Comparative genomic and phenomic analysis of Clostridium difficile and Clostridium sordellii, two related pathogens with differing host tissue preference

Codon usage behavior distinguishes pathogenic Clostridium species from the non-pathogenic species

Genus Clostridium is of the largest genus in class Clostridia. It is comprised of spore-forming, anaerobic, gram-positive organisms. The members of this genus include human pathogens to free-living nitrogen fixing bacteria. In the present study, we have performed a comparison of the choice of preferred codons, codon usage patterns, dinucleotide and amino acid usage pattern of 76 species of Genus Clostridium. We found the pathogenic clostridium species to have smaller AT-rich genomes as compared to opportunistic and non-pathogenic clostridium species. The choice of preferred and optimal codons was also influenced by genomic GC/AT content of the respective clostridium species. The pathogenic clostridium species displayed a strict bias in the codon usage, employing 35 of the 61 codons encoding for 20 amino acids. Comparison of amino acid usage revealed an increased usage of amino acids with lower biosynthetic cost by pathogenic clostridium species as compared to opportunistic and non-pathogenic clostridium species. Smaller genome, strict codon usage bias and amino acid usage lead to lower protein energetic cost for the clostridial pathogens. Overall, we found the pathogenic members of genus Clostridium to prefer small, AT-rich codons to reduce biosynthetic costs and match the cellular environment of its AT-rich human host.

The cwp66 Gene Affects Cell Adhesion, Stress Tolerance, and Antibiotic Resistance in Clostridioides difficile

Clostridioides difficile is a Gram-positive, spore-forming anaerobic bacteria that is one of the leading causes of antibiotic-associated diarrhea. The cell wall protein 66 gene (cwp66) encodes a cell wall protein, which is the second major cell surface antigen of C. difficile. Although immunological approaches, such as antibodies and purified recombinant proteins, have been implemented to study the role of Cwp66 in cell adhesion, no deletion mutant of the cwp66 gene has yet been characterized. We constructed a cwp66 gene deletion mutant using Clustered Regularly Interspaced Short Palindromic Repeats Cpf1 (CRISPR-Cpf1) system. The phenotypic and transcriptomic changes of the Δcwp66 mutant compared with the wild-type (WT) strain were studied. The deletion of the cwp66 gene led to the decrease of cell adhesive capacity, cell motility, and stresses tolerance (to Triton X-100, acidic environment, and oxidative stress). Interestingly, the Δcwp66 mutant is more sensitive than the WT strain to clindamycin, ampicillin, and erythromycin but more resistant than the latter to vancomycin and metronidazole. Moreover, mannitol utilization capability in the Δcwp66 mutant was lost. Comparative transcriptomic analyses indicated that (i) 22.90-fold upregulation of cwpV gene and unable to express gpr gene were prominent in the Δcwp66 mutant; (ii) the cwp66 gene was involved in vancomycin resistance of C. difficile by influencing the expression of d-Alanine-d-Alanine ligase; and (iii) the mannose/fructose/sorbose IIC and IID components were upregulated in Δcwp66 mutant. The present work deepens our understanding of the contribution of the cwp66 gene to cell adhesion, stress tolerance, antibiotic resistance, and mannitol transportation of C. difficile. IMPORTANCE The cell wall protein 66 gene (cwp66) encodes a cell wall protein, which is the second major cell surface antigen of C. difficile. Although immunological approaches, such as antibodies and purified recombinant proteins, have been implemented to study the role of Cwp66 in cell adhesion, no deletion mutant of the cwp66 gene has yet been characterized. The current study provides direct evidence that the cwp66 gene serves as a major adhesion in C. difficile, and also suggested that deletion of the cwp66 gene led to the decrease of cell adhesive capacity, cell motility, and stresses tolerance (to Triton X-100, acidic environment, and oxidative stress). Interestingly, the antibiotic resistance and carbon source utilization profiles of the Δcwp66 mutant were significantly changed. These phenotypes were detrimental to the survival and pathogenesis of C. difficile in the human gut and may shed light on preventing C. difficile infection.

The Macronutrient Composition of Infant Formula Produces Differences in Gut Microbiota Maturation That Associate with Weight Gain Velocity and Weight Status

This proof-of-principle study analyzed fecal samples from 30 infants who participated in a randomized controlled trial on the effects of the macronutrient composition of infant formula on growth and energy balance. In that study, infants randomized to be fed cow milk formula (CMF) had faster weight-gain velocity during the first 4 months and higher weight-for-length Z scores up to 11.5 months than those randomized to an isocaloric extensive protein hydrolysate formula (EHF). Here we examined associations among infant formula composition, gut microbial composition and maturation, and children’s weight status. Fecal samples collected before and monthly up to 4.5 months after randomization were analyzed by shotgun metagenomic sequencing and targeted metabolomics. The EHF group had faster maturation of gut microbiota than the CMF group, and increased alpha diversity driven by Clostridia taxa. Abundance of Ruminococcus gnavus distinguished the two groups after exclusive feeding of the assigned formula for 3 months. Abundance of Clostridia at 3–4 months negatively correlated with prior weight-gain velocity and body weight phenotypes when they became toddlers. Macronutrient differences between the formulas likely led to the observed divergence in gut microbiota composition that was associated with differences in transient rapid weight gain, a well-established predictor of childhood obesity and other comorbidities.

Prevalence and Antimicrobial Resistance of Paeniclostridium sordellii in Hospital Settings

(1) Background: The purpose of this study was to determine the prevalence of clostridia strains in a hospital environment in Algeria and to evaluate their antimicrobial susceptibility to antibiotics and biocides. (2) Methods: Five hundred surface samples were collected from surfaces in the intensive care unit and surgical wards in the University Hospital of Tlemcen, Algeria. Bacterial identification was carried out using MALDI-TOF-MS, and then the minimum inhibitory concentrations (MICs) of various antimicrobial agents were determined by the E-test method. P. sordellii toxins were searched by enzymatic and PCR assays. Seven products intended for daily disinfection in the hospitals were tested against Clostridium spp. spore collections. (3) Results: Among 100 isolates, 90 P. sordellii were identified, and all strains were devoid of lethal and hemorrhagic toxin genes. Beta-lactam, linezolid, vancomycin, tigecycline, rifampicin, and chloramphenicol all proved effective against isolated strains. Among all strains tested, the spores of P. sordellii exhibited remarkable resistance to the tested biocides compared to other Clostridium species. The (chlorine-based 0.6%, 30 min), (glutaraldehyde solution 2.5%, 30 min), and (hydrogen peroxide/peracetic acid 3%, 15 min) products achieved the required reduction in spores. (4) Conclusions: Our hospital’s current cleaning and disinfection methods need to be optimized to effectively remove spores from caregivers’ hands, equipment, and surfaces.

Comparative genomic analysis of hyper-ammonia producing Acetoanaerobium sticklandii DSM 519 with purinolytic Gottschalkia acidurici 9a and pathogenic Peptoclostridium difficile 630

Acetoanaerobium sticklandii DSM519 (CST) is a hype-ammonia producing non-pathogenic anaerobe that can use amino acids as important carbon and energy sources through the Stickland reactions. Biochemical aspects of this organism have been extensively studied, but systematic studies addressing its metabolic discrepancy remain scant. In this perspective, we have intensively analyzed its genomic and metabolic characteristics to comprehend the evolutionary conservation of amino acid catabolism by a comparative genomic approach. The whole-genome data indicated that CST has shown a phylogenomic similarity with hyper-ammonia producing, purinolytic, and proteolytic pathogenic Clostridia. CST has shown to common genomic context sharing across the purinolytic Gottschalkia acidurici 9a and pathogenic Peptoclostridium difficile 630. Genome syntenic analysis described that syntenic orthologs might be originated from the recent ancestor at a slow evolution rate and syntenic-out paralogs evolved from either CDF or CAC via α-event and β-event. Collinearity of either gene orders or gene families was adjusted with syntenic out-paralogs across these genomes. The genome-wide metabolic analysis predicted 11 unique putative metabolic subsystems from the CST genome for amino acid catabolism and hydrogen production. The in silico analysis of our study revealed that a characteristic system for amino acid catabolism-directed biofuel synthesis might have slowly evolved and established as a core genomic content of CST.

Mucin-Degrading Microbes Release Monosaccharides That Chemoattract Clostridioides difficile and Facilitate Colonization of the Human Intestinal Mucus Layer

It is widely accepted that the pathogen Clostridioides difficile exploits an intestinal environment with an altered microbiota, but the details of these microbe-microbe interactions are unclear. Adherence and colonization of mucus has been demonstrated for several enteric pathogens and it is possible that mucin-associated microbes may be working in concert with C. difficile. We showed that C. difficile ribotype-027 adheres to MUC2 glycans and using fecal bioreactors, we identified that C. difficile associates with several mucin-degrading microbes. C. difficile was found to chemotax toward intestinal mucus and its glycan components, demonstrating that C. difficile senses the mucus layer. Although C. difficile lacks the glycosyl hydrolases required to degrade mucin glycans, coculturing C. difficile with the mucin-degrading Akkermansia muciniphila, Bacteroides thetaiotaomicron, and Ruminococcus torques allowed C. difficile to grow in media that lacked glucose but contained purified MUC2. Collectively, these studies expand our knowledge on how intestinal microbes support C. difficile.

The Impact of pH on Clostridioides difficile Sporulation and Physiology

Clostridioides difficile is a pathogenic bacterium that infects the human colon to cause diarrheal disease. Growth of the bacterium is known to be dependent on certain bile acids, oxygen levels, and nutrient availability in the intestine, but how the environmental pH can influence C. difficile is mostly unknown. Previous studies indicated that C. difficile modulates the intestinal pH, and prospective cohort studies have found a strong association between a more alkaline fecal pH and C. difficile infection. Based on these data, we hypothesized that C. difficile physiology can be affected by various pH conditions. In this study, we investigated the impact of a range of pH conditions on C. difficile to assess potential effects on growth, sporulation, motility, and toxin production in the strains 630Δerm and R20291. We observed pH-dependent differences in sporulation rate, spore morphology, and viability. Sporulation frequency was lowest under acidic conditions, and differences in cell morphology were apparent at low pH. In alkaline environments, C. difficile sporulation was greater for strain 630Δerm, whereas R20291 produced relatively high levels of spores in a broad range of pH conditions. Rapid changes in pH during exponential growth impacted sporulation similarly among the strains. Furthermore, we observed an increase in C. difficile motility with increases in pH, and strain-dependent differences in toxin production under acidic conditions. The data demonstrate that pH is an important parameter that affects C. difficile physiology and may reveal relevant insights into the growth and dissemination of this pathogen.IMPORTANCE Clostridioides difficile is an anaerobic bacterium that causes gastrointestinal disease. C. difficile forms dormant spores which can survive harsh environmental conditions, allowing their spread to new hosts. In this study, we determine how intestinally relevant pH conditions impact C. difficile physiology in the two divergent strains, 630Δerm and R20291. Our data demonstrate that low pH conditions reduce C. difficile growth, sporulation, and motility. However, toxin production and spore morphology were differentially impacted in the two strains at low pH. In addition, we observed that alkaline environments reduce C. difficile growth, but increase cell motility. When pH was adjusted rapidly during growth, we observed similar impacts on both strains. This study provides new insights into the phenotypic diversity of C. difficile grown under diverse pH conditions present in the intestinal tract, and demonstrates similarities and differences in the pH responses of different C. difficile isolates.

Genomics of the Pathogenic Clostridia

Whole-genome sequences are now available for all the clinically important clostridia and many of the lesser or opportunistically pathogenic clostridia. The complex clade structures of C. difficile, C. perfringens, and the species that produce botulinum toxins have been delineated by whole-genome sequence analysis. The true clostridia of cluster I show relatively low levels of gross genomic rearrangements within species, in contrast to the species of cluster XI, notably C. difficile, which have been found to have very plastic genomes with significant levels of chromosomal rearrangement. Throughout the clostridial phylotypes, a large proportion of the strain diversity is driven by the acquisition and loss of mobile elements, including phages, plasmids, insertion sequences, and transposons. Genomic analysis has been used to investigate the diversity and spread of C. difficile within hospital settings, the zoonotic transfer of isolates, and the emergence, origins, and geographic spread of epidemic ribotypes. In C. perfringens the clades defined by chromosomal sequence analysis show no indications of clustering based on host species or geographical location. Whole-genome sequence analysis helps to define the different survival and pathogenesis strategies that the clostridia use. Some, such as C. botulinum, produce toxins which rapidly act to kill the host, whereas others, such as C. perfringens and C. difficile, produce less lethal toxins which can damage tissue but do not rapidly kill the host. The genomes provide a resource that can be mined to identify potential vaccine antigens and targets for other forms of therapeutic intervention.

Detecting Clostridioides (Clostridium) difficile using canine teams: What does the nose know?

Background

Trained canines are capable of detecting Clostridioides (Clostridium) difficile (CD) in the environment; however, the primary odour of interest on which the dogs alert is unclear.

Aim

To evaluate the inter-rater reliability of two canine detection teams for their ability to discriminate between scent pads containing CD-toxin-positive and -negative odours and their ability to discriminate between clostridial strains.

Methods

During a six-month period, two canine teams were tested weekly for their ability to detect CD-toxin-positive odours and discriminate between these and -negative odours. To further determine the canines' discrimination capability, scent pads impregnated with odours from reference isolates representing common CD toxin types (including toxin-negative CD isolates) or from clinical isolates representing other clostridial species were used.

Results

A total of 264 samples were tested with an overall sensitivity of 94.7% (Team A) and 86.8% (Team B) and specificities of 96.9% and 98.7%, respectively. Inter-rater reliability was very good (Cohen's kappa 0.87). When challenged with toxin- and non-toxin-producing strains, the teams alerted on 96.3% of all CD isolate odours (including nontoxigenic strains) and 46.7% of closely related species.

Conclusions

The canine teams exhibited strong inter-rater reliability on both clinical faecal specimens and reference CD isolates (both toxin and non-toxin producing) but were challenged to discriminate between CD and closely related clostridial species. These findings strongly support the development of scent detection programmes provided dogs and their handlers are properly trained and used in the right context.

Novel Clade C-I Clostridium difficile strains escape diagnostic tests, differ in pathogenicity potential and carry toxins on extrachromosomal elements

The population structure of Clostridium difficile currently comprises eight major genomic clades. For the highly divergent C-I clade, only two toxigenic strains have been reported, which lack the tcdA and tcdC genes and carry a complete locus for the binary toxin (CDT) next to an atypical TcdB monotoxin pathogenicity locus (PaLoc). As part of a routine surveillance of C. difficile in stool samples from diarrheic human patients, we discovered three isolates that consistently gave negative results in a PCR-based screening for tcdC. Through phenotypic assays, whole-genome sequencing, experiments in cell cultures, and infection biomodels we show that these three isolates (i) escape common laboratory diagnostic procedures, (ii) represent new ribotypes, PFGE-types, and sequence types within the Clade C-I, (iii) carry chromosomal or plasmidal TcdBs that induce classical or variant cytopathic effects (CPE), and (iv) cause different levels of cytotoxicity and hamster mortality rates. These results show that new strains of C. difficile can be detected by more refined techniques and raise questions on the origin, evolution, and distribution of the toxin loci of C. difficile and the mechanisms by which this emerging pathogen causes disease.

MM, Prakash Mishra G, Singh D, Ye W, Tyler BM, Tripathy S. EumicrobeDBLite: a lightweight genomic resource and analytic platform for draft oomycete genomes

We have developed EumicrobeDBLite-a lightweight comprehensive genome resource and sequence analysis platform for oomycete organisms. EumicrobeDBLite is a successor of the VBI Microbial Database (VMD) that was built using the Genome Unified Schema (GUS). In this version, GUS has been greatly simplified with the removal of many obsolete modules and the redesign of others to incorporate contemporary data. Several dependences, such as perl object layers used for data loading in VMD, have been replaced with independent lightweight scripts. EumicrobeDBLite now runs on a powerful annotation engine developed at our laboratory, called 'Genome Annotator Lite'. Currently, this database has 26 publicly available genomes and 10 expressed sequence tag (EST) datasets of oomycete organisms. The browser page has dynamic tracks presenting comparative genomics analyses, coding and non-coding data, tRNA genes, repeats and EST alignments. In addition, we have defined 44 777 core conserved proteins from 12 oomycete organisms which form 2974 clusters. Synteny viewing is enabled by the incorporation of the Genome Synteny Viewer (GSV) tool. The user interface has undergone major changes for ease of browsing. Queryable comparative genomics information, conserved orthologous genes and pathways are among the new key features updated in this database. The browser has been upgraded to enable user upload of GFF files for quick view of genome annotation comparisons. The toolkit page integrates the EMBOSS package and has a gene prediction tool. Annotations for the organisms are updated once every 6 months to ensure quality. The database resource is available at www.eumicrobedb.org.

Phylogenomic analysis of the family Peptostreptococcaceae (Clostridium cluster XI) and proposal for reclassification of Clostridium litorale (Fendrich et al. 1991) and Eubacterium acidaminophilum (Zindel et al. 1989) as Peptoclostridium litorale gen. nov. comb. nov. and Peptoclostridium acidaminophilum comb. nov

In 1994, analyses of clostridial 16S rRNA gene sequences led to the assignment of 18 species to Clostridium cluster XI, separating them from Clostridium sensu stricto (Clostridium cluster I). Subsequently, most cluster XI species have been assigned to the family Peptostreptococcaceae with some species being reassigned to new genera. However, several misclassified Clostridium species remained, creating a taxonomic conundrum and confusion regarding their status. Here, we have re-examined the phylogeny of cluster XI species by comparing the 16S rRNA gene-based trees with protein- and genome-based trees, where available. The resulting phylogeny of the Peptostreptococcaceae was consistent with the recent proposals on creating seven new genera within this family. This analysis also revealed a tight clustering of Clostridium litorale and Eubacterium acidaminophilum. Based on these data, we propose reassigning these two organisms to the new genus Peptoclostridium as Peptoclostridium litorale gen. nov. comb. nov. (the type species of the genus) and Peptoclostridium acidaminophilum comb. nov., respectively. As correctly noted in the original publications, the genera Acetoanaerobium and Proteocatella also fall within cluster XI, and can be assigned to the Peptostreptococcaceae. Clostridium sticklandii, which falls within radiation of genus Acetoanaerobium, is proposed to be reclassified as Acetoanaerobium sticklandii comb. nov. The remaining misnamed members of the Peptostreptococcaceae, [Clostridium] hiranonis, [Clostridium] paradoxum and [Clostridium] thermoalcaliphilum, still remain to be properly classified.

Identifying Multiple Potential Metabolic Cycles in Time-Series from Biolog Experiments

Biolog Phenotype Microarray (PM) is a technology allowing simultaneous screening of the metabolic behaviour of bacteria under a large number of different conditions. Bacteria may often undergo several cycles of metabolic activity during a Biolog experiment. We introduce a novel algorithm to identify these metabolic cycles in PM experimental data, thus increasing the potential of PM technology in microbiology. Our method is based on a statistical decomposition of the time-series measurements into a set of growth models. We show that the method is robust to measurement noise and captures accurately the biologically relevant signals from the data. Our implementation is made freely available as a part of an R package for PM data analysis and can be found at www.helsinki.fi/bsg/software/Biolog_Decomposition.