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"Peter, Silke"
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Distinct impact of antibiotics on the gut microbiome and resistome: a longitudinal multicenter cohort study
Background
The selection pressure exercised by antibiotic drugs is an important consideration for the wise stewardship of antimicrobial treatment programs. Treatment decisions are currently based on crude assumptions, and there is an urgent need to develop a more quantitative knowledge base that can enable predictions of the impact of individual antibiotics on the human gut microbiome and resistome.
Results
Using shotgun metagenomics, we quantified changes in the gut microbiome in two cohorts of hematological patients receiving prophylactic antibiotics; one cohort was treated with ciprofloxacin in a hospital in Tübingen and the other with cotrimoxazole in a hospital in Cologne. Analyzing this rich longitudinal dataset, we found that gut microbiome diversity was reduced in both treatment cohorts to a similar extent, while effects on the gut resistome differed. We observed a sharp increase in the relative abundance of sulfonamide antibiotic resistance genes (ARGs) by 148.1% per cumulative defined daily dose of cotrimoxazole in the Cologne cohort, but not in the Tübingen cohort treated with ciprofloxacin. Through multivariate modeling, we found that factors such as individual baseline microbiome, resistome, and plasmid diversity; liver/kidney function; and concurrent medication, especially virostatic agents, influence resistome alterations. Strikingly, we observed different effects on the plasmidome in the two treatment groups. There was a substantial increase in the abundance of ARG-carrying plasmids in the cohort treated with cotrimoxazole, but not in the cohort treated with ciprofloxacin, indicating that cotrimoxazole might contribute more efficiently to the spread of resistance.
Conclusions
Our study represents a step forward in developing the capability to predict the effect of individual antimicrobials on the human microbiome and resistome. Our results indicate that to achieve this, integration of the individual baseline microbiome, resistome, and mobilome status as well as additional individual patient factors will be required. Such personalized predictions may in the future increase patient safety and reduce the spread of resistance.
Trial registration
ClinicalTrials.gov,
NCT02058888
. Registered February 10 2014
Journal Article
Translational metagenomics and the human resistome: confronting the menace of the new millennium
The increasing threat of antimicrobial resistance poses one of the greatest challenges to modern medicine. The collection of all antimicrobial resistance genes carried by various microorganisms in the human body is called the human resistome and represents the source of resistance in pathogens that can eventually cause life-threatening and untreatable infections. A deep understanding of the human resistome and its multilateral interaction with various environments is necessary for developing proper measures that can efficiently reduce the spread of resistance. However, the human resistome and its evolution still remain, for the most part, a mystery to researchers. Metagenomics, particularly in combination with next-generation-sequencing technology, provides a powerful methodological approach for studying the human microbiome as well as the pathogenome, the virolume and especially the resistome. We summarize below current knowledge on how the human resistome is shaped and discuss how metagenomics can be employed to improve our understanding of these complex processes, particularly as regards a rapid translation of new findings into clinical diagnostics, infection control and public health.
Journal Article
Genomic characterisation of clinical and environmental Pseudomonas putida group strains and determination of their role in the transfer of antimicrobial resistance genes to Pseudomonas aeruginosa
Background
Pseudomonas putida
is a Gram-negative, non-fermenting bacterium frequently encountered in various environmental niches.
P. putida
rarely causes disease in humans, though serious infections and outbreaks have been reported from time to time. Some have suggested that
P. putida
functions as an exchange platform for antibiotic resistance genes (ARG), and thus represents a serious concern in the spread of ARGs to more pathogenic organisms within a hospital. Though poorly understood, the frequency of ARG exchange between
P. putida
and the more virulent
Pseudomonas aeruginosa
and its clinical relevance are particularly important for designing efficient infection control strategies, such as deciding whether high-risk patients colonized with a multidrug resistant but typically low pathogenic
P. putida
strain should be contact isolated or not.
Results
In this study, 21,373 screening samples (stool, rectal and throat swab) were examined to determine the presence of
P. putida
in a high-risk group of haemato-oncology patients during a 28-month period. A total of 89
P. putida
group strains were isolated from 85 patients, with 41 of 89 (46.1%) strains harbouring the metallo-beta-lactamase gene
bla
VIM
. These 41 clinical isolates, plus 18
bla
VIM
positive environmental
P. putida
isolates, and 17
bla
VIM
positive
P. aeruginosa
isolates, were characterized by whole genome sequencing (WGS).
We constructed a maximum-likelihood tree to separate the 59
bla
VIM
positive
P. putida
group strains into eight distinct phylogenetic clusters.
Bla
VIM-1
was present in 6 clusters while
bla
VIM-2
was detected in 4 clusters. Five
P. putida
group strains contained both,
bla
VIM-1
and
bla
VIM-2
genes.
In contrast, all
P. aeruginosa
strains belonged to a single genetic cluster and contained the same ARGs. Apart from
bla
VIM-2
and
sul
genes, no other ARGs were shared between
P. aeruginosa
and
P. putida
. Furthermore, the
bla
VIM-2
gene in
P. aeruginosa
was predicted to be only chromosomally located.
Conclusion
These data provide evidence that no exchange of comprehensive ARG harbouring mobile genetic elements had occurred between
P. aeruginosa
and
P. putida group
strains during the study period, thus eliminating the need to implement enhanced infection control measures for high-risk patients colonized with a
bla
VIM
positiv
P. putida
group strains in our clinical setting.
Journal Article
Evaluation of two rapid molecular test systems to establish an algorithm for fast identification of bacterial pathogens from positive blood cultures
Fast identification of pathogens directly from positive blood cultures is of highest importance to supply an adequate therapy of bloodstream infections (BSI). There are several platforms providing molecular-based identification, detection of antimicrobial resistance genes, or even a full antimicrobial susceptibility testing (AST). Two of such test systems allowing rapid diagnostics were assessed in this study: The Biofire FilmArray® and the Genmark ePlex®, both fully automated test system with a minimum of hands-on time. Overall 137 BSI episodes were included in our study and compared to conventional culture–based reference methods. The FilmArray® is using one catridge including a panel for the most common bacterial and fungal BSI pathogens as well as selected resistance markers. The ePlex® offers three different cartridges for detection of Gram-positives, Gram-negatives, and fungi resulting in a broader panel including also rare pathogens, putative contaminants, and more genetic resistance markers. The FilmArray® and ePlex® were evaluated for all 137 BSI episodes with FilmArray® detecting 119 and ePlex® detecting 128 of these. For targets on the respective panel of the system, the FilmArray® generated a sensitivity of 98.9% with 100% specificity on Gram-positive isolates. The ePlex® system generated a sensitivity of 94.7% and a specificity of 90.7% on Gram-positive isolates. In each case, the two systems performed with 100% sensitivity and specificity for the detection of Gram-negative specimens covered by each panel. In summary, both evaluated test systems showed a satisfying overall performance for fast pathogen identification and are beneficial tools for accelerating blood culture diagnostics of sepsis patients.
Journal Article
OXA-48-like carbapenemases in Proteus mirabilis – novel genetic environments and a challenge for detection
OXA-48-like enzymes represent the most frequently detected carbapenemases in Enterobacterales in Western Europe, North Africa and the Middle East. In contrast to other species, the presence of OXA-48-like in
leads to an unusually susceptible phenotype with low MICs for carbapenems and piperacillin-tazobactam, which is easily missed in the diagnostic laboratory. So far, there is little data available on the genetic environments of the corresponding genes,
-like, in
In this study susceptibility phenotypes and genomic data of 13 OXA-48-like-producing
were investigated (OXA-48,
= 9; OXA-181,
= 3; OXA-162,
= 1). Ten isolates were susceptible to meropenem and ertapenem and three isolates were susceptible to piperacillin-tazobactam. The gene
was chromosomally located in 7/9 isolates. Thereof, in three isolates
was inserted into a
genomic island. Of the three isolates harbouring
one was located on an IncX3 plasmid and two were located on a novel MOB
plasmid, pOXA-P12, within the new transposon Tn
. In 5/6 isolates with plasmidic location of
like, the plasmids could conjugate to
recipients
.
,
-carrying plasmids could conjugate from other Enterobacterales into a
recipient. These data show a high diversity of
-like genetic environments compared to other Enterobacterales, where genetic environments are quite homogenous. Given the difficult-to-detect phenotype of OXA-48-like-producing
and the location of
-like on mobile genetic elements
it is likely that OXA-48-like-producing
can disseminate, escape most surveillance systems, and contribute to a hidden spread of OXA-48-like.
Journal Article
Prognostic Value of Gut Microbiome for Conversion from Mild Cognitive Impairment to Alzheimer’s Disease Dementia within 4 Years: Results from the AlzBiom Study
Alterations in the gut microbiome are associated with the pathogenesis of Alzheimer’s disease (AD) and can be used as a diagnostic measure. However, longitudinal data of the gut microbiome and knowledge about its prognostic significance for the development and progression of AD are limited. The aim of the present study was to develop a reliable predictive model based on gut microbiome data for AD development. In this longitudinal study, we investigated the intestinal microbiome in 49 mild cognitive impairment (MCI) patients over a mean (SD) follow-up of 3.7 (0.6) years, using shotgun metagenomics. At the end of the 4-year follow-up (4yFU), 27 MCI patients converted to AD dementia and 22 MCI patients remained stable. The best taxonomic model for the discrimination of AD dementia converters from stable MCI patients included 24 genera, yielding an area under the receiver operating characteristic curve (AUROC) of 0.87 at BL, 0.92 at 1yFU and 0.95 at 4yFU. The best models with functional data were obtained via analyzing 25 GO (Gene Ontology) features with an AUROC of 0.87 at BL, 0.85 at 1yFU and 0.81 at 4yFU and 33 KO [Kyoto Encyclopedia of Genes and Genomes (KEGG) ortholog] features with an AUROC of 0.79 at BL, 0.88 at 1yFU and 0.82 at 4yFU. Using ensemble learning for these three models, including a clinical model with the four parameters of age, gender, body mass index (BMI) and Apolipoprotein E (ApoE) genotype, yielded an AUROC of 0.96 at BL, 0.96 at 1yFU and 0.97 at 4yFU. In conclusion, we identified novel and timely stable gut microbiome algorithms that accurately predict progression to AD dementia in individuals with MCI over a 4yFU period.
Journal Article
Prognostic Value of a Multivariate Gut Microbiome Model for Progression from Normal Cognition to Mild Cognitive Impairment Within 4 Years
Little is known about the dysbiosis of the gut microbiome in patients with mild cognitive impairment (MCI) potentially at risk for the development of Alzheimer’s disease (AD). So far, only cross-sectional differences and not longitudinal changes and their prognostic significance have been in the scope of research in MCI. Therefore, we investigated the ability of longitudinal taxonomic and functional gut microbiome data from 100 healthy controls (HC) to predict the progression from normal cognition to MCI over a 4-year follow-up period (4yFU). Logistic regression models were built with baseline features that best discriminated between the two groups using an ANOVA-type statistical analysis. The best model for the discrimination of MCI converters was based on functional data using Gene Ontology (GO), which included 14 features. This model achieved an area under the receiver operating characteristic curve (AUROC) of 0.84 at baseline, 0.78 at the 1-year follow-up (1yFU), and 0.75 at 4yFU. This functional model outperformed the taxonomic model, which included 38 genera features, in terms of descriptive performance and showed comparable efficacy to combined analyses integrating functional, taxonomic, and clinical characteristics. Thus, gut microbiome algorithms have the potential to predict MCI conversion in HCs over a 4-year period, offering a promising innovative supplement for early AD identification.
Journal Article
Resolving colistin resistance and heteroresistance in Enterobacter species
Species within the
Enterobacter cloacae
complex (ECC) include globally important nosocomial pathogens. A three-year study of ECC in Germany identified
Enterobacter xiangfangensis
as the most common species (65.5%) detected, a result replicated by examining a global pool of 3246 isolates. Antibiotic resistance profiling revealed widespread resistance and heteroresistance to the antibiotic colistin and detected the mobile colistin resistance (
mcr
)−9 gene in 19.2% of all isolates. We show that resistance and heteroresistance properties depend on the chromosomal
arnBCADTEF
gene cassette whose products catalyze transfer of L-Ara4N to lipid A. Using comparative genomics, mutational analysis, and quantitative lipid A profiling we demonstrate that intrinsic lipid A modification levels are genospecies-dependent and governed by allelic variations in
phoPQ
and
mgrB
, that encode a two-component sensor-activator system and specific inhibitor peptide. By generating
phoPQ
chimeras and combining them with
mgrB
alleles, we show that interactions at the pH-sensing interface of the sensory histidine kinase
phoQ
dictate
arnBCADTEF
expression levels. To minimize therapeutic failures, we developed an assay that accurately detects colistin resistance levels for any ECC isolate.
Taxonomical complexity has muddled the classification of clinically relevant
Enterobacter
species. Authors carry out a genome-based study on clinical isolates to investigate colistin resistance and heteroresistance in
Enterobacter
.
Journal Article
Metabolic mutations reduce antibiotic susceptibility of E. coli by pathway-specific bottlenecks
Metabolic variation across pathogenic bacterial strains can impact their susceptibility to antibiotics and promote the evolution of antimicrobial resistance (AMR). However, little is known about how metabolic mutations influence metabolism and which pathways contribute to antibiotic susceptibility. Here, we measured the antibiotic susceptibility of 15,120
Escherichia coli
mutants, each with a single amino acid change in one of 346 essential proteins. Across all mutants, we observed modest increases of the minimal inhibitory concentration (twofold to tenfold) without any cases of major resistance. Most mutants that showed reduced susceptibility to either of the two tested antibiotics carried mutations in metabolic genes. The effect of metabolic mutations on antibiotic susceptibility was antibiotic- and pathway-specific: mutations that reduced susceptibility against the β-lactam antibiotic carbenicillin converged on purine nucleotide biosynthesis, those against the aminoglycoside gentamicin converged on the respiratory chain. In addition, metabolic mutations conferred tolerance to carbenicillin by reducing growth rates. These results, along with evidence that metabolic bottlenecks are common among clinical
E. coli
isolates, highlight the contribution of metabolic mutations for AMR.
Synopsis
A CRISPR screen and metabolomics reveal that metabolic mutations in
E. coli
create pathway-specific bottlenecks that reduce antibiotic susceptibility, demonstrating that bacterial metabolism plays a role in antimicrobial resistance and tolerance.
A CRISPR library was screened against two antibiotics.
Resistance mutations were enriched in metabolic genes.
Metabolic mutations caused bottlenecks in their pathways.
Clinical
E. coli
exhibited similar metabolic bottlenecks.
A CRISPR screen and metabolomics reveal that metabolic mutations in
E. coli
create pathway-specific bottlenecks that reduce antibiotic susceptibility, demonstrating that bacterial metabolism plays a role in antimicrobial resistance and tolerance.
Journal Article