Recent development and fighting strategies for lincosamide antibiotic resistance

SUMMARYLincosamides constitute an important class of antibiotics used against a wide range of pathogens, including methicillin-resistant Staphylococcus aureus. However, due to the misuse of lincosamide and co-selection pressure, the resistance to lincosamide has become a serious concern. It is urgently needed to carefully understand the phenomenon and mechanism of lincosamide resistance to effectively prevent and control lincosamide resistance. To date, six mobile lincosamide resistance classes, including lnu, cfr, erm, vga, lsa, and sal, have been identified. These lincosamide resistance genes are frequently found on mobile genetic elements (MGEs), such as plasmids, transposons, integrative and conjugative elements, genomic islands, and prophages. Additionally, MGEs harbor the genes that confer resistance not only to antimicrobial agents of other classes but also to metals and biocides. The ultimate purpose of discovering and summarizing bacterial resistance is to prevent, control, and combat resistance effectively. This review highlights four promising strategies, including chemical modification of antibiotics, the development of antimicrobial peptides, the initiation of bacterial self-destruct program, and antimicrobial stewardship, to fight against resistance and safeguard global health.

Antimicrobial resistance determinants in silage

Animal products may play a role in developing and spreading antimicrobial resistance in several ways. On the one hand, residues of antibiotics not adequately used in animal farming can enter the human body via food. However, resistant bacteria may also be present in animal products, which can transfer the antimicrobial resistance genes (ARG) to the bacteria in the consumer's body by horizontal gene transfer. As previous studies have shown that fermented foods have a meaningful ARG content, it is indicated that such genes may also be present in silage used as mass feed in the cattle sector. In our study, we aspired to answer what ARGs occur in silage and what mobility characteristics they have? For this purpose, we have analyzed bioinformatically 52 freely available deep sequenced silage samples from shotgun metagenome next-generation sequencing. A total of 16 perfect matched ARGs occurred 54 times in the samples. More than half of these ARGs are mobile because they can be linked to integrative mobile genetic elements, prophages or plasmids. Our results point to a neglected but substantial ARG source in the food chain.

Large-scale characterization of the macrolide resistome reveals high diversity and several new pathogen-associated genes

Macrolides are broad-spectrum antibiotics used to treat a range of infections. Resistance to macrolides is often conferred by mobile resistance genes encoding Erm methyltransferases or Mph phosphotransferases. New erm and mph genes keep being discovered in clinical settings but their origins remain unknown, as is the type of macrolide resistance genes that will appear in the future. In this study, we used optimized hidden Markov models to characterize the macrolide resistome. Over 16 terabases of genomic and metagenomic data, representing a large taxonomic diversity (11 030 species) and diverse environments (1944 metagenomic samples), were searched for the presence of erm and mph genes. From this data, we predicted 28 340 macrolide resistance genes encoding 2892 unique protein sequences, which were clustered into 663 gene families (<70 % amino acid identity), of which 619 (94 %) were previously uncharacterized. This included six new resistance gene families, which were located on mobile genetic elements in pathogens. The function of ten predicted new resistance genes were experimentally validated in Escherichia coli using a growth assay. Among the ten tested genes, seven conferred increased resistance to erythromycin, with five genes additionally conferring increased resistance to azithromycin, showing that our models can be used to predict new functional resistance genes. Our analysis also showed that macrolide resistance genes have diverse origins and have transferred horizontally over large phylogenetic distances into human pathogens. This study expands the known macrolide resistome more than ten-fold, provides insights into its evolution, and demonstrates how computational screening can identify new resistance genes before they become a significant clinical problem.

Antimicrobial Resistance among Staphylococci of Animal Origin

Antimicrobial resistance among staphylococci of animal origin is based on a wide variety of resistance genes. These genes mediate resistance to many classes of antimicrobial agents approved for use in animals, such as penicillins, cephalosporins, tetracyclines, macrolides, lincosamides, phenicols, aminoglycosides, aminocyclitols, pleuromutilins, and diaminopyrimidines. In addition, numerous mutations have been identified that confer resistance to specific antimicrobial agents, such as ansamycins and fluoroquinolones. The gene products of some of these resistance genes confer resistance to only specific members of a class of antimicrobial agents, whereas others confer resistance to the entire class or even to members of different classes of antimicrobial agents, including agents approved solely for human use. The resistance genes code for all three major resistance mechanisms: enzymatic inactivation, active efflux, and protection/modification/replacement of the cellular target sites of the antimicrobial agents. Mobile genetic elements, in particular plasmids and transposons, play a major role as carriers of antimicrobial resistance genes in animal staphylococci. They facilitate not only the exchange of resistance genes among members of the same and/or different staphylococcal species, but also between staphylococci and other Gram-positive bacteria. The observation that plasmids of staphylococci often harbor more than one resistance gene points toward coselection and persistence of resistance genes even without direct selective pressure by a specific antimicrobial agent. This chapter provides an overview of the resistance genes and resistance-mediating mutations known to occur in staphylococci of animal origin.

Mobile macrolide resistance genes in staphylococci

Macrolide resistance in staphylococci is based on the expression of a number of genes which specify four major resistance mechanisms: (i) target site modification by methylation of the ribosomal target site in the 23S rRNA, (ii) ribosome protection via ABC-F proteins, (iii) active efflux via Major Facilitator Superfamily (MFS) transporters, and (iv) enzymatic inactivation by phosphotransferases or esterases. So far, 14 different classes of erm genes, which code for 23S rRNA methylases, have been reported to occur in staphylococci from humans, animals and environmental sources. Inducible or constitutive expression of the erm genes depends on the presence and intactness of a regulatory region known as translational attenuator. The erm genes commonly confer resistance not only to macrolides, but also to lincosamides and streptogramin B compounds. In contrast, the msr(A) gene codes for an ABC-F protein which confers macrolide and streptogramin B resistance whereas the mef(A) gene codes for a Major Facilitator Superfamily protein that can export only macrolides. Enzymatic inactivation of macrolides may be due to the macrolide phosphotransferase gene mph(C) or the macrolide esterase genes ere(A) or ere(B). Many of these macrolide resistance genes are part of either plasmids, transposons, genomic islands or prophages and as such, can easily be transferred across strain, species and genus boundaries. The co-location of other antimicrobial or metal resistance genes on the same mobile genetic element facilitates co-selection and persistence of macrolide resistance genes under the selective pressure of metals or other antimicrobial agents.

Changes in mouse gut bacterial community in response to different types of drinking water

Gut microbiota exerts a fundamental role on host physiology, and how extrinsic perturbations influence its composition has been increasingly examined. However, the effect of drinking water on gut microbiota is still poorly understood. In this study, we explored the response of mouse gut bacterial community (fecal and mucosa-adhered) to the ingestion of different types of drinking water. The experimental cohort was divided according to different water sources into four groups of mice that consumed autoclaved tap water (control group), water collected directly from a drinking water treatment plant, tap water, and commercial bottled mineral water. Differences among groups were observed, especially related to control group, which exhibited the smallest intra-group variation, and the largest distance from test groups on the last experimental day. Clinically important taxa, such as Acinetobacter and Staphylococcus, increased in feces of mice that drank tap water and in mucosa-adhered samples of animals from disinfected and tap water groups. Furthermore, statistical analyses showed that both time elapsed between samplings and water type significantly influenced the variation observed in the samples. Our results reveal that drinking water potentially affects gut microbiota composition. Additionally, the increase of typical drinking water clinically relevant and antibiotic resistance-associated bacteria in gut microbiota is a cause of concern.

Metabolomic profiling of Campylobacter jejuni with resistance gene ermB by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry and tandem quadrupole mass spectrometry

The metabolome changes of Campylobacter jejuni with resistant gene ermB remain unclear. Here, we described an untargeted metabolomic workflow based on ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry to investigate the metabolites perturbations mediated by ermB in C. jejuni. After optimization of extractants and chromatographic conditions, the combination of 100% methanol extraction with a 12 min gradient by C18 column was adopted for untargeted metabolomic profiling in reversed phase separation. Meanwhile, 60% methanol extraction followed by a 14 min separation using hydrophilic interaction chromatography column was suitable to complementally expand the metabolite coverage of C. jejuni. Multivariate statistical analysis was performed by means of orthogonal projection to latent structures-discriminant analysis to select metabolic features. The selected features were further confirmed by ultra-high performance liquid chromatography-tandem quadrupole mass spectrometry. A total of thirty-six differential metabolites between the susceptible strain (C. jejuni NCTC 11168) and resistant stain (C. jejuni NCTC 11168 with ermB) were identified. These pivotal metabolites were primarily participated in biological processes as cell signaling, membrane integrity/stability, fuel and energy source/storage and nutrient. The biofilm formation capability of resistant strain was inferior to that of susceptible strain, confirming the influence of ermB on membrane integrity/stability of C. jejuni. Our findings revealed important metabolic regulatory pathways associated with resistant C. jejuni with ermB.

A Novel erm(44) Gene Variant from a Human Staphylococcus saprophyticus Isolate Confers Resistance to Macrolides and Lincosamides but Not Streptogramins

A novel erm(44) gene variant, erm(44)_v, has been identified by whole-genome sequencing in a Staphylococcus saprophyticus isolate from the skin of a healthy person. It has the particularity to confer resistance to macrolides and lincosamides but not to streptogramin B when expressed in S. aureus The erm(44)_v gene resides on a 19,400-bp genomic island which contains phage-associated proteins and is integrated into the chromosome of S. saprophyticus.

Diversity of species and antimicrobial resistance determinants of staphylococci in superficial waters in Spain

The objectives were to determine the presence and diversity of staphylococcal species in surface waters in La Rioja region (Spain), and to characterize recovered isolates. Staphylococci were detected in 42 of 47 evaluable samples, and 72 isolates were obtained, of which 13 were coagulase-positive (CoPS) and 59 were coagulase-negative (CoNS). Twelve CoPS were identified as S. aureus and typed as follows (number of strains): t002/t502/ST5 (four), t10668/ST425 (one), t10712//ST1643 (one), t843/ST130 (one), t10855/ST2461 (one), t3369/ST2657 (one), t1166/ST133 (one), t8083/ST2049 (one) and t045/ST2460 (one); and one as S. pseudintermedius ST147. Virulence genes tst, cna and lukS/F-I were detected, and one strain showed the immune evasion cluster type F. Regarding CoNS, 12 different species were recovered (number of strains): S. epidermidis (11), S. vitulinus (10), S. sciuri (nine), S. fleurettii (seven), S. lentus (six), S. simulans (five), S. xylosus (four), S. chromogenes (two), S. hominis (two), and S. equorum, S. succinus and S. warneri (one each). Fourteen CoNS isolates presented a multidrug resistance phenotype, with the following resistance genes: blaZ, mecA, fusB, fusC, erm(C), mph(C), erm(A), msr(A)/(B), mph(C), ant(4')-Ia, tet(K), tet(L), cat_pc194 and str The high diversity of staphylococcal species, as well as multiple resistance and virulence genes, highlights the importance of surface waters as a temporary reservoir and source of transmission.

Novel chromosome-encoded erm(47) determinant responsible for constitutive MLSB resistance in Helcococcus kunzii

OBJECTIVES

The aim of the study was to identify the determinant responsible for erythromycin resistance in Helcococcus kunzii clinical isolate UCN99 and to characterize the genetic support and environment of this novel gene.

METHODS

MICs were determined using the broth microdilution method according to EUCAST guidelines. The entire genome sequence of H. kunzii UCN99 was determined using a 454/Roche GS Junior sequencer. The fragment encompassing the new resistance gene and its own promoter was cloned into the pAT29 shuttle vector and the recombinant plasmid pAT29Ωerm(47) was expressed in both Staphylococcus aureus and Streptococcus agalactiae. The transcription start site (TSS) was experimentally determined by 5' RACE-PCR.

RESULTS

UCN99 exhibited a constitutive macrolide/lincosamide/streptogramin B (MLS_B) resistance phenotype, suggesting the presence of an Erm protein. WGS allowed the identification of a novel gene, named erm(47), encoding a protein sharing 44%-48% amino acid identity with known Erm methylases. In both S. aureus and S. agalactiae, the introduction of pAT29Ωerm(47) conferred a significant increase (≥16-fold) in MICs of all macrolides and lincosamides tested, as well as a 4-fold increase in MICs of quinupristin (streptogramin B), confirming the MLS_B resistance. The TSS identification revealed the presence of a short leader peptide, potentially implicated in a translational attenuation mechanism. It was also demonstrated that erm(47) was harboured by a 81 kb genomic island integrated into a chromosomal gene.

CONCLUSIONS

This is the first description of a novel MLS_B resistance determinant, named erm(47). The prevalence of this gene among Gram-positive cocci must be further investigated to determine its clinical significance.

Resistance gene naming and numbering: is it a new gene or not?

In the genomic era, studying the epidemiology of individual antibiotic resistance genes and resistance gene discovery are open to all. However, the identification and naming of resistance genes is not currently understandable by all owing to a plethora of competing nomenclature systems, many of which do not comply with the basic rules of bacterial gene nomenclature. Change is needed urgently. Here, we make a case for the resistance research community to begin this process by agreeing on an answer to the question of when a new gene number should be assigned. This cut-off is of necessity arbitrary and we suggest a threshold value of ≥2% difference in the sequences of the DNA, predicted protein or both as a realistic boundary for assigning a new gene number. This proposal can be a starting point for agreement or debate followed by renumbering of the affected gene families.