Intestinal carbapenem-resistant Klebsiella pneumoniae undergoes complex transcriptional reprogramming following immune activation.

Carbapenem-resistant Klebsiella pneumoniae (CR-Kp) is a significant threat to public health worldwide. The primary reservoir for CR-Kp is the intestinal tract. There, the bacterium is usually present at low density but can bloom following antibiotic treatment, mostly in hospital settings. The impact of disturbances in the intestinal environment on the fitness, survival, expansion, and drug susceptibility of this pathogen is not well-understood, yet it may be relevant to devise strategies to tackle CR-Kp colonization and infection. Here, we adopted an in vivo model to examine the transcriptional adaptation of a CR-Kp clinical isolate to immune activation in the intestine. We report that as early as 6 hours following host treatment with anti-CD3 antibody, CR-Kp underwent rapid transcriptional changes including downregulation of genes involved in sugar utilization and amino acid biosynthesis and upregulation of genes involved in amino acid uptake and catabolism, antibiotic resistance, and stress response. In agreement with these findings, treatment increased the concentration of oxidative species and amino acids in the mouse intestine. Genes encoding for proteins containing the domain of unknown function (DUF) 1471 were strongly upregulated, however their deletion did not impair CR-Kp fitness in vivo upon immune activation. Transcription factor enrichment analysis identified the global regulator cAMP-Receptor Protein, CRP, as a potential orchestrator of the observed transcriptional signature. In keeping with the recognized role of CRP in regulating utilization of alternative carbon sources, crp deletion in CR-Kp resulted in strongly impaired gut colonization, although this effect was not amplified by immune activation. Thus, following intestinal colonization, which occurs in a CRP-dependent manner, CR-Kp can rapidly respond to immune cues by implementing a well-defined and complex transcriptional program whose direct relevance toward bacterial fitness warrants further investigation. Additional analyses utilizing this model may identify key factors to tackle CR-Kp colonization of the intestine.

Comprehensive analyses of a large human gut Bacteroidales culture collection reveal species and strain level diversity and evolution.

Species of the Bacteroidales order are among the most abundant and stable bacterial members of the human gut microbiome with diverse impacts on human health. While Bacteroidales strains and species are genomically and functionally diverse, order-wide comparative analyses are lacking. We cultured and sequenced the genomes of 408 Bacteroidales isolates from healthy human donors representing nine genera and 35 species and performed comparative genomic, gene-specific, mobile gene, and metabolomic analyses. Families, genera, and species could be grouped based on many distinctive features. However, we also show extensive DNA transfer between diverse families, allowing for shared traits and strain evolution. Inter- and intra-specific diversity is also apparent in the metabolomic profiling studies. This highly characterized and diverse Bacteroidales culture collection with strain-resolved genomic and metabolomic analyses can serve as a resource to facilitate informed selection of strains for microbiome reconstitution.

Dietary- and host-derived metabolites are used by diverse gut bacteria for anaerobic respiration.

Respiratory reductases enable microorganisms to use molecules present in anaerobic ecosystems as energy-generating respiratory electron acceptors. Here we identify three taxonomically distinct families of human gut bacteria (Burkholderiaceae, Eggerthellaceae and Erysipelotrichaceae) that encode large arsenals of tens to hundreds of respiratory-like reductases per genome. Screening species from each family (Sutterella wadsworthensis, Eggerthella lenta and Holdemania filiformis), we discover 22 metabolites used as respiratory electron acceptors in a species-specific manner. Identified reactions transform multiple classes of dietary- and host-derived metabolites, including bioactive molecules resveratrol and itaconate. Products of identified respiratory metabolisms highlight poorly characterized compounds, such as the itaconate-derived 2-methylsuccinate. Reductase substrate profiling defines enzyme-substrate pairs and reveals a complex picture of reductase evolution, providing evidence that reductases with specificities for related cinnamate substrates independently emerged at least four times. These studies thus establish an exceptionally versatile form of anaerobic respiration that directly links microbial energy metabolism to the gut metabolome.

Activity of Gut-Derived Nisin-like Lantibiotics against Human Gut Pathogens and Commensals.

Recent advances in sequencing techniques unveiled the vast potential of ribosomally synthesized and post-translationally modified peptides (RiPPs) encoded in microbiomes. Class I lantibiotics such as nisin A, widely used as a food preservative, have been investigated for their efficacy in killing pathogens. However, the impact of nisin and nisin-like class I lantibiotics on commensal bacteria residing in the human gut remains unclear. Here, we report six gut-derived class I lantibiotics that are close homologues of nisin, four of which are novel. We applied an improved lantibiotic expression platform to produce and purify these lantibiotics for antimicrobial assays. We determined their minimal inhibitory concentration (MIC) against both Gram-positive human pathogens and gut commensals and profiled the lantibiotic resistance genes in these pathogens and commensals. Structure-activity relationship (SAR) studies with analogs revealed key regions and residues that impact their antimicrobial properties. Our characterization and SAR studies of nisin-like lantibiotics against both pathogens and human gut commensals could shed light on the future development of lantibiotic-based therapeutics and food preservatives.

Fecal metabolite profiling identifies liver transplant recipients at risk for postoperative infection.

Metabolites produced by the intestinal microbiome modulate mucosal immune defenses and optimize epithelial barrier function. Intestinal dysbiosis, including loss of intestinal microbiome diversity and expansion of antibiotic-resistant pathobionts, is accompanied by changes in fecal metabolite concentrations and increased incidence of systemic infection. Laboratory tests that quantify intestinal dysbiosis, however, have yet to be incorporated into clinical practice. We quantified fecal metabolites in 107 patients undergoing liver transplantation (LT) and correlated these with fecal microbiome compositions, pathobiont expansion, and postoperative infections. Consistent with experimental studies implicating microbiome-derived metabolites with host-mediated antimicrobial defenses, reduced fecal concentrations of short- and branched-chain fatty acids, secondary bile acids, and tryptophan metabolites correlate with compositional microbiome dysbiosis in LT patients and the relative risk of postoperative infection. Our findings demonstrate that fecal metabolite profiling can identify LT patients at increased risk of postoperative infection and may provide guideposts for microbiome-targeted therapies.

An evolution-based framework for describing human gut bacteria.

The human gut microbiome contains many bacterial strains of the same species ('strain-level variants'). Describing strains in a biologically meaningful way rather than purely taxonomically is an important goal but challenging due to the genetic complexity of strain-level variation. Here, we measured patterns of co-evolution across >7,000 strains spanning the bacterial tree-of-life. Using these patterns as a prior for studying hundreds of gut commensal strains that we isolated, sequenced, and metabolically profiled revealed widespread structure beneath the phylogenetic level of species. Defining strains by their co-evolutionary signatures enabled predicting their metabolic phenotypes and engineering consortia from strain genome content alone. Our findings demonstrate a biologically relevant organization to strain-level variation and motivate a new schema for describing bacterial strains based on their evolutionary history.

Bifidobacteria metabolize lactulose to optimize gut metabolites and prevent systemic infection in patients with liver disease.

Progression of chronic liver disease is precipitated by hepatocyte loss, inflammation and fibrosis. This process results in the loss of critical hepatic functions, increasing morbidity and the risk of infection. Medical interventions that treat complications of hepatic failure, including antibiotic administration for systemic infections and lactulose treatment for hepatic encephalopathy, can impact gut microbiome composition and metabolite production. Here, using shotgun metagenomic sequencing and targeted metabolomic analyses on 847 faecal samples from 262 patients with acute or chronic liver disease, we demonstrate that patients hospitalized for liver disease have reduced microbiome diversity and a paucity of bioactive metabolites, including short-chain fatty acids and bile acid derivatives, that impact immune defences and epithelial barrier integrity. We find that patients treated with the orally administered but non-absorbable disaccharide lactulose have increased densities of intestinal bifidobacteria and reduced incidence of systemic infections and mortality. Bifidobacteria metabolize lactulose, produce high concentrations of acetate and acidify the gut lumen in humans and mice, which, in combination, can reduce the growth of antibiotic-resistant bacteria such as vancomycin-resistant Enterococcus faecium in vitro. Our studies suggest that lactulose and bifidobacteria serve as a synbiotic to reduce rates of infection in patients with severe liver disease.

Virulence and genomic diversity among clinical isolates of ST1 (BI/NAP1/027) Clostridioides difficile.

Clostridioides difficile produces toxins that damage the colonic epithelium, causing colitis. Variation in disease severity is poorly understood and has been attributed to host factors and virulence differences between C. difficile strains. We test 23 epidemic ST1 C. difficile clinical isolates for their virulence in mice. All isolates encode a complete Tcd pathogenicity locus and achieve similar colonization densities. However, disease severity varies from lethal to avirulent infections. Genomic analysis of avirulent isolates reveals a 69-bp deletion in the cdtR gene, which encodes a response regulator for binary toxin expression. Deleting the 69-bp sequence in virulent R20291 strain renders it avirulent in mice with reduced toxin gene transcription. Our study demonstrates that a natural deletion within cdtR attenuates virulence in the epidemic ST1 C. difficile isolates without reducing colonization and persistence. Distinguishing strains on the basis of cdtR may enhance the specificity of diagnostic tests for C. difficile colitis.

High-resolution analyses of associations between medications, microbiome, and mortality in cancer patients.

Discerning the effect of pharmacological exposures on intestinal bacterial communities in cancer patients is challenging. Here, we deconvoluted the relationship between drug exposures and changes in microbial composition by developing and applying a new computational method, PARADIGM (parameters associated with dynamics of gut microbiota), to a large set of longitudinal fecal microbiome profiles with detailed medication-administration records from patients undergoing allogeneic hematopoietic cell transplantation. We observed that several non-antibiotic drugs, including laxatives, antiemetics, and opioids, are associated with increased Enterococcus relative abundance and decreased alpha diversity. Shotgun metagenomic sequencing further demonstrated subspecies competition, leading to increased dominant-strain genetic convergence during allo-HCT that is significantly associated with antibiotic exposures. We integrated drug-microbiome associations to predict clinical outcomes in two validation cohorts on the basis of drug exposures alone, suggesting that this approach can generate biologically and clinically relevant insights into how pharmacological exposures can perturb or preserve microbiota composition. The application of a computational method called PARADIGM to a large dataset of cancer patients' longitudinal fecal specimens and detailed daily medication records reveals associations between drug exposures and the intestinal microbiota that recapitulate in vitro findings and are also predictive of clinical outcomes.

Corrigendum: A MALDI-TOF MS library for rapid identification of human commensal gut bacteria from the class Clostridia.

[This corrects the article DOI: 10.3389/fmicb.2023.1104707.].

The TaxUMAP atlas: Efficient display of large clinical microbiome data reveals ecological competition in protection against bacteremia.

Longitudinal microbiome data provide valuable insight into disease states and clinical responses, but they are challenging to mine and view collectively. To address these limitations, we present TaxUMAP, a taxonomically informed visualization for displaying microbiome states in large clinical microbiome datasets. We used TaxUMAP to chart a microbiome atlas of 1,870 patients with cancer during therapy-induced perturbations. Bacterial density and diversity were positively associated, but the trend was reversed in liquid stool. Low-diversity states (dominations) remained stable after antibiotic treatment, and diverse communities had a broader range of antimicrobial resistance genes than dominations. When examining microbiome states associated with risk for bacteremia, TaxUMAP revealed that certain Klebsiella species were associated with lower risk for bacteremia localize in a region of the atlas that is depleted in high-risk enterobacteria. This indicated a competitive interaction that was validated experimentally. Thus, TaxUMAP can chart comprehensive longitudinal microbiome datasets, enabling insights into microbiome effects on human health.

Assembling symbiotic bacterial species into live therapeutic consortia that reconstitute microbiome functions.

Increasing experimental evidence suggests that administering live commensal bacterial species can optimize microbiome composition and lead to reduced disease severity and enhanced health. Our understanding of the intestinal microbiome and its functions has increased over the past two decades largely due to deep sequence analyses of fecal nucleic acids, metabolomic and proteomic assays to measure nutrient use and metabolite production, and extensive studies on the metabolism and ecological interactions of a wide range of commensal bacterial species inhabiting the intestine. Herein, we review new and important findings that have emerged from this work and provide thoughts and considerations on approaches to re-establish and optimize microbiome functions by assembling and administering commensal bacterial consortia.

A MALDI-TOF MS library for rapid identification of human commensal gut bacteria from the class Clostridia.

Introduction: Microbial isolates from culture can be identified using 16S or whole-genome sequencing which generates substantial costs and requires time and expertise. Protein fingerprinting via Matrix-assisted Laser Desorption Ionization-time of flight mass spectrometry (MALDI-TOF MS) is widely used for rapid bacterial identification in routine diagnostics but shows a poor performance and resolution on commensal bacteria due to currently limited database entries. The aim of this study was to develop a MALDI-TOF MS plugin database (CLOSTRI-TOF) allowing for rapid identification of non-pathogenic human commensal gastrointestinal bacteria. Methods: We constructed a database containing mass spectral profiles (MSP) from 142 bacterial strains representing 47 species and 21 genera within the class Clostridia. Each strain-specific MSP was constructed using >20 raw spectra measured on a microflex Biotyper system (Bruker-Daltonics) from two independent cultures. Results: For validation, we used 58 sequence-confirmed strains and the CLOSTRI-TOF database successfully identified 98 and 93% of the strains, respectively, in two independent laboratories. Next, we applied the database to 326 isolates from stool of healthy Swiss volunteers and identified 264 (82%) of all isolates (compared to 170 (52.1%) with the Bruker-Daltonics library alone), thus classifying 60% of the formerly unknown isolates. Discussion: We describe a new open-source MSP database for fast and accurate identification of the Clostridia class from the human gut microbiota. CLOSTRI-TOF expands the number of species which can be rapidly identified by MALDI-TOF MS.

Questioning the fetal microbiome illustrates pitfalls of low-biomass microbial studies.

Whether the human fetus and the prenatal intrauterine environment (amniotic fluid and placenta) are stably colonized by microbial communities in a healthy pregnancy remains a subject of debate. Here we evaluate recent studies that characterized microbial populations in human fetuses from the perspectives of reproductive biology, microbial ecology, bioinformatics, immunology, clinical microbiology and gnotobiology, and assess possible mechanisms by which the fetus might interact with microorganisms. Our analysis indicates that the detected microbial signals are likely the result of contamination during the clinical procedures to obtain fetal samples or during DNA extraction and DNA sequencing. Furthermore, the existence of live and replicating microbial populations in healthy fetal tissues is not compatible with fundamental concepts of immunology, clinical microbiology and the derivation of germ-free mammals. These conclusions are important to our understanding of human immune development and illustrate common pitfalls in the microbial analyses of many other low-biomass environments. The pursuit of a fetal microbiome serves as a cautionary example of the challenges of sequence-based microbiome studies when biomass is low or absent, and emphasizes the need for a trans-disciplinary approach that goes beyond contamination controls by also incorporating biological, ecological and mechanistic concepts.

Virulence and genomic diversity among clinical isolates of ST1 (BI/NAP1/027) Clostridioides difficile.

Clostridioides difficile (C. difficile) , a leading cause of nosocomial infection, produces toxins that damage the colonic epithelium and results in colitis that varies from mild to fulminant. Variation in disease severity is poorly understood and has been attributed to host factors (age, immune competence and intestinal microbiome composition) and/or virulence differences between C. difficile strains, with some, such as the epidemic BI/NAP1/027 (MLST1) strain, being associated with greater virulence. We tested 23 MLST1(ST1) C. difficile clinical isolates for virulence in antibiotic-treated C57BL/6 mice. All isolates encoded a complete Tcd pathogenicity locus and achieved similar colonization densities in mice. Disease severity varied, however, with 5 isolates causing lethal infections, 16 isolates causing a range of moderate infections and 2 isolates resulting in no detectable disease. The avirulent ST1 isolates did not cause disease in highly susceptible Myd88 -/- or germ-free mice. Genomic analysis of the avirulent isolates revealed a 69 base-pair deletion in the N-terminus of the cdtR gene, which encodes a response regulator for binary toxin (CDT) expression. Genetic deletion of the 69 base-pair cdtR sequence in the highly virulent ST1 R20291 C. difficile strain rendered it avirulent and reduced toxin gene transcription in cecal contents. Our study demonstrates that a natural deletion within cdtR attenuates virulence in the epidemic ST1 C. difficile strain without reducing colonization and persistence in the gut. Distinguishing strains on the basis of cdtR may enhance the specificity of diagnostic tests for C. difficile colitis.

Exposure and resistance to lantibiotics impact microbiota composition and function.

The intestinal microbiota is composed of hundreds of distinct microbial species that interact with each other and their mammalian host. Antibiotic exposure dramatically impacts microbiota compositions and leads to acquisition of antibiotic-resistance genes. Lantibiotics are ribosomally synthesized and post-translationally modified peptides produced by some bacterial strains to inhibit the growth of competing bacteria. Nisin A is a lantibiotic produced by Lactococcus lactis that is commonly added to food products to reduce contamination with Gram-positive pathogens. Little is known, however, about lantibiotic-resistance of commensal bacteria inhabiting the human intestine. Herein, we demonstrate that Nisin A administration to mice alters fecal microbiome compositions and the concentration of taurine-conjugated primary bile acids. Lantibiotic Resistance System genes (LRS) are encoded by lantibiotic-producing bacterial strains but, we show, are also prevalent in microbiomes across human cohorts spanning vastly different lifestyles and 5 continents. Bacterial strains encoding LRS have enhanced in vivo fitness upon dietary exposure to Nisin A but reduced fitness in the absence of lantibiotic pressure. Differential binding of host derived, secreted IgA contributes to fitness discordance between bacterial strains encoding or lacking LRS. Although LRS are associated with mobile genetic elements, sequence comparisons of LRS encoded by distinct bacterial species suggest they have been long-term components of their respective genomes. Our study reveals the prevalence, abundance and physiologic significance of an underappreciated subset of antimicrobial resistance genes encoded by commensal bacterial species constituting the human gut microbiome, and provides insights that will guide development of microbiome augmenting strategies.

Immunomodulatory fecal metabolites are associated with mortality in COVID-19 patients with respiratory failure.

Respiratory failure and mortality from COVID-19 result from virus- and inflammation-induced lung tissue damage. The intestinal microbiome and associated metabolites are implicated in immune responses to respiratory viral infections, however their impact on progression of severe COVID-19 remains unclear. We prospectively enrolled 71 patients with COVID-19 associated critical illness, collected fecal specimens within 3 days of medical intensive care unit admission, defined microbiome compositions by shotgun metagenomic sequencing, and quantified microbiota-derived metabolites (NCT #04552834). Of the 71 patients, 39 survived and 32 died. Mortality was associated with increased representation of Proteobacteria in the fecal microbiota and decreased concentrations of fecal secondary bile acids and desaminotyrosine (DAT). A microbiome metabolic profile (MMP) that accounts for fecal secondary bile acids and desaminotyrosine concentrations was independently associated with progression of respiratory failure leading to mechanical ventilation. Our findings demonstrate that fecal microbiota composition and microbiota-derived metabolite concentrations can predict the trajectory of respiratory function and death in patients with severe SARS-Cov-2 infection and suggest that the gut-lung axis plays an important role in the recovery from COVID-19.

Translating Microbiome Research From and To the Clinic.

Extensive research has elucidated the influence of the gut microbiota on human health and disease susceptibility and resistance. We review recent clinical and laboratory-based experimental studies associating the gut microbiota with certain human diseases. We also highlight ongoing translational advances that manipulate the gut microbiota to treat human diseases and discuss opportunities and challenges in translating microbiome research from and to the bedside.

A compilation of fecal microbiome shotgun metagenomics from hematopoietic cell transplantation patients.

Hospitalized patients receiving hematopoietic cell transplants provide a unique opportunity to study the human gut microbiome. We previously compiled a large-scale longitudinal dataset of fecal microbiota and associated metadata, but we had limited that analysis to taxonomic composition of bacteria from 16S rRNA gene sequencing. Here we augment those data with shotgun metagenomics. The compilation amounts to a nested subset of 395 samples compiled from different studies at Memorial Sloan Kettering. Shotgun metagenomics describes the microbiome at the functional level, particularly in antimicrobial resistances and virulence factors. We provide accession numbers that link each sample to the paired-end sequencing files deposited in a public repository, which can be directly accessed by the online services of PATRIC to be analyzed without the users having to download or transfer the files. Then, we show how shotgun sequencing enables the assembly of genomes from metagenomic data. The new data, combined with the metadata published previously, enables new functional studies of the microbiomes of patients with cancer receiving bone marrow transplantation.