through the Ministry of Agriculture, livestock, Fisheries, and Irrigation published 152 ‘GUIDELINES FOR THE PRUDENT USE OF ANTIMICROBIALS IN ANIMALS’ in October 2018. These guidelines are supposed to be implemented and enforced by the relevant Government sectors such as The National and County Governments, Various regulatory Institutions such as the Kenya Veterinary Board (KVB), Veterinary Medicine Directorate (VMD), Research and Training Institutions, Private sector players including Manufacturers of pharmaceuticals and animal feed, various veterinary practitioners and animal keepers. (Directorate of Veterinary Services; Kenya, 2018). A dream yet to be realized as of now.
This lack of regulation has resulted in the abuse and misuse of these drugs by the farmers, whose improper administration has made these drugs to accumulate in biological systems including animal-sourced human food such as poultry products and plants. In addition, much of the dosage (over 90%) given to poultry is not assimilated in the body and is expelled in the feces. Poultry droppings are used as fertilizers, cattle and fish feed, among other uses, and therefore contaminating the other animals and environment with antibiotics (Franklin et al., 2016).
For example, the maximum residue level (MRL) recommended by Food and Agriculture Organization (FAO) and World Health Organization (WHO) joint expert committee for tetracycline in raw meat are 200, 600, and 1200 µg/Kg for liver, muscle and, kidney, respectively (Ramatla et al., 2017).
2.4 Bacteria resistance to antibiotics
Munita and Arias (2016) point out that discussion of antimicrobial resistance especially in bacteria is done based on various conceptions. First, bacteria naturally produce many antibiotics such as tetracycline and as such, these organisms and their co-residents are ‘intrinsically’ resistant to these antibiotics.
Intrinsic resistance is not usually the focus of antibiotic resistance in clinical discussions but rather ‘acquired resistance’ to antibiotics to which they were previously susceptible. However, intrinsic resistance can be passed to other medically important microorganisms. Second antibiotic resistance/ susceptibility is a complex phenomenon that can not only be explained by in vitro determination of sensitivity breakpoints (susceptibility, intermediate and resistant). Other factors such as pharmacological parameters, size of inoculum, site of infection among other in vivo factors come in play.
Bacteria use two main genetic strategies in adaptation to antibiotic resistance. The first is gene mutation whereby a portion of bacteria cells in a susceptible population undergoes mutations on the gene that is responsible for the interaction between the bacterium and the drug. The resistant mutant organism survives and predominates while the antibiotic eliminates the susceptible cells in the population. Horizontal gene transfer is another primary driver of bacterial resistance whereby foreign DNA, especially from intrinsic resistance, is passed to a susceptible bacterial population by such processes as transformation, transduction, and conjugation (Blair et al., 2015).
The underlying mechanisms of antibiotic resistance as discussed by Sosa et al. (2010) are, degradation of the antibacterial drugs by enzymes secreted by the resistant bacteria, alteration of the antimicrobial target sites on bacteria surface, membrane permeability changes to the antibiotics, and use of efflux mechanism to extrude the antibiotic from the bacterium. To achieve these resistant strains of bacteria have adapted various specific mechanisms by which they can successfully evade the threat of antimicrobial drugs. These include the following mechanisms.
First is the Multiple Antibiotic Resistance (mar) regulon by some gram-negative organisms, which is a rapid defense mechanism in response to environmental stress. For example the outer membrane of most Enterobactericeae family contain porins that are outer membrane proteins (OMP) with pores which are substrate-specific, ion-specific or non-specific channels that regulate the influx of substances (small hydrophilic nutrients) and efflux of waste products, antibiotics and other inhibitors such as bile salts (Ángel et al., 2010).
Second is the adaptation to oxidative stress (caused by high concentrations of Hydrogen peroxide (H2O2) and excess Oxygen (O2) or Nitric Oxide (NO-) inducing expression of oxyR and soxRS regulons respectively (Demple, 1996)). soxRS and oxyR regulons are critical response mechanisms as studied in Escherichia coli and Salmonella enterica. Koutsolioutsou et al., (2001) demonstrated that resistance to quinolones in a clinical isolate of Salmonella enterica serovar typhimurium is highly depended on expression of its soxRc allele and concluded that activation of the mar and soxRs regulons by immune attack, inflammation or antibiotics themselves can lead to multiple drug resistance. Many more similar studies have been done using other strains of bacteria, including Koutsolioutsou et al., (2005), Lee et al., (2009), Turnbull et al., (2010), and Daugherty et al., (2012), among others.
The above two mechanisms also work in conjunction with bacteria SOS response, which apart from being a system of deoxyribonucleic acid (DNA) repair is also involved in cell damage repair, horizontal gene transfer as well as cell hibernation and dormancy (Beaber et al., 2004; Michel, 2005). In a Study with E. coli, Dörr et al., (2009) revealed that antibiotic resistance to ciprofloxacin, a quinolone which causes DNA breaks in bacteria, is achieved when the SOS response is induced to repair these breaks by homologous recombination. Miller et al., (2004) also reported that SOS response genes are induced in E. coli due to defects in cell wall synthesis because of exposure to β-lactams antibiotics and thus limiting their antibiotic lethality. Many strains of bacteria are able to mount SOS response, which comprise of more than 30 inducible genes (Qin et al., 2015).
The third mechanism involves biofilm growth, which confers resistance and/or tolerance to antibiotics. Bacterial biofilm can simply be defined as a structure composed of cells from free-swimming plankton, which flock to form a mass of bacterial cells encased in an extra-cellular self-synthesizing polysaccharide matrix attached to a solid surface (De la Fuente-Núñez et al., 2013). Biofilms are not necessarily uniform structures having cells with the same physiological status and therefore, there is no particular single antibiotic tolerance/resistance mechanism through which they escape the effects of antibiotics. However, there are many varied antibiotic resistance/tolerance mechanisms that biofilms have shown to exhibit, and they include; Physiological barriers such as the matrix, slow growth rate, or cell dormancy due to a several reasons; (acidic and anoxic environment, nutrient deprivation, hypoxia which influences multidrug efflux pump), presence of resistance genes and other extracellular DNA, mutations, genetic transfer, prior exposure to antibiotics in sub-Minimum inhibitory concentrations (MICs), swarming of bacterial cells, and quorum sensing (Q-S) among many other studied mechanisms ( Stewart, 2002; Høiby et al., 2010; Mah, 2012; Balcázar et al., 2015; Hall et al., 2017)
Interdependency of plasmids and bacterial antibiotic resistance resulting in inhibiting the growth of cells that do not contain plasmids is the fourth mechanism by which microorganisms evade or escape the threat of antimicrobial drugs. Plasmids are circular, extra-chromosomal, autonomic replicating DNA elements that are non-essential to the host bacteria but confer advantageous qualities to the microorganisms such as ability to survive harsh environment conditions and development of rare metabolic pathways that utilize nutrients from substances, which are naturally too stable to be broken-down, or metabolized among other qualities. One such advantage of these plasmids is that they carry genes for antibiotic resistance (Carroll et al., 2018). Though advantageous, the presence of plasmids in bacteria poses a metabolic burden due to the extra energy required during their expression and replication and therefore are liable to be lost during cell division. The copy number of plasmids per bacterial cell varies from 1 – 2 copies for large plasmids and up to 200 copies per cell for small plasmids (Silva et al., 2012).
Tendencies of plasmid loss by bacteria due to non-segregation during cell division occur, especially in those cells with low copy numbers of the plasmids. Bacteria with no plasmid replicate faster than those without, and hence they can out-compete the latter. This has an overall disadvantage to the bacteria species because lack of plasmids makes them vulnerable to the condition the plasmid was conferring them to. Therefore, Bacteria have coped by developing adaptations that ensure that plasmids are passed on to daughter cells or those cells, that do not possess them are killed (Million-Weaver et al., 2014). Some of these adaptations are discussed below.
The first adaptation is the presence of partitioning systems (par system) which are genes found mostly in bacteria cells with low copy number of plasmids. They encode certain proteins that function as active partitioning mechanisms (segregation mechanism), which physically distribute plasmids in such a manner that each daughter cell receives at least one copy of the plasmid during cell division. These proteins are analogous to spindle fibres in eukaryotic cells. Examples of these partitioning systems found in plasmids includes the rep/mob of the gram positive bacteria, the Rep/ABC in alpha-proteobacteria, parRMC in gamma proteobacteria, sopABC of conjugated F plasmid among other well characterized partitioning systems ( Debaugny et al., 2018; Williams et al., 2018; Weaver & Camps, 2014; Ah-Seng et al., 2013; Pananghat et al., 2010; Salje et al., 2008; Million- Møller-Jensen et al., 2003; Bignell et al., 2001; Lin et al., 1998.).
The second adaptation by which a bacterial population ensures generational presence of plasmids is by random segregation. As earlier mentioned high copy number (hcn) plasmids has a heavy metabolic burden to the cells they occur in, due to the energy required in their expression and replication however, their presence in nature has persisted. The chances of losing plasmids due to non-segregation during cell division are highly diminished for hcn plasmids despite lack of positive selection e.g. the par systems in these cells. The stability of hcn plasmids over generations can be attributed to a phenomenon known as random distribution model where the plasmids are evenly diffused throughout the cytoplasm prior to random segregation at cell division (Wang, 2017; Nordström et al., 2003). This model of adaptation has however been negated by various assumptions such as normal distribution of plasmids in a population and lack of negative/positive selection as an expense of the metabolic burden, studies have shown that hcn plasmids are localized at the cell poles during cell division as opposed to having a normal distribution (Reyes-Lamothe et al., 2014).
The third and may be the most important adaptation of hcn plasmid containing cells is presence of plasmid addiction systems (PASs) which are ‘selfish’ plasmid DNA elements that ensure those cells that contain plasmids in a population retain their viability while those that do not are eliminated by processes such as post-segregational killing (PSK). Naturally PASs consists of a mechanism made of a stable toxin and unstable anti-toxin complex (TA system) which mediates PSK. Though there are many different modes through which TA PASs mechanisms operate, they all fall in to three categories namely; protein regulated PASs, antisense RNA regulated PASs and restriction modification PASs (Tsang, 2017). In 2007 Sevin and Barloy-Hubler developed a web tool known as Rapid Automated Scan for Toxins and Antitoxins in Bacteria (RASTA-Bacteria) for identification of TA loci in prokaryotic cells which relies on their genomic traits.
In protein regulated PASs, a stable toxin protein regulates the PSK in such a way that viability of those cells that retain plasmids after replication is maintained by continuous production of the antitoxin protein and thus ‘neutralizing’ the effects of the toxin while in those cell that lose plasmids, the unstable antitoxin leaves the stable toxin to accumulate leading to cell death (Engelberg-Kulka & Glaser, 1999). Examples of protein regulated loci TA PASs are the MazE/MazF, CcdB/CcdA, HipA/HipB e.t.c in E. coli, (Yamaguchi & Inouye, 2011) Zeta/Epsilo in streptococci, TasB/TasA in Bacillus thuringiensis, HigB/HigA in Proteus vulgaris and FitB/FitA in Nesseira gonorrhoeae among many others (Hayes, 2003). In most protein regulated systems the unstable antitoxin gene is located upstream the stable toxin gene. Its worthy to note that these protein regulated TA PASs are similar genetically and functionality differing only slightly in the gene loci (few are chromosomal while others are extra-chromosomal), the toxin target or mechanisms of the anti-toxin degradation.
Antisense RNA is an unstable single stranded RNA molecule that compliments its cognate mRNA and thereby inhibiting its translation. Antisense RNA regulated PASs take this advantage and utilize the mRNA to translate expression of a protein which acts as a stable toxin whose presence in high concentration lead to cell death however presence of the unstable antisense transcript acts as an antidote to the toxin. One of the most studied antisense RNA regulated PASs is the hok/sok system of the R1 plasmid in E. coli whose loci consists of three genes namely, hok, sok,and mok. The hok gene encodes for a stable toxin that kills cells internally by permanently damaging the cell membranes, hok gene requires mok gene for it to be translated and expressed but this is inhibited by sok gene which acts as an unstable antisense RNA transcript and binds to the mok gene. These sok-mok molecule binds with hok mRNA to form a hok mRNA:sok-mok duplex which is cleaved by RNase III and thereby saving the cell from PSK. More examples of antisense RNA regulated PASs include the par locus of the gram positive Enterococcus faecalis, ldrD–rdlD locus of E. coli and ratA–txpA of B. subtilis among others (Kroll et al., 2010).
The restriction modification PASs (RM PASs) consists of two genes, the first one encodes for a restriction endonuclease enzyme which acts as a toxin by cleaving DNA molecules at or near specific recognition sites of a nucleotide sequence while the second gene codes for a DNA methyltransferase enzyme that acts as an antitoxin by methylating a base on the recognition site thus preventing cleavage of DNA by the endonuclease. Hence, if a cell does not contain plasmids the methyltransferase will be degraded or diluted leading to the action of endonuclease, which creates breaks on chromosomal double, stranded DNA resulting in cell death. Ecor1 in E. coli and Bsp61 in Bacillus sp have demonstrated RM PASs (Sengupta et al., 2011).
The fifth, final and the most studied mechanism through which bacteria has successfully evaded antimicrobial actions is the mobility of the resistance gene a phenomenon that is still being studied since its discovery over 60 years ago. As stated earlier most resistance genes are carried by mobile extra chromosomal elements such as plasmids, transposons and integrons. These mobile genetic elements (MGEs) are capable of moving from one cell to another via vertical or horizontal (lateral) gene transfer. Vertical gene transfer occurs during cell division and is by segregation as previously discussed herein. Horizontal gene transfer is a part of ecological and evolutional adaptation of bacteria that confer them new phenotypic traits enabling them to conquer new ecological niches, whereby spread of antibiotic resistance is a good example (Gillings, 2017).
Horizontal gene transfer (HGT) is the most common mechanism by which bacteria acquire resistance gene carried in MGEs via processes such as conjugation (transfer of DNA directly from cell to cell often mediated by plasmids), transduction (transfer of DNA from cell to cell by phages) ,and transformation (acquisition of DNA by cell directly from the environment). Of these three mechanisms, the bacteria control only transformation while semiautonomous vectors such as phages and conjugative elements regulate the former two (Lerminiaux et al., 2019).
Conjugative plasmids are the most significant vectors because they contain genes that encode for their own transmission. HGT occurs interspecific, intraspecific, and even between various kingdoms. HGT in the environment is induced by selective pressure like presence of sub-lethal concentrations of antimicrobials and nano-particles, while some presence of metals are known to facilitate the transfer and uptake of these conjugative gene elements (Harrison et al., 2012). Other Conjugative and non-conjugative extra-chromosomal genetic elements such as transposons and integrons are also spread by HGT and therefore important contributing factors to the mosaic nature of the overall bacterial genome. HGT, PSK and partitioning systems are adaptation mechanisms that has allowed plasmids and other MGEs to persist in nature despite their obvious metabolic burden and as such increasing the bacterial fitness against antibiotics (Carroll & Wong, 2018).
2.5 Mode of resistance to specific classes of antibiotics
β lactam antibiotics act on penicillin-binding proteins (PBPs) that are involved in the synthesis of the bacterial cell wall. They encompass 4 classes namely penicillins such as penicillin G, amoxicillin and ampicillin, cepharosporins such as cephalexin, Cefuroxime, cefixime ,among others, carbapenems that includes imipenem, meropenem, doripenem exectra and lastly monobactams in which Aztreonam is the only approved drug. Resistance to these antibiotics is due to the presence of β-lactamases enzymes and less frequently, mutations in PBPs that result in low affinity of the cell membrane to the antibiotics (Bush et al., 2016).
β lactamases are classified in two main ways; the first method is called the Amber classification which classifies them on the basis of amino acid homology grouping them as cepharosporinases that include Extended Spectrum β lactamases (ESBLs) and carbapenemases encompassing all metallo-beta- lactamases (MBLs). Examples of ESBLs include SHV- (sulphydryl variable), TEM- (Temoneira), OXA- (oxacillin hydrolyzing abilities) and CTX-M (cefotaximase-Munich) all of which fall in classes A, C, and D in the Amber method of β lactamases classification while all MBLs are classified in class B in this type of classification (Kocsis and Szabó, 2013). The second method of β lactamases classification is the Bush-Jacoby-Medeiros classification which classifies them into 3 major groups and 16 sub-groups based on their substrates and inhibitors.
To counter problems posed by β lactamases, extensive research has been done on compounds that inhibit the action of these enzymes. These compounds are administered alongside or combined with the antibiotics however, there are challenges due to affinity variability of inhibitors to various β lactamases and occurrence of a vast range of these enzymes produced by the resistant strains. Examples of these β lactamases inhibitors include clavulanic acid, tazobactam, sulbactam among others (Blair et al., 2015).
Azmi et al., (2014) explains that flouroquinolones antibiotics target on bacteria are DNA gyrase (Topoisomerase II), and Topoisomerase IV whose gene (gry A, gry B and par C, par E for DNA gyrase and topoisomerase IV respectively) contain regions known as quinolone resistance determining regions (QRDRs). Resistance occurs due to point mutations on the nucleic acid resulting in the substitution of amino acids and thus diminishing the ability of quinolone binding (Hopkins et al., 2005). Resistance to quinolones can also be conferred by a low intracellular accumulation of the antibiotic due to innate efflux pumps and membrane impermeability of the drug especially in gram-negative bacteria (Carrique-mas, 2017).
The first plasmid mediated quinolone resistant (PMQR) was reported by Munshi et al., (1987) using clinical isolates of Shigella dysentriae type 1 against nalidixic acid. Later the gene responsible for PMQR was first confirmed in 1998 by Martínez-Martínez et al., and proposed the gene locus in the plasmid to be named quinolone resistance (qnr). More studies have been done since then with precedented discovery of a number of novel qnr that were ascertained to be DNA codes for pentapeptide repeat family proteins. The first PMQR determinant to be identified was designated QnrA1 with a few variants discovered later on, subsequently further research has detected more Qnrs that encompass QnrB, QnrC, QnrD and QnrS from enterobacteriaceae (Poirel et al., 2012; Tran et al., 2005). Other reported PMQR mechanisms include QepA and OqxAB that code for efflux pumps and aminoglycoside transferase AAC(6′)-Ib-cr, an enzyme that modifies ciprofloxacin. (Liu et al., 2013).
Aminoglycosides and polymyxin were the second important antibiotics to be discovered after penicillin. They were isolated from soil bacteria Streptomyces griseus in 1944, the first being streptomycin and later from Micromonospora sp such as gentamicin. Aminoglycosides bind to the 30s subunit of the bacteria and thus inhibit initiation of protein synthesis and also affect the fidelity of genetic message translation leading to synthesis of wrong proteins. They have a synergistic effect when administered together with some beta lactams though some react resulting in deactivation of the antibiotic (Krause et al., 2016).
Resistance of bacteria to aminoglycosides as discussed by Ramirez et al., (2013) is due to mutation of the 30s subunit and/or the energy dependent transport system and also inactivation of the antibiotic by structural modification using enzymes produced by the bacteria, the latter is the most studied mechanism of resistance with more than 50 reported aminoglycoside-inactivating enzymes. These enzymes act by three main reactions namely N-acetylation of amino groups using acetyl co A as a donor and N-acetyl transferases as the responsible enzyme, O-Adenylylation by O-Adenyl transferases that catalyzes transfer of an AMP from ATP to certain Hydroxyl groups within the structure of the antibiotic and lastly O-Phosphorylation by O-Phosphoryl transferases which uses ATP as a source of a phosphate group to phosphorylate some hydroxyl groups in the first and third rings of the antibiotics (Garneau-Tsodikova et al., 2016).
Unlike most eukaryotic cells which get their source of folic acid from uptake of nutrients, prokaryotes synthesize their folic acid de novo through a pathway that involves condensation of p, aminobenzoic acid (PABA) and 7,8-dihydro-6-hydroxymethylpterin-pyrophophate (DHPPP) forming dihydropteroic acid which is a precursor of dihydrofolic acid. The enzyme responsible for this reaction is dihydropteroate synthase (DHPS) which is the target of sulfonamides antibiotics and hence the basis of their selectivity. Due to their structural analogy with PABA substrate, they competitively bind to the enzyme and thus inhibiting formation of folic acid in the prokaryotes (Tacic et al., 2017).
Sulfonamides were the first synthetic antibiotics to be used systematically and have broad spectrum activity against bacteria and other prokaryotic parasites. Sulfonamides are usually administered together with trimethoprim that are also synthetic compounds in diaminopyrimidine group acting as antifolate by competitively inhibiting dihydrofolate reductase (DHFR) enzyme that catalyzes the reduction of dihydrofolic acid to tetrahydrofolate, an essential reaction in the synthesis of folic acid in prokaryotic cells. Both drugs act synergistically when administered together (Sköld, 2001).
Due to the fact that sulfonamides and trimethoprim are synthetic compounds, resistance to them is majorly not intrinsic rather is due to gene mutations of the chromosomal target enzymes dihydropteroate synthase (dhps) and dihydrofolate reductase (dhfr), respectively. These gene alteration range from structural modifications of the dhps (folp) and dhfr gene that include single base pair substitutions as documented in E. coli to recombination in Neisseria sp. These mutations occurred randomly and spontaneously across various bacteria genera resulting mostly in efficient folic acid production caused by over-production of the substrates and increased affinity of the enzymes to substrates and thus reduction of inhibition by the sulfonamide and trimethoprim drugs (Sköld et al., 2017).
The second and the most important mechanism of sulfonamide and trimethoprim resistance occurs through plasmid-mediated gene. Four plasmid borne gene sul1, 2, 3, and 4 has been described to code for dhps resistance. Sul 1 and sul 2 are the most studied and clinically relevant gene, the former is located in the class 1 integron and is associated with other resistance gene while the latter is located in the smaller non-conjugative plasmid of the incQ
group. Sul 3 was characterized from E. coli pVP440 conjugative plasmid which were isolated from pigs while sul 4 was recently found in class 1 integron gene from sediments in an Indian river though it has not been shown to occur in clinical isolates (Sánchez-Osuna et al., 2019). Plasmid encoded trimethoprim resistant gene cassetes are few, about 20 gene encoding for DHFRs resistance are known and they are located in both the class 1 and 2 integrons. They are consecutively numbered from dfr 1 onwards and the list is still growing (Sköld et al., 2001).
Tetracycline act by binding to the 30s subunit of the ribosome and thus distorting the A site to which charged tRNAs bind and thereby inhibiting protein synthesis (Li et al., 2013). The various mechanisms of tetracycline resistance as reviewed by Roberts and Schwarz, (2016) include; energy dependent efflux pumps that are regulated by more than 30 different genes, ribosome protection by proteins with more than different 12 gene, enzyme inactivation with more than 3 different gene and , ribosomal mutations. Most of these genes are associated with plasmids, both non-conjugative and conjugative transposons, and integrons consequently making the distribution of these ARGs wide spread among different genera of microorganism.
Tetracycline resistance genes are categorized into two major classes (tet and otr) by molecular techniques such as DNA-DNA hybridization, restriction enzyme analysis, and gene expression. The nomenclature of these genes is done by assigning the gene class a Roman alphabet letter however the tet genes have reached the end of the alphabet and instead new tet genes are now being assigned numbers. In an article Grossman, (2016) discusses that, among the 30 or so tetracycline resistance efflux genes the most abundant are tet A, B, C and D, included also are a few ort and tcr genes. The genes coding for ribosomal protection proteins (RPPs) include tet(O), tet(M), tet(Q), tet(S), and otr(A) among others though there are about 11 more mosaic genes that code for RPPs examples being tet(O/32/O) and tet(O/W/32/O). The three known genes that code for tetracycline resistance by enzymatic inactivation are tet(X)+, tet(34), and tet(37)+. In addition there is also one more gene whose mechanism of action is still unknown and is named tet(U) (Ian et al., 2001).
Macrolides antibiotics bind to the 23s subunit of the larger 50s subunit of the ribosome causing early detachment of premature polypeptide chain by inhibiting transpeptidation and translocation process during protein synthesis (Vester et al., 2001). They are structurally made of a macro-lactonic ring surrounded by a series of amino sugars and other side chains. Macrolides are classified in a number of ways but the most common classification is based on the size of the ring and structural modification of the natural ring. Based on the size of the ring, macrolides are classified as 13C, 14C, 15C, and 16C depending on the number of carbon within the ring. Erythromycin, which is a natural antibiotic, is a 14C macrolide while Azithromycin is a semisynthetic antibiotic whose macro-lactonic ring is made of 15 carbons (15C.) (Giguère, 2013). Classification according to structural modification divides the macrolides into four groups; the natural macrolides such as erythromycin, azalides which include azithromycin, Ketolides example being Picromycin and flouroketolides which are still under development with solithromycin as an example (Gomes et al., 2017).
Bolinger et al., (2017) illustrates resistance to macrolides as due to rRNA methylation, drug efflux and enzyme inactivation, with the first two exhibited by majority of the resistant isolates. Most macrolide resistance genes are associated with mobile extra-chromosomal genetic elements and therefore they can potentially be spread among different bacterial ecosystems. Resistance to macrolides by methylation of rRNA is encoded by erythromycin resistant methylase (erm) methyltransferases which are synthesized by macrolides producers and transferred horizontally to clinically relevant organisms. These gene acts by dimethylating specific sites at the macrolide binding site and there by drastically reducing the drug affinity to the target site rendering the organisms resistant to even high doses of the drug (Gaynor et al., 2012).
Apart from target site modification by the erm, expulsion of the drug from bacterial cells by efflux transporters is also an important mechanism of macrolide resistance. There are more than nine ATP transporters and two major facilitator superfamily (MFS) proteins that actively pump the drug from the cells through the cell membrane and cell wall. The intercellular concentration of the drug is consequently kept low thus allowing the ribosomes to function optimally without the drug interruption . Majority of these transporter proteins have been isolated from Streptomyces spp but some were isolated in other microorganisms such as staphylococcus spp and Enterococcus spp (Roberts, 2004). Other less common modes of Macrolide resistance mechanisms include enzyme inactivation (macrolide esterases. Glycosyltransferases, kinases and phosphotransferases) (Dinos, 2017) and presence of short peptides that are known to mediate macrolide resistance
Glycopeptides antibiotics (GPAs) are also referred, as ‘drugs of the last resort’ and mainly used in treatment of drug resistant gram-positive bacteria such as methicillin resistant Staphylococcus aureus (MRSA), Enterococcus spp and Clostridium difficale. This class of antibiotics consists of both natural and semi-synthetic compounds whose structure is composed of a glycolysated cyclic or polycyclic heptapeptide moiety. The first generation GPAs were isolated from actinomycetes in late 1950s, vancomycin (1958) and teicoplanin (1978) were isolated from Amycolatopsis orientalis and Actinoplanes teichomyceticus respectively and are still important clinical treatment options though semi-synthetic GPAs such as telavancin, dalbavancin and oritavancin have been developed to curb the continued resistance to GPAs (Butler et al., 2014).
The mechanism of action of GPAs is inhibition of bacterial cell wall synthesis, whereby the heptapeptide backbone non-covalently bind to l-lys-D-ala-D-Ala terminus of peptidoglycan precursor lipid ii via five Hydrogen bonds and thereby inhibiting transpeptidation and transglycosylation reactions in the late stages of peptidoglycan cross-linking (Binda et al., 2014). Resistance to GPAs is a remarkable process that is engineered by multiple proteins encoded by mobile transposons to alter the binding site of the antibiotics to the peptidoglycan rendering the drug ‘useless’. Genes encoding these polypeptides responsible for transposition are located on Tn1546: ORF1 and ORF2 and they include those that regulate the resistance (VanR and VanS), modification of the peptidoglycan precursor that terminates dipeptide D-Ala-D-Ala with depsipeptide D-Ala-D-lac (VanH and VanA) and hydrolysis of the remnant dipeptide D-Ala-D-Ala terminus (VanX and VanY). This replacement of the dipeptide D-Ala-D-Ala terminus with depsipeptide D-Ala-D-lac structurally modifies the target site of the GPAs and thus reducing the antibiotics affinity to the peptidoglycan layer (O’Driscoll et al., 2015; Zeng et al., 2016)