Escherichia coli Clonobiome: Assessing the Strain Diversity in Feces and Urine by Deep Amplicon Sequencing

Evidence of Lactobacillus strains shared between the female urinary and vaginal microbiota

Lactobacillus species are common inhabitants of the 'healthy' female urinary and vaginal communities, often associated with a lack of symptoms in both anatomical sites. Given identification by prior studies of similar bacterial species in both communities, it has been hypothesized that the two microbiotas are in fact connected. Here, we carried out whole-genome sequencing of 49 Lactobacillus strains, including 16 paired urogenital samples from the same participant. These strains represent five different Lactobacillus species: L. crispatus, L. gasseri, L. iners, L. jensenii, and L. paragasseri. Average nucleotide identity (ANI), alignment, single-nucleotide polymorphism (SNP), and CRISPR comparisons between strains from the same participant were performed. We conducted simulations of genome assemblies and ANI comparisons and present a statistical method to distinguish between unrelated, related, and identical strains. We found that 50 % of the paired samples have identical strains, evidence that the urinary and vaginal communities are connected. Additionally, we found evidence of strains sharing a common ancestor. These results establish that microbial sharing between the urinary tract and vagina is not limited to uropathogens. Knowledge that these two anatomical sites can share lactobacilli in females can inform future clinical approaches.

Gut resident Escherichia coli profile predicts the eighteen-month probability and antimicrobial susceptibility of urinary tract infections

Background

Community-acquired UTI is the most common bacterial infection managed in general medical practice that can lead to life-threatening outcomes. While UTIs are primarily caused by Escherichia coli colonizing the patient's gut, it is unclear whether the gut resident E. coli profiles can predict the person's risks for UTI and optimal antimicrobial treatments. Thus, we conducted an eighteen-month long community-based observational study of fecal E. coli colonization and UTI in women aged 50 years and above.

Methods and Findings

We enrolled a total of 1,804 women distributed among age groups 50-59 yo (437 participants), 60-69 yo (632), 70-79 yo (532), and above 80 yo (203), lacking antibiotic prescriptions for at least one year. The provided fecal samples were plated for the presence of E. coli and other enterobacteria resistant to trimethoprim/sulfamethoxazole (TMP/STX), ciprofloxacin (CIP) and 3rd generation cephalosporins (3GC). E. coli was also characterized as belonging to the pandemic multi-drug resistant clonal groups ST131 (subclone H30) and ST1193. Following sample collection, the women were monitored for 18 months for occurrence of UTI.E. coli was cultured from 90.8% fecal samples, with 24.1% containing bacteria resistant to TMP/STX, 19.4% to CIP, and 7.9% to 3GC. In 62.5% samples, only all-susceptible E. coli were present. Overall, there were no age-related differences in resistance prevalence. However, while the total E. coli H30 and ST1193 carriage rates were similar (4.3% and 4.2%, respectively), there was a notable increase of H30 carriage with age (P = .001), while carriage decreased with age for ST1193 (P = .057).Within 18 months, 184 women (10.2%) experienced at least one episode of UTI - 10.9% among the gut E. coli carriers and 3.0% among the non-carriers (P=.0013). The UTI risk among carriers of E. coli H30 but not ST1193 was significantly above average (24.3%, P = .0004). The UTI probability increased with age, occurring in 6.4% of 50-59 yo and 19.7% of 80+ yo (P<.001), with the latter group being especially at high risk for UTI, if they were colonized by E. coli H30 (40.0%, P<.001).E. coli was identified in 88.1% of urine samples, with 16.1% resistant to TMP/STX, 16.1% to CIP, 4.2% to 3GC and 73.1% to none of the antibiotics. Among tested urinary E. coli resistant to antibiotics, 86.1% matched the resistance profile of E. coli in the fecal samples, with the clonotyping and whole genome sequencing confirming the matching strains' identity. Positive predictive value (PPV) of using gut resistance profiles to predict UTI pathogens' susceptibility to TMP/STX, CIP, 3GC and all three antibiotics were 98.4%, 98.3%, 96.6% and 95.3%, respectively. Corresponding negative predictive values (NPV) were 63.0%, 54.8%, 44.4% and 75.8%, respectively. The AUC ROC curve values for the accuracy of fecal diagnostic testing for the prediction of UTI resistance ranged .86-.89. The fecal test-guided drug-bug mismatch rate for empirical (pre-culture) prescription of TMP-SXT or CIP is reduced to ≤2% in 89.6% of patients and 94.8% of patients with an optional 3GC prescription.

Conclusion

The resistance profile and clonal identity of gut colonizing E. coli, along with the carrier's age, can inform personalized prediction of a patients' UTI risk and the UTI pathogen's antibiotic susceptibility within an 18-month period.

Previous Antibiotic Exposure Reshapes the Population Structure of Infecting Uropathogenic Escherichia coli Strains by Selecting for Antibiotic Resistance over Urovirulence

Antibiotic therapy is the standard of care for urinary tract infections (UTIs) caused by uropathogenic Escherichia coli (UPEC). However, previous antibiotic therapy may impart a selective pressure that influences the population structure and pathogenic potential of infecting UPEC strains. Here, we conducted a 3-year study using whole-genome-sequencing analysis and retrospective medical record review to characterize how antibiotic exposure influenced the phenotypic antibiotic resistance, acquired resistome, virulome, and population structure of 88 UTI-causing E. coli strains from dogs. A majority of UTI-associated E. coli strains were from phylogroup B2 and clustered within sequence type 372. Previous antibiotic exposure was associated with a population shift toward UPEC from phylogroups other than the typical urovirulent phylogroup B2. The specific virulence profiles within the accessory virulome that were associated with antibiotic use were elicited by the effect of antibiotics on UPEC phylogenetic structure. Among phylogroup B2, antibiotic exposure increased the quantity of genes within the resistome and the odds of developing reduced susceptibility to at least one antibiotic. Non-B2 UPEC strains harbored a more diverse and greater resistome that conferred reduced susceptibility to multiple antibiotic classes following antibiotic exposure. Collectively, these data suggest that previous antibiotic exposure establishes an environment that provides a selective edge to non-B2 UPEC strains through their diverse and abundant antibiotic resistance genes, despite their lack of urovirulence genes. Our findings highlight the necessity for judicious use of antibiotics as we uncover another mechanism by which antibiotic exposure and resistance can influence the dynamics of bacterial infectious disease. IMPORTANCE Urinary tract infections (UTIs) are one of the most common infections of dogs and humans. While antibiotic therapy is the standard of care for UTIs and other infections, antibiotic exposure may influence the pathogenic profile of subsequent infections. We used whole-genome sequencing and retrospective medical record review to characterize the effect of systemic antibiotic therapy on the resistance, virulence, and population structure of 88 UTI-causing UPEC strains isolated from dogs. Our results indicate that antibiotic exposure alters the population structure of infecting UPEC strains, providing a selective edge for non-B2 phylogroups that harbor diverse and abundant resistance gene catalogues but fewer urovirulence genes. These findings highlight how antibiotic resistance can influence pathogen infection dynamics and have clinical implications for the judicious use of antibiotics for bacterial infections.

The cnf1 gene is associated with an expanding Escherichia coli ST131 H30Rx/C2 subclade and confers a competitive advantage for gut colonization

Epidemiological projections point to acquisition of ever-expanding multidrug resistance (MDR) by Escherichia coli, a commensal of the digestive tract and a source of urinary tract pathogens. Bioinformatics analyses of a large collection of E. coli genomes from EnteroBase, enriched in clinical isolates of worldwide origins, suggest the Cytotoxic Necrotizing Factor 1 (CNF1)-toxin encoding gene, cnf1, is preferentially distributed in four common sequence types (ST) encompassing the pandemic E. coli MDR lineage ST131. This lineage is responsible for a majority of extraintestinal infections that escape first-line antibiotic treatment, with known enhanced capacities to colonize the gastrointestinal tract. Statistical projections based on this dataset point to a global expansion of cnf1-positive multidrug-resistant ST131 strains from subclade H30Rx/C2, accounting for a rising prevalence of cnf1-positive strains in ST131. Despite the absence of phylogeographical signals, cnf1-positive isolates segregated into clusters in the ST131-H30Rx/C2 phylogeny, sharing a similar profile of virulence factors and the same cnf1 allele. The suggested dominant expansion of cnf1-positive strains in ST131-H30Rx/C2 led us to uncover the competitive advantage conferred by cnf1 for gut colonization to the clinical strain EC131GY ST131-H30Rx/C2 versus cnf1-deleted isogenic strain. Complementation experiments showed that colon tissue invasion was compromised in the absence of deamidase activity on Rho GTPases by CNF1. Hence, gut colonization factor function of cnf1 was confirmed for another clinical strain ST131-H30Rx/C2. In addition, functional analysis of the cnf1-positive clinical strain EC131GY ST131-H30Rx/C2 and a cnf1-deleted isogenic strain showed no detectable impact of the CNF1 gene on bacterial fitness and inflammation during the acute phase of bladder monoinfection. Together these data argue for an absence of role of CNF1 in virulence during UTI, while enhancing gut colonization capacities of ST131-H30Rx/C2 and suggested expansion of cnf1-positive MDR isolates in subclade ST131-H30Rx/C2.

A population-level strain genotyping method to study pathogen strain dynamics in human infections

A hallmark of chronic bacterial infections is the long-term persistence of 1 or more pathogen species at the compromised site. Repeated detection of the same bacterial species can suggest that a single strain or lineage is continually present. However, infection with multiple strains of a given species, strain acquisition and loss, and changes in strain relative abundance can occur. Detecting strain-level changes and their effects on disease is challenging because most methods require labor-intensive isolate-by-isolate analyses, and thus, only a few cells from large infecting populations can be examined. Here, we present a population-level method for enumerating and measuring the relative abundance of strains called population multi-locus sequence typing (PopMLST). The method exploits PCR amplification of strain-identifying polymorphic loci, next-generation sequencing to measure allelic variants, and informatic methods to determine whether variants arise from sequencing errors or low-abundance strains. These features enable PopMLST to simultaneously interrogate hundreds of bacterial cells that are cultured en masse from patient samples or are present in DNA directly extracted from clinical specimens without ex vivo culture. This method could be used to detect epidemic or super-infecting strains, facilitate understanding of strain dynamics during chronic infections, and enable studies that link strain changes to clinical outcomes.

Structural and functional characterization of the FimH adhesin of uropathogenic Escherichia coli and its novel applications

Type 1 fimbriae are responsible for bacterial pathogenicity and biofilm production, which are important virulence factors in uropathogenic Escherichia coli strains. Many articles are published on fimH, but each examined a specific aspect of this protein. The current review study aimed at focusing on structure and conformational changes and describing efforts to use this protein in novel potential treatments for urinary tract infections, typing methods, and expression systems. The current study was the first review that briefly and effectively examined issues related to fimH adhesin.

The microbiome and host mucosal interactions in urinary tract diseases

The urinary tract consists of the bladder, ureters, and kidneys, and is an essential organ system for filtration and excretion of waste products and maintaining systemic homeostasis. In this capacity, the urinary tract is impacted by its interactions with other mucosal sites, including the genitourinary and gastrointestinal systems. Each of these sites harbors diverse ecosystems of microbes termed the microbiota, that regulates complex interactions with the local and systemic immune system. It remains unclear whether changes in the microbiota and associated metabolites may be a consequence or a driver of urinary tract diseases. Here, we review the current literature, investigating the impact of the microbiota on the urinary tract in homeostasis and disease including urinary stones, acute kidney injury, chronic kidney disease, and urinary tract infection. We propose new avenues for exploration of the urinary microbiome using emerging technology and discuss the potential of microbiome-based medicine for urinary tract conditions.

Is Global Microbial Biodiversity Increasing, Decreasing, or Staying the Same?

Animal and plant biodiversity is decreasing. In contrast, the global direction and the pace of change in microbial, including viral, biodiversity is unknown. Important niches for microbial diversity occur in highly specific associations with plants and animals, and these niches are lost as hosts become extinct. The taxonomic diversity of human gut bacteria is reported to be decreasing. On the other hand, SARS-CoV-2 variation is increasing. Where microbes are concerned, Darwin’s “tangled bank” of interdependent organisms may be composed mostly of other microbes. There is the likelihood that as some classes of microbes become extinct, others evolve and diversify. A better handle on all processes that affect microbial biodiversity and their net balance is needed. Lack of insight into the dynamics of evolution of microbial biodiversity is arguably the single most profound and consequential unknown with regard to human knowledge of the biosphere. If some or all parts of microbial diversity are relentlessly increasing, then survey approaches may be too slow to ever catch up. New approaches, including single-molecule or single-cell sequencing in populations, as well as focused attention on modulators and vectors of vertical and horizontal evolution may offer more direct insights into some aspects of the pace of microbial evolution.

Evaluation of CRISPR Diversity in the Human Skin Microbiome for Personal Identification

Microbial community diversity analysis can be utilized to characterize the personal microbiome that varies between individuals. CRISPR sequences, which reflect virome structure, in the human skin environment may be highly personalized similar to the structures of individual viromes.

The highly personalized human skin microbiome may serve as a viable marker in personal identification. Amplicon sequencing resolution using 16S rRNA cannot identify bacterial communities sufficiently to discriminate between individuals. Thus, novel higher-resolution genetic markers are required for forensic purposes. The clustered regularly interspaced short palindromic repeats (CRISPRs) are prokaryotic genetic elements that can provide a history of infections encountered by the bacteria. The sequencing of CRISPR spacers may provide phylogenetic information with higher resolution than other markers. However, using spacer sequencing for discrimination of personal skin microbiome is difficult due to limited information on CRISPRs in human skin microbiomes. It remains unclear whether personal microbiome discrimination can be achieved using spacer diversity or which CRISPRs will be forensically relevant. We identified common CRISPRs in the human skin microbiome via metagenomic reconstruction and used amplicon sequencing for deep sequencing of spacers. We successfully reconstructed 24 putative CRISPR arrays using metagenomic data sets. A total of 1,223,462 reads from three CRISPR arrays revealed that spacers in the skin microbiome were highly personalized, and conserved repeats were commonly shared between individuals. These individual specificities observed using CRISPR typing were confirmed by comparing the CRISPR diversity to microbiome diversity assessed using 16S rRNA amplicon sequencing. CRISPR typing achieved 95.2% accuracy in personal classification, whereas 16S rRNA sequencing only achieved 52.6%. These results suggest that sequencing CRISPRs in the skin microbiome may be a more powerful approach for personal identification and ecological studies compared to conventional 16S rRNA sequencing.

IMPORTANCE Microbial community diversity analysis can be utilized to characterize the personal microbiome that varies between individuals. CRISPR sequences, which reflect virome structure, in the human skin environment may be highly personalized similar to the structures of individual viromes. In this study, we identified 24 putative CRISPR arrays using a shotgun metagenome data set of the human skin microbiome. The findings of this study expand our understanding of the nature of CRISPRs by identifying novel CRISPR candidates. We developed a method to efficiently determine the diversity of three CRISPR arrays. Our analysis revealed that the CRISPR spacer diversity in the human skin microbiome is highly personalized compared with the microbiome diversity assessed by 16S rRNA sequencing, providing a new perspective on the study of the skin microbiome.