The human gut resistome

In recent decades, the emergence and spread of antibiotic resistance among bacterial pathogens has become a major threat to public health. Bacteria can acquire antibiotic resistance genes by the mobilization and transfer of resistance genes from a donor strain. The human gut contains a densely populated microbial ecosystem, termed the gut microbiota, which offers ample opportunities for the horizontal transfer of genetic material, including antibiotic resistance genes. Recent technological advances allow microbiota-wide studies into the diversity and dynamics of the antibiotic resistance genes that are harboured by the gut microbiota (‘the gut resistome’). Genes conferring resistance to antibiotics are ubiquitously present among the gut microbiota of humans and most resistance genes are harboured by strictly anaerobic gut commensals. The horizontal transfer of genetic material, including antibiotic resistance genes, through conjugation and transduction is a frequent event in the gut microbiota, but mostly involves non-pathogenic gut commensals as these dominate the microbiota of healthy individuals. Resistance gene transfer from commensals to gut-dwelling opportunistic pathogens appears to be a relatively rare event but may contribute to the emergence of multi-drug resistant strains, as is illustrated by the vancomycin resistance determinants that are shared by anaerobic gut commensals and the nosocomial pathogen Enterococcus faecium.     

Functional Characterization of Bacteria Isolated from Ancient Arctic Soil Exposes Diverse Resistance Mechanisms to Modern Antibiotics

Using functional metagenomics to study the resistomes of bacterial communities isolated from different layers of the Canadian high Arctic permafrost, we show that microbial communities harbored diverse resistance mechanisms at least 5,000 years ago. Among bacteria sampled from the ancient layers of a permafrost core, we isolated eight genes conferring clinical levels of resistance against aminoglycoside, β-lactam and tetracycline antibiotics that are naturally produced by microorganisms. Among these resistance genes, four also conferred resistance against amikacin, a modern semi-synthetic antibiotic that does not naturally occur in microorganisms. In bacteria sampled from the overlaying active layer, we isolated ten different genes conferring resistance to all six antibiotics tested in this study, including aminoglycoside, β-lactam and tetracycline variants that are naturally produced by microorganisms as well as semi-synthetic variants produced in the laboratory. On average, we found that resistance genes found in permafrost bacteria conferred lower levels of resistance against clinically relevant antibiotics than resistance genes sampled from the active layer. Our results demonstrate that antibiotic resistance genes were functionally diverse prior to the anthropogenic use of antibiotics, contributing to the evolution of natural reservoirs of resistance genes.     

Functional cloning and characterization of antibiotic resistance genes from the chicken gut microbiome

Culture-independent sampling in conjunction with a functional cloning approach identified diverse antibiotic resistance genes for different classes of antibiotics in gut microbiomes from both conventionally raised and free-range chickens. Many of the genes are phylogenetically distant from known resistance genes. Two unique genes that conferred ampicillin and spectinomycin resistance were also functional in Campylobacter, a distant relative of the Escherichia coli host used to generate the genomic libraries.     

Resistance to β-Lactam Antibiotics Conferred by Point Mutations in Penicillin-Binding Proteins PBP3, PBP4 and PBP6 in Salmonella enterica

Penicillin-binding proteins (PBPs) are enzymes responsible for the polymerization of the glycan strand and the cross-linking between glycan chains as well as the target proteins for β-lactam antibiotics. Mutational alterations in PBPs can confer resistance either by reducing binding of the antibiotic to the active site or by evolving a β-lactamase activity that degrades the antibiotic. As no systematic studies have been performed to examine the potential of all PBPs present in one bacterial species to evolve increased resistance against β-lactam antibiotics, we explored the ability of fifteen different defined or putative PBPs in Salmonella enterica to acquire increased resistance against penicillin G. We could after mutagenesis and selection in presence of penicillin G isolate mutants with amino-acid substitutions in the PBPs, FtsI, DacB and DacC (corresponding to PBP3, PBP4 and PBP6) with increased resistance against β-lactam antibiotics. Our results suggest that: (i) most evolved PBPs became ‘generalists” with increased resistance against several different classes of β-lactam antibiotics, (ii) synergistic interactions between mutations conferring antibiotic resistance are common and (iii) the mechanism of resistance of these mutants could be to make the active site more accessible for water allowing hydrolysis or less binding to β-lactam antibiotics.     

Knowledge and Attitudes towards Antibiotic Use and Resistance - A Latent Class Analysis of a Swedish Population-Based Sample

BackgroundIn 2006, a study investigating knowledge and attitudes regarding antibiotic use and resistance in Sweden, indicated high level of knowledge but also areas in need of improvement.Objective(i) To provide an update on the knowledge and attitudes to antibiotic use and resistance of the Swedish population, and (ii) to identify which groups within the population are in particular need of improved knowledge or attitudes.MethodsA questionnaire was sent by post in 2013 to 2,500 randomly-selected individuals aged 18–74, living in Sweden. Latent class analyses were conducted to group respondents based on their responses. The association between socio-demographic characteristics and the probability of belonging to each latent class was assessed.ResultsThe response rate was 57%. Ninety-four per cent of the responders knew that bacteria could become resistant to antibiotics and the majority answered correctly to the questions regarding antibiotic resistance development. The respondents expressed confidence in doctors who decided not to prescribe antibiotics. Three latent classes related to ‘knowledge regarding antibiotic use and resistance’, two regarding ‘attitudes towards antibiotic accessibility and infection prevention’ and three regarding ‘attitudes towards antibiotic use and effects’ were revealed. Men, younger and more educated people were more knowledgeable but males had a less restrictive attitude. Respondents with high levels of knowledge on antibiotics were more likely to have appropriate restrictive attitudes to antibiotics.ConclusionKnowledge on antibiotic use and resistance is maintained high and has improved in Sweden compared to 2006. People with lower education and elderly are especially in need of improved knowledge about antibiotic use and resistance.     

Compositional and genetic alterations in Graves’ disease gut microbiome reveal specific diagnostic biomarkers

Graves’ Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves’ disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson’s Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.Subject terms: Microbiome, Biomarkers, Population genetics     

Application of Microarray and Functional-Based Screening Methods for the Detection of Antimicrobial Resistance Genes in the Microbiomes of Healthy Humans

The aim of this study was to screen for the presence of antimicrobial resistance genes within the saliva and faecal microbiomes of healthy adult human volunteers from five European countries. Two non-culture based approaches were employed to obviate potential bias associated with difficult to culture members of the microbiota. In a gene target-based approach, a microarray was employed to screen for the presence of over 70 clinically important resistance genes in the saliva and faecal microbiomes. A total of 14 different resistance genes were detected encoding resistances to six antibiotic classes (aminoglycosides, β-lactams, macrolides, sulphonamides, tetracyclines and trimethoprim). The most commonly detected genes were erm(B), bla _TEM, and sul2. In a functional-based approach, DNA prepared from pooled saliva samples was cloned into Escherichia coli and screened for expression of resistance to ampicillin or sulphonamide, two of the most common resistances found by array. The functional ampicillin resistance screen recovered genes encoding components of a predicted AcrRAB efflux pump. In the functional sulphonamide resistance screen, folP genes were recovered encoding mutant dihydropteroate synthase, the target of sulphonamide action. The genes recovered from the functional screens were from the chromosomes of commensal species that are opportunistically pathogenic and capable of exchanging DNA with related pathogenic species. Genes identified by microarray were not recovered in the activity-based screen, indicating that these two methods can be complementary in facilitating the identification of a range of resistance mechanisms present within the human microbiome. It also provides further evidence of the diverse reservoir of resistance mechanisms present in bacterial populations in the human gut and saliva. In future the methods described in this study can be used to monitor changes in the resistome in response to antibiotic therapy.     

Combination Patterns of Major R Genes Determine the Level of Resistance to the M. oryzae in Rice (Oryza sativa L.)

Rice blast caused by Magnaporthe oryzae is the most devastating disease of rice and poses a serious threat to world food security. In this study, the distribution and effectiveness of 18 R genes in 277 accessions were investigated based on pathogenicity assays and molecular markers. The results showed that most of the accessions exhibited some degree of resistance (resistance frequency, RF >50%). Accordingly, most of the accessions were observed to harbor two or more R genes, and the number of R genes harbored in accessions was significantly positively correlated with RF. Some R genes were demonstrated to be specifically distributed in the genomes of rice sub-species, such as Pigm, Pi9, Pi5 and Pi1, which were only detected in indica-type accessions, and Pik and Piz, which were just harbored in japonica-type accessions. By analyzing the relationship between R genes and RF using a multiple stepwise regression model, the R genes Pid3, Pi5, Pi9, Pi54, Pigm and Pit were found to show the main effects against M. oryzae in indica-type accessions, while Pita, Pb1, Pik, Pizt and Pia were indicated to exhibit the main effects against M. oryzae in japonica-type accessions. Principal component analysis (PCA) and cluster analysis revealed that combination patterns of major R genes were the main factors determining the resistance of rice varieties to M. oryzae, such as ‘Pi9+Pi54’, ‘Pid3+Pigm’, ‘Pi5+Pid3+Pigm’, ‘Pi5+Pi54+Pid3+Pigm’, ‘Pi5+Pid3’ and ‘Pi5+Pit+Pid3’ in indica-type accessions and ‘Pik+Pib’, ‘Pik+Pita’, ‘Pik+Pb1’, ‘Pizt+Pia’ and ‘Pizt+Pita’ in japonica-type accessions, which were able to confer effective resistance against M. oryzae. The above results provide good theoretical support for the rational utilization of combinations of major R genes in developing rice cultivars with broad-spectrum resistance.     

Identification of Aminoglycoside and β-Lactam Resistance Genes from within an Infant Gut Functional Metagenomic Library

The infant gut microbiota develops rapidly during the first 2 years of life, acquiring microorganisms from diverse sources. During this time, significant opportunities exist for the infant to acquire antibiotic resistant bacteria, which can become established and constitute the infant gut resistome. With increased antibiotic resistance limiting our ability to treat bacterial infections, investigations into resistance reservoirs are highly pertinent. This study aimed to explore the nascent resistome in antibiotically-naïve infant gut microbiomes, using a combination of metagenomic approaches. Faecal samples from 22 six-month-old infants without previous antibiotic exposure were used to construct a pooled metagenomic library, which was functionally screened for ampicillin and gentamicin resistance. Our library of ∼220Mb contained 0.45 ampicillin resistant hits/Mb and 0.059 gentamicin resistant hits/Mb. PCR-based analysis of fosmid clones and uncloned metagenomic DNA, revealed a diverse and abundant aminoglycoside and β-lactam resistance reservoir within the infant gut, with resistance determinants exhibiting homology to those found in common gut inhabitants, including Escherichia coli, Enterococcus sp., and Clostridium difficile, as well as to genes from cryptic environmental bacteria. Notably, the genes identified differed from those revealed when a sequence-driven PCR-based screen of metagenomic DNA was employed. Carriage of these antibiotic resistance determinants conferred substantial, but varied (2–512x), increases in antibiotic resistance to their bacterial host. These data provide insights into the infant gut resistome, revealing the presence of a varied aminoglycoside and β-lactam resistance reservoir even in the absence of selective pressure, confirming the infant resistome establishes early in life, perhaps even at birth.     

Antibiotic resistance is prevalent in an isolated cave microbiome

Antibiotic resistance is a global challenge that impacts all pharmaceutically used antibiotics. The origin of the genes associated with this resistance is of significant importance to our understanding of the evolution and dissemination of antibiotic resistance in pathogens. A growing body of evidence implicates environmental organisms as reservoirs of these resistance genes; however, the role of anthropogenic use of antibiotics in the emergence of these genes is controversial. We report a screen of a sample of the culturable microbiome of Lechuguilla Cave, New Mexico, in a region of the cave that has been isolated for over 4 million years. We report that, like surface microbes, these bacteria were highly resistant to antibiotics; some strains were resistant to 14 different commercially available antibiotics. Resistance was detected to a wide range of structurally different antibiotics including daptomycin, an antibiotic of last resort in the treatment of drug resistant Gram-positive pathogens. Enzyme-mediated mechanisms of resistance were also discovered for natural and semi-synthetic macrolide antibiotics via glycosylation and through a kinase-mediated phosphorylation mechanism. Sequencing of the genome of one of the resistant bacteria identified a macrolide kinase encoding gene and characterization of its product revealed it to be related to a known family of kinases circulating in modern drug resistant pathogens. The implications of this study are significant to our understanding of the prevalence of resistance, even in microbiomes isolated from human use of antibiotics. This supports a growing understanding that antibiotic resistance is natural, ancient, and hard wired in the microbial pangenome.     

Towards a mechanistic understanding of reciprocal drug–microbiome interactions

Broad‐spectrum antibiotics target multiple gram‐positive and gram‐negative bacteria, and can collaterally damage the gut microbiota. Yet, our knowledge of the extent of damage, the antibiotic activity spectra, and the resistance mechanisms of gut microbes is sparse. This limits our ability to mitigate microbiome‐facilitated spread of antibiotic resistance. In addition to antibiotics, non‐antibiotic drugs affect the human microbiome, as shown by metagenomics as well as in vitro studies. Microbiome–drug interactions are bidirectional, as microbes can also modulate drugs. Chemical modifications of antibiotics mostly function as antimicrobial resistance mechanisms, while metabolism of non‐antibiotics can also change the drugs’ pharmacodynamic, pharmacokinetic, and toxic properties. Recent studies have started to unravel the extensive capacity of gut microbes to metabolize drugs, the mechanisms, and the relevance of such events for drug treatment. These findings raise the question whether and to which degree these reciprocal drug–microbiome interactions will differ across individuals, and how to take them into account in drug discovery and precision medicine. This review describes recent developments in the field and discusses future study areas that will benefit from systems biology approaches to better understand the mechanistic role of the human gut microbiota in drug actions.     

Steering Evolution with Sequential Therapy to Prevent the Emergence of Bacterial Antibiotic Resistance

The increasing rate of antibiotic resistance and slowing discovery of novel antibiotic treatments presents a growing threat to public health. Here, we consider a simple model of evolution in asexually reproducing populations which considers adaptation as a biased random walk on a fitness landscape. This model associates the global properties of the fitness landscape with the algebraic properties of a Markov chain transition matrix and allows us to derive general results on the non-commutativity and irreversibility of natural selection as well as antibiotic cycling strategies. Using this formalism, we analyze 15 empirical fitness landscapes of E. coli under selection by different β-lactam antibiotics and demonstrate that the emergence of resistance to a given antibiotic can be either hindered or promoted by different sequences of drug application. Specifically, we demonstrate that the majority, approximately 70%, of sequential drug treatments with 2–4 drugs promote resistance to the final antibiotic. Further, we derive optimal drug application sequences with which we can probabilistically ‘steer’ the population through genotype space to avoid the emergence of resistance. This suggests a new strategy in the war against antibiotic–resistant organisms: drug sequencing to shepherd evolution through genotype space to states from which resistance cannot emerge and by which to maximize the chance of successful therapy.     

Factors That Affect Transfer of the IncI1 β-Lactam Resistance Plasmid pESBL-283 between E. coli Strains

The spread of antibiotic resistant bacteria worldwide presents a major health threat to human health care that results in therapy failure and increasing costs. The transfer of resistance conferring plasmids by conjugation is a major route by which resistance genes disseminate at the intra- and interspecies level. High similarities between resistance genes identified in foodborne and hospital-acquired pathogens suggest transmission of resistance conferring and transferrable mobile elements through the food chain, either as part of intact strains, or through transfer of plasmids from foodborne to human strains. To study the factors that affect the rate of plasmid transfer, the transmission of an extended-spectrum β-lactamase (ESBL) plasmid from a foodborne Escherichia coli strain to the β-lactam sensitive E. coli MG1655 strain was documented as a function of simulated environmental factors. The foodborne E. coli isolate used as donor carried a CTX-M-1 harboring IncI1 plasmid that confers resistance to β-lactam antibiotics. Cell density, energy availability and growth rate were identified as factors that affect plasmid transfer efficiency. Transfer rates were highest in the absence of the antibiotic, with almost every acceptor cell picking up the plasmid. Raising the antibiotic concentrations above the minimum inhibitory concentration (MIC) resulted in reduced transfer rates, but also selected for the plasmid carrying donor and recombinant strains. Based on the mutational pattern of transconjugant cells, a common mechanism is proposed which compensates for fitness costs due to plasmid carriage by reducing other cell functions. Reducing potential fitness costs due to maintenance and expression of the plasmid could contribute to persistence of resistance genes in the environment even without antibiotic pressure. Taken together, the results identify factors that drive the spread and persistence of resistance conferring plasmids in natural isolates and shows how these can contribute to transmission of resistance genes through the food chain.     

Explaining Bacterial Dispersion on Leaf Surfaces with an Individual-Based Model (PHYLLOSIM)

We developed the individual-based model PHYLLOSIM to explain observed variation in the size of bacterial clusters on plant leaf surfaces (the phyllosphere). Specifically, we tested how different ‘waterscapes’ impacted the diffusion of nutrients from the leaf interior to the surface and the growth of individual bacteria on these nutrients. In the ‘null’ model or more complex ‘patchy’ models, the surface was covered with a continuous water film or with water drops of equal or different volumes, respectively. While these models predicted the growth of individual bacterial immigrants into clusters of variable sizes, they were unable to reproduce experimentally derived, previously published patterns of dispersion which were characterized by a much larger variation in cluster sizes and a disproportionate occurrence of clusters consisting of only one or two bacteria. The fit of model predictions to experimental data was about equally poor (<5%) regardless of whether the water films were continuous or patchy. Only by allowing individual bacteria to detach from developing clusters and re-attach elsewhere to start a new cluster, did PHYLLOSIM come much closer to reproducing experimental observations. The goodness of fit including detachment increased to about 70–80% for all waterscapes. Predictions of this ‘detachment’ model were further supported by the visualization and quantification of bacterial detachment and attachment events at an agarose-water interface. Thus, both model and experiment suggest that detachment of bacterial cells from clusters is an important mechanism underlying bacterial exploration of the phyllosphere.     

Novel genes underlying beta cell survival in metabolic stress

Relative insulin deficiency, in response to increased metabolic demand (obesity, genetic insulin resistance, pregnancy and aging) lead to Type2 diabetes. Susceptibility of the type 2 diabetes has a genetic basis, as a subset of people with risk factors (obesity, Insulin Resistance, pregnancy), develop Type2 Diabetes. We aimed to identify ‘cluster’ of overexpressed genes, underlying increased beta cell survival in diabetes resistant C57BL/6J ob/ob mice (compared to diabetes susceptible BTBR ob/ob mice). We used ‘consensus’ overexpression status to identify ‘cluster’ of 11 genes consisting of Aldh18a1, Rfc4, Dynlt3, Prom1, H13, Psen1, Ssr4, Dad1, Anpep, Fam111a and Plk1. Information (biological processes, molecular functions, cellular components, protein-protein interactions/associations, gene deletion/knockout/inhibition studies) of all the genes in ‘cluster’ were collected by text mining using different literature search tools, gene information databases and protein-protein interaction databases. Beta cell specific function of these genes were also inferred using meta analysis tool of Beta Cell Biology Consortium, by studying the expression pattern of these genes in microarray studies related to beta-cell stimulation/injury, pancreas development and growth and cell differentiation. In the ‘clusters’, 6 genes (Dad1, Psen1, Ssr4, Rfc4, H13, Plk1) have a role in cell survival. Only Psen1 was previously identified to have role in successful beta cell compensation. We advocate these genes to be potentially involved in successful beta cell compensation and prevent T2D in humans, by conferring protection against diabetogenic insults.     

Are Patient Views about Antibiotics Related to Clinician Perceptions,Management and Outcome? A Multi-Country Study in Outpatients with Acute Cough

Background

Outpatients with acute cough who expect, hope for or ask for antibiotics may be more unwell, benefit more from antibiotic treatment, and be more satisfied with care when they are prescribed antibiotics. Clinicians may not accurately identify those patients.

Objective

To explore whether patient views (expecting, hoping for or asking for antibiotics) are associated with illness presentation and resolution, whether patient views are accurately perceived by clinicians, and the association of all these factors with antibiotic prescribing and patient satisfaction with care.

Methods

Prospective observational study of 3402 adult patients with acute cough presenting in 14 primary care networks. Correlations and associations tested with multilevel logistic regression and McNemar ‘s tests, and Cohen’s Kappa, positive agreement (PA) and negative agreement (NA) calculated as appropriate.

Results

1,213 (45.1%) patients expected, 1,093 (40.6%) hoped for, and 275 (10.2%) asked for antibiotics. Clinicians perceived 840 (31.3%) as wanting to be prescribed antibiotics (McNemar’s test, p<0.05). Their perception agreed modestly with the three patient views (Kappa’s = 0.29, 0.32 and 0.21, PA’s = 0.56, 0.56 and 0.33, NA’s = 0.72, 0.75 and 0.82, respectively). 1,464 (54.4%) patients were prescribed antibiotics. Illness presentation and resolution were similar for patients regardless their views. These associations were not modified by antibiotic treatment. Patient expectation and hope (OR:2.08, 95% CI:[1.48,2.93] and 2.48 [1.73,3.55], respectively), and clinician perception (12.18 [8.31,17.84]) were associated with antibiotic prescribing. 2,354 (92.6%) patients were satisfied. Only those hoping for antibiotics were less satisfied when antibiotics were not prescribed (0.39 [0.17,0.90]).

Conclusion

Patient views about antibiotic treatment were not useful for identifying those who will benefit from antibiotics. Clinician perceptions did not match with patient views, but particularly influenced antibiotic prescribing. Patients were generally satisfied with care, but those hoping for but not prescribed antibiotics were less satisfied. Clinicians need to more effectively elicit and address patient views about antibiotics.     

Comparative glycan profiling of Ceratopteris richardii ‘C-Fern’ gametophytes and sporophytes links cell-wall composition to functional specialization

Background and Aims

Innovations in vegetative and reproductive characters were key factors in the evolutionary history of land plants and most of these transformations, including dramatic changes in life cycle structure and strategy, necessarily involved cell-wall modifications. To provide more insight into the role of cell walls in effecting changes in plant structure and function, and in particular their role in the generation of vascularization, an antibody-based approach was implemented to compare the presence and distribution of cell-wall glycan epitopes between (free-living) gametophytes and sporophytes of Ceratopteris richardii ‘C-Fern’, a widely used model system for ferns.

Methods

Microarrays of sequential diamino-cyclohexane-tetraacetic acid (CDTA) and NaOH extractions of gametophytes, spores and different organs of ‘C-Fern’ sporophytes were probed with glycan-directed monoclonal antibodies. The same probes were employed to investigate the tissue- and cell-specific distribution of glycan epitopes.

Key Results

While monoclonal antibodies against pectic homogalacturonan, mannan and xyloglucan widely labelled gametophytic and sporophytic tissues, xylans were only detected in secondary cell walls of the sporophyte. The LM5 pectic galactan epitope was restricted to sporophytic phloem tissue. Rhizoids and root hairs showed similarities in arabinogalactan protein (AGP) and xyloglucan epitope distribution patterns.

Conclusions

The differences and similarities in glycan cell-wall composition between ‘C-Fern’ gametophytes and sporophytes indicate that the molecular design of cell walls reflects functional specialization rather than genetic origin. Glycan epitopes that were not detected in gametophytes were associated with cell walls of specialized tissues in the sporophyte.     

The initial state of the human gut microbiome determines its reshaping by antibiotics

Microbiome studies have demonstrated the high inter-individual diversity of the gut microbiota. However, how the initial composition of the microbiome affects the impact of antibiotics on microbial communities is relatively unexplored. To specifically address this question, we administered a second-generation cephalosporin, cefprozil, to healthy volunteers. Stool samples gathered before antibiotic exposure, at the end of the treatment and 3 months later were analysed using shotgun metagenomic sequencing. On average, 15 billion nucleotides were sequenced for each sample. We show that standard antibiotic treatment can alter the gut microbiome in a specific, reproducible and predictable manner. The most consistent effect of the antibiotic was the increase of Lachnoclostridium bolteae in 16 out of the 18 cefprozil-exposed participants. Strikingly, we identified a subgroup of participants who were enriched in the opportunistic pathogen Enterobacter cloacae after exposure to the antibiotic, an effect linked to lower initial microbiome diversity and to a Bacteroides enterotype. Although the resistance gene content of participants'' microbiomes was altered by the antibiotic, the impact of cefprozil remained specific to individual participants. Resistance genes that were not detectable prior to treatment were observed after a 7-day course of antibiotic administration. Specifically, point mutations in beta-lactamase bla_CfxA-6 were enriched after antibiotic treatment in several participants. This suggests that monitoring the initial composition of the microbiome before treatment could assist in the prevention of some of the adverse effects associated with antibiotics or other treatments.     

Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology

Antibiotic resistance is a dire clinical problem with important ecological dimensions. While antibiotic resistance in human pathogens continues to rise at alarming rates, the impact of environmental resistance on human health is still unclear. To investigate the relationship between human-associated and environmental resistomes, we analyzed functional metagenomic selections for resistance against 18 clinically relevant antibiotics from soil and human gut microbiota as well as a set of multidrug-resistant cultured soil isolates. These analyses were enabled by Resfams, a new curated database of protein families and associated highly precise and accurate profile hidden Markov models, confirmed for antibiotic resistance function and organized by ontology. We demonstrate that the antibiotic resistance functions that give rise to the resistance profiles observed in environmental and human-associated microbial communities significantly differ between ecologies. Antibiotic resistance functions that most discriminate between ecologies provide resistance to β-lactams and tetracyclines, two of the most widely used classes of antibiotics in the clinic and agriculture. We also analyzed the antibiotic resistance gene composition of over 6000 sequenced microbial genomes, revealing significant enrichment of resistance functions by both ecology and phylogeny. Together, our results indicate that environmental and human-associated microbial communities harbor distinct resistance genes, suggesting that antibiotic resistance functions are largely constrained by ecology.     

Membrane-Active Macromolecules Resensitize NDM-1 Gram-Negative Clinical Isolates to Tetracycline Antibiotics

Gram-negative ‘superbugs’ such as New Delhi metallo-beta-lactamase-1 (bla _NDM-1) producing pathogens have become world’s major public health threats. Development of molecular strategies that can rehabilitate the ‘old antibiotics’ and halt the antibiotic resistance is a promising approach to target them. We report membrane-active macromolecules (MAMs) that restore the antibacterial efficacy (enhancement by >80-1250 fold) of tetracycline antibiotics towards bla _NDM-1 Klebsiella pneumonia and bla _NDM-1 Escherichia coli clinical isolates. Organismic studies showed that bacteria had an increased and faster uptake of tetracycline in the presence of MAMs which is attributed to the mechanism of re-sensitization. Moreover, bacteria did not develop resistance to MAMs and MAMs stalled the development of bacterial resistance to tetracycline. MAMs displayed membrane-active properties such as dissipation of membrane potential and membrane-permeabilization that enabled higher uptake of tetracycline in bacteria. In-vivo toxicity studies displayed good safety profiles and preliminary in-vivo antibacterial efficacy studies showed that mice treated with MAMs in combination with antibiotics had significantly decreased bacterial burden compared to the untreated mice. This report of re-instating the efficacy of the antibiotics towards bla _NDM-1 pathogens using membrane-active molecules advocates their potential for synergistic co-delivery of antibiotics to combat Gram-negative superbugs.