Antimicrobial resistance (AMR) is one of the Global Health challenges of the 21st century. The inclusion of AMR on the global map parallels the scientific, technological, and organizational progress of the healthcare system and the socioeconomic changes of the last 100 years. Available knowledge about AMR has mostly come from large healthcare institutions in high-income countries and is scattered in studies across various fields, focused on patient safety (infectious diseases), transmission pathways and pathogen reservoirs (molecular epidemiology), the extent of the problem at a population level (public health), their management and cost (health economics), cultural issues (community psychology), and events associated with historical periods (history of science). However, there is little dialogue between the aspects that facilitate the development, spread, and evolution of AMR and various stakeholders (patients, clinicians, public health professionals, scientists, economic sectors, and funding agencies). This study consists of four complementary sections. The first reviews the socioeconomic factors that have contributed to building the current Global Healthcare system, the scientific framework in which AMR has traditionally been approached in such a system, and the novel scientific and organizational challenges of approaching AMR in the fourth globalization scenario. The second discusses the need to reframe AMR in the current public health and global health contexts. Given that the implementation of policies and guidelines are greatly influenced by AMR information from surveillance systems, in the third section, we review the unit of analysis (“the what” and “the who”) and the indicators (the “operational units of surveillance”) used in AMR and discuss the factors that affect the validity, reliability, and comparability of the information to be applied in various healthcare (primary, secondary, and tertiary), demographic, and economic contexts (local, regional, global, and inter-sectorial levels). Finally, we discuss the disparities and similarities between distinct stakeholders’ objectives and the gaps and challenges of combatting AMR at various levels. In summary, this is a comprehensive but not exhaustive revision of the known unknowns about how to analyze the heterogeneities of hosts, microbes, and hospital patches, the role of surrounding ecosystems, and the challenges they represent for surveillance, antimicrobial stewardship, and infection control programs, which are the traditional cornerstones for controlling AMR in human health.

Vancomycin-resistant Enterococcus faecium (VREfm) have been increasingly reported since the 1980s. Despite the high number of published studies about VRE epidemiology, the dynamics and evolvability of these microorganisms are still not fully understood. A multilevel population genetic analysis of VREfm outbreak strains since 1986, representing the first comprehensive characterization of plasmid content in E. faecium, was performed to provide a detailed view of potential transmissible units. From a comprehensive MeSH search, we identified VREfm strains causing hospital outbreaks (1986–2012). In total, 53 VanA and 18 VanB isolates (27 countries, 5 continents) were analysed and 82 vancomycin-susceptible E. faecium (VSEfm) were included for comparison. Clonal relatedness was established by PFGE and MLST (goeBURST/Bayesian Analysis of Population Structure, BAPS). Characterization of van transposons (PCR mapping, RFLP, sequencing), plasmids (transfer, ClaI-RFLP, PCR typing of relaxases, replication-initiation proteins and toxin–antitoxin systems, hybridization, sequencing), bacteriocins and virulence determinants (PCR, hybridization, sequencing) was performed. VREfm were mainly associated with major human lineages ST17, ST18 and ST78. VREfm and VSEfm harboured plasmids of different families [RCR, small theta plasmids, RepA_N (pRUM/pLG1) and Inc18] able to yield mosaic elements. Tn1546-vanA was mainly located on pRUM/Axe-Txe (USA) and Inc18-pIP186 (Europe) plasmids. The VanB2 type (Tn5382/Tn1549) was predominant among VanB strains (chromosome and plasmids). Both strains and plasmids contributed to the spread and persistence of vancomycin resistance among E. faecium. Horizontal gene transfer events among genetic elements from different clonal lineages (same or different species) result in chimeras with different stability and host range, complicating the surveillance of epidemic plasmids.

Antimicrobial resistance is a major global health challenge. Metagenomics allows analyzing the presence and dynamics of “resistomes” (the ensemble of genes encoding antimicrobial resistance in a given microbiome) in disparate microbial ecosystems. However, the low sensitivity and specificity of available metagenomic methods preclude the detection of minority populations (often present below their detection threshold) and/or the identification of allelic variants that differ in the resulting phenotype. Here, we describe a novel strategy that combines targeted metagenomics using last generation in-solution capture platforms, with novel bioinformatics tools to establish a standardized framework that allows both quantitative and qualitative analyses of resistomes. We developed ResCap, a targeted sequence capture platform based on SeqCapEZ (NimbleGene) technology, which includes probes for 8667 canonical resistance genes (7963 antibiotic resistance genes and 704 genes conferring resistance to metals or biocides), and 2517 relaxase genes (plasmid markers) and 78,600 genes homologous to the previous identified targets (47,806 for antibiotics and 30,794 for biocides or metals). Its performance was compared with metagenomic shotgun sequencing (MSS) for 17 fecal samples (9 humans, 8 swine). ResCap significantly improves MSS to detect “gene abundance” (from 2.0 to 83.2%) and “gene diversity” (26 versus 14.9 genes unequivocally detected per sample per million of reads; the number of reads unequivocally mapped increasing up to 300-fold by using ResCap), which were calculated using novel bioinformatic tools. ResCap also facilitated the analysis of novel genes potentially involved in the resistance to antibiotics, metals, biocides, or any combination thereof. ResCap, the first targeted sequence capture, specifically developed to analyze resistomes, greatly enhances the sensitivity and specificity of available metagenomic methods and offers the possibility to analyze genes related to the selection and transfer of antimicrobial resistance (biocides, heavy metals, plasmids). The model opens the possibility to study other complex microbial systems in which minority populations play a relevant role.

Niches are spaces for the biological units of selection, from cells to complex communities. In a broad sense, “species” are biological units of individuation. Niches do not exist without individual organisms, and every organism has a niche. We use “niche” in the Hutchinsonian sense as an abstraction of a multidimensional environmental space characterized by a variety of conditions, both biotic and abiotic, whose quantitative ranges determine the positive or negative growth rates of the microbial individual, typically a species, but also parts of the communities of species contained in this space. Microbial organisms (“species”) constantly diversify, and such diversification (radiation) depends on the possibility of opening up unexploited or insufficiently exploited niches. Niche exploitation frequently implies “niche construction,” as the colonized niche evolves with time, giving rise to new potential subniches, thereby influencing the selection of a series of new variants in the progeny. The evolution of niches and organisms is the result of reciprocal interacting processes that form a single unified process. Centrifugal microbial diversification expands the limits of the species’ niches while a centripetal or cohesive process occurs simultaneously, mediated by horizontal gene transfers and recombinatorial events, condensing all of the information recovered during the diversifying specialization into “novel organisms” (possible future species), thereby creating a more complex niche, where the selfishness of the new organism(s) establishes a “homeostatic power” limiting the niche’s variation. Once the niche’s full carrying capacity has been reached, reproductive isolation occurs, as no foreign organisms can outcompete the established population/community, thereby facilitating speciation. In the case of individualization-speciation of the microbiota, its contribution to the animal’ gut structure is a type of “niche construction,” the result of crosstalk between the niche (host) and microorganism(s). Lastly, there is a parallelism between the hierarchy of niches and that of microbial individuals. The increasing anthropogenic effects on the biosphere (such as globalization) might reduce the diversity of niches and bacterial individuals, with the potential emergence of highly transmissible multispecialists (which are eventually deleterious) resulting from the homogenization of the microbiosphere, a possibility that should be explored and prevented.

The diversity of enterococcal populations from fecal samples from hospitalized ( n = 133) and nonhospitalized individuals ( n = 173) of different age groups (group I, ages 0 to 19 years; group II, ages 20 to 59 years; group III, ages ≥60 years) was analyzed. Enterococci were recovered at similar rates from hospitalized and nonhospitalized persons (77.44% to 79.77%) of all age groups (75.0% to 82.61%). Enterococcus faecalis and Enterococcus faecium were predominant, although seven other Enterococcus species were identified. E. faecalis and E. faecium (including ampicillin-resistant E. faecium ) colonization rates in nonhospitalized persons were age independent. For inpatients, E. faecalis colonization rates were age independent, but E. faecium colonization rates (particularly the rates of ampicillin-resistant E. faecium colonization) significantly increased with age. The population structure of E. faecium and E. faecalis was determined by superimposing goeBURST and Bayesian analysis of the population structure (BAPS). Most E. faecium sequence types (STs; 150 isolates belonging to 75 STs) were linked to BAPS groups 1 (22.0%), 2 (31.3%), and 3 (36.7%). A positive association between hospital isolates and BAPS subgroups 2.1a and 3.3a (which included major ampicillin-resistant E. faecium human lineages) and between community-based ampicillin-resistant E. faecium isolates and BAPS subgroups 1.2 and 3.3b was found. Most E. faecalis isolates (130 isolates belonging to 58 STs) were grouped into 3 BAPS groups, BAPS groups 1 (36.9%), 2 (40.0%), and 3 (23.1%), with each one comprising widespread lineages. No positive associations with age or hospitalization were established. The diversity and dynamics of enterococcal populations in the fecal microbiota of healthy humans are largely unexplored, with the available knowledge being fragmented and contradictory. The study offers a novel and comprehensive analysis of enterococcal population landscapes and suggests that E. faecium populations from hospitalized patients and from community-based individuals differ, with a predominance of certain clonal lineages, often in association with elderly individuals, occurring in the hospital setting.

The success of Enterococcus faecium and E. faecalis evolving as multi-resistant nosocomial pathogens is associated with their ability to acquire and share adaptive traits, including antimicrobial resistance genes encoded by mobile genetic elements (MGEs). Here, we investigate this mobilome in successful hospital associated genetic lineages, E. faecium sequence type (ST)17 (n=10) and ST78 (n=10), E. faecalis ST6 (n=10) and ST40 (n=10) by DNA microarray analyses. The hybridization patterns of 272 representative targets including plasmid backbones (n=85), transposable elements (n=85), resistance determinants (n=67), prophages (n=29) and clustered regularly interspaced short palindromic repeats (CRISPR)-cas sequences (n=6) separated the strains according to species, and for E. faecalis also according to STs. RCR-, Rep_3-, RepA_N- and Inc18-family plasmids were highly prevalent and with the exception of Rep_3, evenly distributed between the species. There was a considerable difference in the replicon profile, with rep 17/pRUM , rep 2/pRE25 , rep 14/EFNP1 and rep 20/pLG1 dominating in E. faecium and rep 9/pCF10 , rep 2/pRE25 and rep 7 in E. faecalis strains. We observed an overall high correlation between the presence and absence of genes coding for resistance towards antibiotics, metals, biocides and their corresponding MGEs as well as their phenotypic antimicrobial susceptibility pattern. Although most IS families were represented in both E. faecalis and E. faecium, specific IS elements within these families were distributed in only one species. The prevalence of IS256-, IS3-, ISL3-, IS200/IS605-, IS110-, IS982- and IS4-transposases was significantly higher in E. faecium than E. faecalis, and that of IS110-, IS982- and IS1182-transposases in E. faecalis ST6 compared to ST40. Notably, the transposases of IS981, ISEfm1 and IS1678 that have only been reported in few enterococcal isolates were well represented in the E. faecium strains. E. faecalis ST40 strains harboured possible functional CRISPR-Cas systems, and still resistance and prophage sequences were generally well represented. The targeted MGEs were highly prevalent among the selected STs, underlining their potential importance in the evolution of hospital-adapted lineages of enterococci. Although the propensity of inter-species horizontal gene transfer (HGT) must be emphasized, the considerable species-specificity of these MGEs indicates a separate vertical evolution of MGEs within each species, and for E. faecalis within each ST.