Long-term ecological and evolutionary dynamics in the gut microbiomes of carbapenemase-producing Enterobacteriaceae colonized subjects

Gut community structure as a risk factor for infection in Klebsiella pneumoniae-colonized patients

The primary risk factor for infection with members of the Klebsiella pneumoniae species complex is prior gut colonization, and infection is often caused by the colonizing strain. Despite the importance of the gut as a reservoir for infectious K. pneumoniae, little is known about the association between the gut microbiome and infection. To explore this relationship, we undertook a case-control study comparing the gut community structure of K. pneumoniae-colonized intensive care and hematology/oncology patients. Cases were K. pneumoniae-colonized patients infected by their colonizing strain (N = 83). Controls were K. pneumoniae-colonized patients who remained asymptomatic (N = 149). First, we characterized the gut community structure of K. pneumoniae-colonized patients agnostic to case status. Next, we determined that gut community data is useful for classifying cases and controls using machine learning models and that the gut community structure differed between cases and controls. K. pneumoniae relative abundance, a known risk factor for infection, had the greatest feature importance, but other gut microbes were also informative. Finally, we show that integration of gut community structure with bacterial genotype data enhanced the ability of machine learning models to discriminate cases and controls. Interestingly, inclusion of patient clinical variables failed to improve the ability of machine learning models to discriminate cases and controls. This study demonstrates that including gut community data with K. pneumoniae-derived biomarkers improves our ability to classify infection in K. pneumoniae-colonized patients.IMPORTANCEColonization is generally the first step in pathogenesis for bacteria with pathogenic potential. This step provides a unique window for intervention since a given potential pathogen has yet to cause damage to its host. Moreover, intervention during the colonization stage may help alleviate the burden of therapy failure as antimicrobial resistance rises. Yet, to understand the therapeutic potential of interventions that target colonization, we must first understand the biology of colonization and if biomarkers at the colonization stage can be used to stratify infection risk. The bacterial genus Klebsiella includes many species with varying degrees of pathogenic potential. Members of the K. pneumoniae species complex have the highest pathogenic potential. Patients colonized in their gut by these bacteria are at higher risk of subsequent infection with their colonizing strain. However, we do not understand if other members of the gut microbiota can be used as a biomarker to predict infection risk. In this study, we show that the gut microbiota differs between colonized patients who develop an infection versus those who do not. Additionally, we show that integrating gut microbiota data with bacterial factors improves the ability to classify infections. Surprisingly, patient clinical factors were not useful for classifying infections alone or when added to microbiota-based models. This indicates that the bacterial genotype and the microbial community in which it exists may determine the progression to infection. As we continue to explore colonization as an intervention point to prevent infections in individuals colonized by potential pathogens, we must develop effective means for predicting and stratifying infection risk.

The Effect of Antibiotics on the Eradication of Multidrug-Resistant Organisms in Intestinal Carriers-A Systematic Review with Meta-Analysis

OBJECTIVES

The aim of this systematic review was to investigate the effect of antibiotics on the eradication of multidrug-resistant organisms (MRO) in intestinal carriers. We defined multidrug-resistant organisms as vancomycin-resistant Enterococcus faecium (VREfm), and multidrug-resistant Gram-negative Enterobacterales. Methods: We searched the EMBASE, Cochrane Central, and PubMed databases from inception to medio November 2023. We included randomised and controlled clinical trials (RCTs), that investigated the effect of antibiotics on the eradication of multidrug-resistant organisms in intestinal carriers. Finally, we performed a meta-analysis.

RESULTS

We included five RTCs in the systematic review. In four studies an effect of antibiotics on the eradication of MRO was shown at the end of intervention, but it was not sustained at follow-up. In the fifth study, the effect at the end of intervention was not reported, and there was no observed effect of the intervention at follow-up. We included four studies in the meta-analysis, and it suggests an effect of antibiotics on the eradication of MRO in intestinal carriers at the end of follow-up with a p-value of 0.04 (95% confidence interval 1.02-1.95). None of the studies reported a significant increase in resistance to the study drug. Gastrointestinal disorders were the most frequent non-severe adverse event.

CONCLUSIONS

The effect of antibiotics on the eradication of multidrug-resistant organisms in intestinal carriers was not statistically significant in any of the five included studies; however, we found a significant effect in the pooled meta-analysis. As the confidence interval is large, we cannot determine the clinical importance of this finding, and it should be further investigated.

Quantifying compositional variability in microbial communities with FAVA

Microbial communities vary across space, time, and individual hosts, presenting new challenges for the development of statistics measuring the variability of community composition. To understand differences across microbiome samples from different host individuals, sampling times, spatial locations, or experimental replicates, we present FAVA, a new normalized measure for characterizing compositional variability across multiple microbiome samples. FAVA quantifies variability across many samples of taxonomic or functional relative abundances in a single index ranging between 0 and 1, equaling 0 when all samples are identical and equaling 1 when each sample is entirely comprised of a single taxon. Its definition relies on the population-genetic statisticF S T , with samples playing the role of "populations" and taxa playing the role of "alleles." Its convenient mathematical properties allow users to compare disparate data sets. For example, FAVA values are commensurable across different numbers of taxonomic categories and different numbers of samples considered. We introduce extensions that incorporate phylogenetic similarity among taxa and spatial or temporal distances between samples. We illustrate how FAVA can be used to describe across-individual taxonomic variability in ruminant microbiomes at different regions along the gastrointestinal tract. In a second example, a longitudinal analysis of gut microbiomes of healthy human adults taking an antibiotic, we use FAVA to quantify the increase in temporal variability of microbiomes following the antibiotic course and to measure the duration of the antibiotic's influence on microbial variability. We have implemented this tool in an R package, FAVA, which can fit easily into existing pipelines for the analysis of microbial relative abundances.

Short-chain fatty acids of various lengths differentially inhibit Klebsiella pneumoniae and Enterobacteriaceae species

The gut microbiota is inextricably linked to human health and disease. It can confer colonization resistance against invading pathogens either through niche occupation and nutrient competition or via its secreted metabolites. Short-chain fatty acids (SCFA) are the primary metabolites in the gut as a result of dietary fiber fermentation by the gut microbiota. In this work, we demonstrate that the interaction of single-species gut commensals on solid media is insufficient for pathogen inhibition, but supernatants from monocultures of these commensal bacteria enriched in acetate confer inhibition against anaerobic growth of the enteric pathogen Klebsiella pneumoniae. The three primary SCFAs (acetate, propionate, and butyrate) strongly inhibit the intestinal commensal Escherichia coli Nissle as well as a panel of enteric pathogens besides K. pneumoniae at physiological pH of the cecum and ascending colon. This inhibition was significantly milder on anaerobic gut commensals Bacteroides thetaiotaomicron and Bifidobacterium adolescentis previously demonstrated to be associated with microbiota recovery after antibiotic-induced dysbiosis. We describe a general suppression of bacterial membrane potential by these SCFAs at physiological cecum and ascending colonic pH. Furthermore, the strength of bacterial inhibition increases with increasing alkyl chain length. Overall, the insights gained in this study shed light on the potential therapeutic use of SCFAs for conferring colonization resistance against invading pathogens in a dysbiotic gut.IMPORTANCERising antimicrobial resistance has made treatment of bacterial infections increasingly difficult. According to the World Health Organization, it has become a burgeoning threat to hospital and public health systems worldwide. This threat is largely attributed to the global rise of carbapenem-resistant Enterobacteriaceae in recent years, with common hospital-acquired pathogens growing increasingly resistant to last-line antibiotics. Antibiotics disrupt the homeostatic balance of the gut microbiota, resulting in the loss of colonization resistance against enteric pathogens. This work describes the ability of short-chain fatty acids (SCFAs) produced by gut microbiota to be effective against a wide panel of enteric pathogens without major impact on common gut commensal species. We also demonstrate a previously undescribed link between alkyl chain length and antibacterial effects of SCFAs. SCFAs, thus, hold promise as an alternative therapeutic option leveraging on the antimicrobial activity of these endogenously produced gut metabolites without disrupting gut microbiota homeostasis.

Hierarchical eco-evo dynamics mediated by the gut microbiome

The concept of eco-evolutionary (eco-evo) dynamics, stating that ecological and evolutionary processes occur at similar time scales and influence each other, has contributed to our understanding of responses of populations, communities, and ecosystems to environmental change. Phenotypes, central to these eco-evo processes, can be strongly impacted by the gut microbiome. The gut microbiome shapes eco-evo dynamics in the host community through its effects on the host phenotype. Complex eco-evo feedback loops between the gut microbiome and the host communities might thus be common. Bottom-up dynamics occur when eco-evo interactions shaping the gut microbiome affect host phenotypes with consequences at population, community, and ecosystem levels. Top-down dynamics occur when eco-evo dynamics shaping the host community structure the gut microbiome.

Antibiotics promote intestinal growth of carbapenem-resistant Enterobacteriaceae by enriching nutrients and depleting microbial metabolites

The intestine is the primary colonisation site for carbapenem-resistant Enterobacteriaceae (CRE) and serves as a reservoir of CRE that cause invasive infections (e.g. bloodstream infections). Broad-spectrum antibiotics disrupt colonisation resistance mediated by the gut microbiota, promoting the expansion of CRE within the intestine. Here, we show that antibiotic-induced reduction of gut microbial populations leads to an enrichment of nutrients and depletion of inhibitory metabolites, which enhances CRE growth. Antibiotics decrease the abundance of gut commensals (including Bifidobacteriaceae and Bacteroidales) in ex vivo cultures of human faecal microbiota; this is accompanied by depletion of microbial metabolites and enrichment of nutrients. We measure the nutrient utilisation abilities, nutrient preferences, and metabolite inhibition susceptibilities of several CRE strains. We find that CRE can use the nutrients (enriched after antibiotic treatment) as carbon and nitrogen sources for growth. These nutrients also increase in faeces from antibiotic-treated mice and decrease following intestinal colonisation with carbapenem-resistant Escherichia coli. Furthermore, certain microbial metabolites (depleted upon antibiotic treatment) inhibit CRE growth. Our results show that killing gut commensals with antibiotics facilitates CRE colonisation by enriching nutrients and depleting inhibitory microbial metabolites.

Comparative Genomic Analysis of Hypervirulence Carbapenem-Resistant Klebsiella pneumoniae from Inpatients with Infection and Gut Colonization, China

Background

The emergence and spread of hypervirulent carbapenem-resistant Klebsiella pneumoniae (hv-CRKP) is a potential epidemiological threat that needs to be monitored. However, the transmission and pathogenic characteristics of hv-CRKP in China remain unclear. We investigated the epidemiological characteristics of gut colonized hv-CRKP in a hospital in Guangdong Province, China.

Methods

A total of 46 gut colonized hv-CRKP isolates were collected from Sun Yat-Sen Memorial Hospital (Guangzhou, China) from August 31st to December 31st, 2021. Minimum inhibitory concentrations (MICs) were obtained for 15 antibiotics for 46 hv-CRKP isolates. BALB/C mice infection model and mucoviscosity assay was used to evaluate the virulence of the isolates. The characteristics of genome, phylogenetic relationship and the structure of the plasmid of 46 gut colonized hv-CRKP isolates were compared with pathogenic isolates from GeneBank based on whole-genome data.

Results

The hv-CRKP isolation rate of all gut colonized carbapenem-resistant Klebsiella pneumoniae was 17% (46/270), and the intestinal colonization rate of hv-CRKP was irrelevant to the sex, age, department of hospitalization, and history of antibiotic use of the host. The gut colonized hv-CRKP showed pandrug resistance and hypervirulence. The gut colonized hv-CRKP and pathogenic hv-CRKP prevalent in China were mainly ST11 hv-CRKP and had two major epidemic clades. The similarities in genomic characteristics between gut colonized hv-CRKP and pathogenic hv-CRKP were consistent. The gut colonized hv-CRKP carried an incomplete structure pK2044 virulence plasmid from hypervirulent K. pneumoniae NTUH-K2044 by analyzing the virulence plasmid structure.

Conclusion

Our results suggest that the gut colonized ST11 hv-CRKP may serve as a reservoir for the clinical pathogenic ST11 HV-CRKP. It is necessary to further strengthen the monitoring of gut colonized hv-CRKP and research the potential mechanism of infection caused by gut colonized hv-CRKP.

Gut community structure as a risk factor for infection in Klebsiella -colonized patients

The primary risk factor for infection with members of the Klebsiella pneumoniae species complex is prior gut colonization, and infection is often caused by the colonizing strain. Despite the importance of the gut as a reservoir for infectious Klebsiella , little is known about the association between the gut microbiome and infection. To explore this relationship, we undertook a case-control study comparing the gut community structure of Klebsiella -colonized intensive care and hematology/oncology patients. Cases were Klebsiella -colonized patients infected by their colonizing strain (N = 83). Controls were Klebsiella -colonized patients that remained asymptomatic (N = 149). First, we characterized the gut community structure of Klebsiella -colonized patients agnostic to case status. Next, we determined that gut community data is useful for classifying cases and controls using machine learning models and that the gut community structure differed between cases and controls. Klebsiella relative abundance, a known risk factor for infection, had the greatest feature importance but other gut microbes were also informative. Finally, we show that integration of gut community structure with bacterial genotype or clinical variable data enhanced the ability of machine learning models to discriminate cases and controls. This study demonstrates that including gut community data with patient- and Klebsiella -derived biomarkers improves our ability to predict infection in Klebsiella -colonized patients.

Importance

Colonization is generally the first step in pathogenesis for bacteria with pathogenic potential. This step provides a unique window for intervention since a given potential pathogen has yet to cause damage to its host. Moreover, intervention during the colonization stage may help alleviate the burden of therapy failure as antimicrobial resistance rises. Yet, to understand the therapeutic potential of interventions that target colonization, we must first understand the biology of colonization and if biomarkers at the colonization stage can be used to stratify infection risk. The bacterial genus Klebsiella includes many species with varying degrees of pathogenic potential. Members of the K. pneumoniae species complex have the highest pathogenic potential. Patients colonized in their gut by these bacteria are at higher risk of subsequent infection with their colonizing strain. However, we do not understand if other members of the gut microbiota can be used as a biomarker to predict infection risk. In this study, we show that the gut microbiota differs between colonized patients that develop an infection versus those that do not. Additionally, we show that integrating gut microbiota data with patient and bacterial factors improves the ability to predict infections. As we continue to explore colonization as an intervention point to prevent infections in individuals colonized by potential pathogens, we must develop effective means for predicting and stratifying infection risk.

Antimicrobial Resistance in the Global Health Network: Known Unknowns and Challenges for Efficient Responses in the 21st Century

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.

Strain-specific alterations in gut microbiome and host immune responses elicited by tolerogenic Bifidobacterium pseudolongum

The beneficial effects attributed to Bifidobacterium are largely attributed to their immunomodulatory capabilities, which are likely to be species- and even strain-specific. However, their strain-specificity in direct and indirect immune modulation remain largely uncharacterized. We have shown that B. pseudolongum UMB-MBP-01, a murine isolate strain, is capable of suppressing inflammation and reducing fibrosis in vivo. To ascertain the mechanism driving this activity and to determine if it is specific to UMB-MBP-01, we compared it to a porcine tropic strain B. pseudolongum ATCC25526 using a combination of cell culture and in vivo experimentation and comparative genomics approaches. Despite many shared features, we demonstrate that these two strains possess distinct genetic repertoires in carbohydrate assimilation, differential activation signatures and cytokine responses signatures in innate immune cells, and differential effects on lymph node morphology with unique local and systemic leukocyte distribution. Importantly, the administration of each B. pseudolongum strain resulted in major divergence in the structure, composition, and function of gut microbiota. This was accompanied by markedly different changes in intestinal transcriptional activities, suggesting strain-specific modulation of the endogenous gut microbiota as a key to immune modulatory host responses. Our study demonstrated a single probiotic strain can influence local, regional, and systemic immunity through both innate and adaptive pathways in a strain-specific manner. It highlights the importance to investigate both the endogenous gut microbiome and the intestinal responses in response to probiotic supplementation, which underpins the mechanisms through which the probiotic strains drive the strain-specific effect to impact health outcomes.