scholarly journals Clostridium difficilecolonizes alternative nutrient niches during infection across distinct murine gut microbiomes

2016 ◽  
Author(s):  
Matthew L. Jenior ◽  
Jhansi L. Leslie ◽  
Vincent B. Young ◽  
Patrick D. Schloss
Keyword(s):  
Clostridium Difficile ◽  
Network Architecture ◽  
Diarrheal Disease ◽  
Carbon Sources ◽  
Metabolic Model ◽  
The United States ◽  
Nutrient Concentrations ◽  
Community Structures ◽  
A Genome

AbstractClostridium difficileis the largest single cause of hospital-acquired infection in the United States. A major risk factor forClostridium difficileinfection (CDI) is prior exposure to antibiotics, as they disrupt the gut bacterial community which protects fromC. difficilecolonization. Multiple antibiotic classes have been associated with CDI susceptibility; many leading to distinct community structures stemming from variation in bacterial targets of action. These community structures present separate metabolic challenges toC. difficile.Therefore we hypothesized that the pathogen adapts its physiology to the nutrients within different gut environments. Utilizing anin vivoCDI model, we demonstratedC. difficilehighly colonized ceca of mice pretreated with any of three antibiotics from distinct classes. Levels ofC. difficilespore formation and toxin activity varied between animals based on the antibiotic pretreatment. These physiologic processes inC. difficileare partially regulated by environmental nutrient concentrations. To investigate metabolic responses of the bacteriumin vivo, we performed transcriptomic analysis ofC. difficilefrom ceca of infected mice across pretreatments. This revealed heterogeneous expression in numerous catabolic pathways for diverse growth substrates. To assess which resourcesC. difficileexploited, we developed a genome-scale metabolic model with a transcriptome-enabled metabolite scoring algorithm integrating network architecture. This platform identified nutrientsC. difficileused preferentially between pretreatments, which were validated through untargeted mass spectrometry of each microbiome. Our results supported the hypothesis thatC. difficileinhabits alternative nutrient niches across cecal microbiomes with increased preference for nitrogen-containing carbon sources, particularly Stickland fermentation substrates and host-derived glycans.ImportanceInfection by the bacteriumClostridium difficilecauses an inflammatory diarrheal disease which can become life-threatening, and has grown to be the most prevalent nosocomial infection. Susceptibility toC. difficileinfection is strongly associated with previous antibiotic treatment, which disrupts the gut microbiota and reduces its ability to prevent colonization. In this study we demonstrated thatC. difficilealtered pathogenesis between hosts pretreated with antibiotics from separate classes, and exploited different nutrient sources across these environments. Our metabolite score calculation also provides a platform to study nutrient requirements of pathogens during an infection. Our results suggest thatC. difficilecolonization resistance is mediated by multiple groups of bacteria competing for several subsets of nutrients and could explain why total reintroduction of competitors through fecal microbial transplant currently is the most effective treatment for recurrent CDI. This work could ultimately contribute to the identification of targeted, context-dependent measures that prevent or reduceC. difficilecolonization including pre- and probiotic therapies.

scholarly journals Metabolic Modeling of Streptococcus mutans Reveals Complex Nutrient Requirements of an Oral Pathogen

mSystems ◽  
2019 ◽  
Vol 4 (5) ◽  
Author(s):  
Kenan Jijakli ◽  
Paul A. Jensen
Keyword(s):  
Streptococcus Mutans ◽  
Single Gene ◽  
Metabolic Model ◽  
The United States ◽  
Defined Medium ◽  
Oral Microbiome ◽  
Tooth Decay ◽  
Oral Pathogen ◽  
Content Type ◽  
A Genome

ABSTRACT Streptococcus mutans is a Gram-positive bacterium that thrives under acidic conditions and is a primary cause of tooth decay (dental caries). To better understand the metabolism of S. mutans on a systematic level, we manually constructed a genome-scale metabolic model of the S. mutans type strain UA159. The model, called iSMU, contains 675 reactions involving 429 metabolites and the products of 493 genes. We validated iSMU by comparing simulations with growth experiments in defined medium. The model simulations matched experimental results for 17 of 18 carbon source utilization assays and 47 of 49 nutrient depletion assays. We also simulated the effects of single gene deletions. The model’s predictions agreed with 78.1% and 84.4% of the gene essentiality predictions from two experimental data sets. Our manually curated model is more accurate than S. mutans models generated from automated reconstruction pipelines and more complete than other manually curated models. We used iSMU to generate hypotheses about the S. mutans metabolic network. Subsequent genetic experiments confirmed that (i) S. mutans catabolizes sorbitol via a sorbitol-6-phosphate 2-dehydrogenase (SMU_308) and (ii) the Leloir pathway is required for growth on complex carbohydrates such as raffinose. We believe the iSMU model is an important resource for understanding the metabolism of S. mutans and guiding future experiments. IMPORTANCE Tooth decay is the most prevalent chronic disease in the United States. Decay is caused by the bacterium Streptococcus mutans, an oral pathogen that ferments sugars into tooth-destroying lactic acid. We constructed a complete metabolic model of S. mutans to systematically investigate how the bacterium grows. The model provides a valuable resource for understanding and targeting S. mutans’ ability to outcompete other species in the oral microbiome.

scholarly journals Modeling the Interplay between Photosynthesis, CO2 Fixation, and the Quinone Pool in a Purple Non-Sulfur Bacterium

2019 ◽  
Author(s):  
Adil Alsiyabi ◽  
Cheryl Immethun ◽  
Rajib Saha
Keyword(s):  
Organic Compounds ◽  
Redox State ◽  
Rhodopseudomonas Palustris ◽  
Tca Cycle ◽  
Metabolic Model ◽  
Hydrogen Gas ◽  
A Genome ◽  
Feed Forward Controller ◽  
Quinone Pool

AbstractRhodopseudomonas palustris CGA009 is a purple non-sulfur bacterium (PNSB) that can fix CO2 and nitrogen or break down organic compounds for its carbon and nitrogen requirements. Light, inorganic, and organic compounds can all be used for its source of energy. Excess electrons produced during its metabolic processes can be exploited to produce hydrogen gas or biodegradable polyesters (polyhydroxybutyrate). A genome-scale metabolic model of the bacterium was reconstructed to study the interactions between photosynthesis, carbon dioxide fixation, and the redox state of the quinone pool. A comparison of model-predicted flux values with published in vivo MFA fluxes resulted in predicted errors of 5-19% across four different growth substrates. The model predicted the presence of an unidentified sink responsible for the oxidation of excess quinols generated by the TCA cycle. Furthermore, light-dependent energy production was found to be highly dependent on the rate of quinol oxidation. Finally, the extent of CO2 fixation was predicted to be dependent on the amount of ATP generated through the electron transport cycle, with excess ATP going toward the energy-demanding CBB pathway. Based on this analysis, it is hypothesized that the quinone redox state acts as a feed-forward controller of the CBB pathway, signaling the amount of ATP available.

scholarly journals In silico analysis of the fast-growing thermophile Geobacillus sp. LC300 using a novel genome-scale metabolic model

2021 ◽  
Author(s):  
Emil Ljungqvist ◽  
Martin Gustavsson
Keyword(s):  
Metabolic Engineering ◽  
Carbon Sources ◽  
In Silico Analysis ◽  
High Growth ◽  
Metabolic Model ◽  
Thermophilic Microorganisms ◽  
Cell Factories ◽  
Conversion Rates ◽  
A Genome ◽  
Genome Scale

AbstractThermophilic microorganisms show high potential for use as biorefinery cell factories. Their high growth temperatures provide fast conversion rates, lower risk of contaminations, and facilitated purification of volatile products. To date, only a few thermophilic species have been utilized for microbial production purposes, and the development of production strains is impeded by the lack of metabolic engineering tools. In this study, we constructed a genome-scale metabolic model, iGEL601, of Geobacillus sp. LC300, an important part of the metabolic engineering pipeline. The model contains 601 genes, 1240 reactions and 1305 metabolites, and the reaction reversibility is based on thermodynamics at the optimum growth temperature. Using flux sampling, the model shows high similarity to experimentally determined reaction fluxes with both glucose and xylose as sole carbon sources. Furthermore, the model predicts previously unidentified by-products, closing the gap in the carbon balance for both carbon sources. Finally, iGEL601 was used to suggest metabolic engineering strategies to maximise production of five industrially relevant compounds. The suggested strategies have previously been experimentally verified in other microorganisms, and predicted production rates are on par with or higher than those previously achieved experimentally. The results highlight the biotechnological potential of LC300 and the application of iGEL601 for use as a tool in the metabolic engineering workflow.

scholarly journals Pseudomonas aeruginosa reverse diauxie is an optimized, resource utilization strategy

2020 ◽  
Author(s):  
S. Lee McGill ◽  
Yeni Yung ◽  
Kristopher A. Hunt ◽  
Michael A. Henson ◽  
Luke Hanley ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Systems Biology ◽  
In Silico ◽  
Carbon Sources ◽  
Opportunistic Pathogen ◽  
Metabolic Model ◽  
Wide Distribution ◽  
Overflow Metabolism ◽  
A Genome

AbstractPseudomonas aeruginosa is a globally-distributed bacterium often found in medical infections. The opportunistic pathogen uses a different, carbon catabolite repression (CCR) strategy than many, model microorganisms. It does not utilize a classic diauxie phenotype, nor does it follow common systems biology assumptions including preferential consumption of glucose with an ‘overflow’ metabolism. Despite these contradictions, P. aeruginosa is competitive in many, disparate environments underscoring knowledge gaps in microbial ecology and systems biology. Physiological, omics, and in silico analyses were used to quantify the P. aeruginosa CCR strategy known as ‘reverse diauxie’. An ecological basis of reverse diauxie was identified using a genome-scale, metabolic model interrogated with in vitro omics data. Reverse diauxie preference for lower energy, nonfermentable carbon sources, such as acetate or succinate over glucose, was predicted using a multidimensional strategy which minimized resource investment into central metabolism while completely oxidizing substrates. Application of a common, in silico optimization criterion, which maximizes growth rate, did not predict the reverse diauxie phenotypes. This study quantifies P. aeruginosa metabolic strategies foundational to its wide distribution and virulence.

scholarly journals Cryptosporidium parvum Pyruvate Kinase Inhibitors With in vivo Anti-cryptosporidial Efficacy

2022 ◽  
Vol 12 ◽  
Author(s):  
Shahbaz M. Khan ◽  
Xuejin Zhang ◽  
William H. Witola
Keyword(s):  
Pyruvate Kinase ◽  
Cryptosporidium Parvum ◽  
Diarrheal Disease ◽  
Severe Disease ◽  
The United States ◽  
Metabolic Energy ◽  
Host Cells ◽  
Infection Model

Cryptosporidium parvum is a highly prevalent protozoan parasite that causes a diarrheal disease in humans and animals worldwide. Thus far, the moderately effective nitazoxanide is the only drug approved by the United States Food and Drug Administration for treating cryptosporidiosis in immunocompetent humans. However, no effective drug exists for the severe disease seen in young children, immunocompromised individuals and neonatal livestock. C. parvum lacks the Krebs cycle and the oxidative phosphorylation steps, making it dependent solely on glycolysis for metabolic energy production. Within its glycolytic pathway, C. parvum possesses two unique enzymes, the bacterial-type lactate dehydrogenase (CpLDH) and the plant-like pyruvate kinase (CpPyK), that catalyze two sequential steps for generation of essential metabolic energy. We have previously reported that inhibitors of CpLDH are effective against C. parvum, both in vitro and in vivo. Herein, we developed an in vitro assay for the enzymatic activity of recombinant CpPyK protein and used it to screen a chemical compound library for inhibitors of CpPyK’s activity. The identified inhibitors were tested (at non-toxic concentrations) for efficacy against C. parvum using in vitro assays, and an in vivo mouse infection model. We identified six CpPyK inhibitors that blocked in vitro growth and proliferation of C. parvum at low micromolar concentrations (EC50 values ranging from 10.29 to 86.01 μM) that were non-toxic to host cells. Among those six compounds, two (NSC252172 and NSC234945) were found to be highly efficacious against cryptosporidiosis in immunocompromised mice at a dose of 10 mg/kg body weight, with very significant reduction in parasite load and amelioration of intestinal pathologies. Together, these findings have unveiled inhibitors for an essential molecular target in C. parvum and demonstrated their efficacy against the parasite in vitro and in vivo. These inhibitors are, therefore, potential lead-compounds for developing efficacious treatments for cryptosporidiosis.

scholarly journals Clostridium difficile Colonizes Alternative Nutrient Niches during Infection across Distinct Murine Gut Microbiomes

mSystems ◽  
2017 ◽  
Vol 2 (4) ◽  
Author(s):  
Matthew L. Jenior ◽  
Jhansi L. Leslie ◽  
Vincent B. Young ◽  
Patrick D. Schloss
Keyword(s):  
Clostridium Difficile ◽  
Nosocomial Infection ◽  
Diarrheal Disease ◽  
Nutrient Requirements ◽  
Colonization Resistance ◽  
Nutrient Sources ◽  
Infection Susceptibility ◽  
Life Threatening ◽  
Multiple Groups

ABSTRACT Infection by the bacterium Clostridium difficile causes an inflammatory diarrheal disease which can become life threatening and has grown to be the most prevalent nosocomial infection. Susceptibility to C. difficile infection is strongly associated with previous antibiotic treatment, which disrupts the gut microbiota and reduces its ability to prevent colonization. In this study, we demonstrated that C. difficile altered pathogenesis between hosts pretreated with antibiotics from separate classes and exploited different nutrient sources across these environments. Our metabolite score calculation also provides a platform to study nutrient requirements of pathogens during an infection. Our results suggest that C. difficile colonization resistance is mediated by multiple groups of bacteria competing for several subsets of nutrients and could explain why total reintroduction of competitors through fecal microbial transplant currently is the most effective treatment for recurrent CDI. This work could ultimately contribute to the identification of targeted, context-dependent measures that prevent or reduce C. difficile colonization, including pre- and probiotic therapies. Clostridium difficile is the largest single cause of hospital-acquired infection in the United States. A major risk factor for Clostridium difficile infection (CDI) is prior exposure to antibiotics, as they disrupt the gut bacterial community which protects from C. difficile colonization. Multiple antibiotic classes have been associated with CDI susceptibility, many leading to distinct community structures stemming from variation in bacterial targets of action. These community structures present separate metabolic challenges to C. difficile. Therefore, we hypothesized that the pathogen adapts its physiology to the nutrients within different gut environments. Utilizing an in vivo CDI model, we demonstrated that C. difficile highly colonized ceca of mice pretreated with any of three antibiotics from distinct classes. Levels of C. difficile spore formation and toxin activity varied between animals based on the antibiotic pretreatment. These physiologic processes in C. difficile are partially regulated by environmental nutrient concentrations. To investigate metabolic responses of the bacterium in vivo, we performed transcriptomic analysis of C. difficile from ceca of infected mice across pretreatments. This revealed heterogeneous expression in numerous catabolic pathways for diverse growth substrates. To assess which resources C. difficile exploited, we developed a genome-scale metabolic model with a transcriptome-enabled metabolite scoring algorithm integrating network architecture. This platform identified nutrients that C. difficile used preferentially between pretreatments, which were validated through untargeted mass spectrometry of each microbiome. Our results supported the hypothesis that C. difficile inhabits alternative nutrient niches across cecal microbiomes with increased preference for nitrogen-containing carbon sources, particularly Stickland fermentation substrates and host-derived glycans. IMPORTANCE Infection by the bacterium Clostridium difficile causes an inflammatory diarrheal disease which can become life threatening and has grown to be the most prevalent nosocomial infection. Susceptibility to C. difficile infection is strongly associated with previous antibiotic treatment, which disrupts the gut microbiota and reduces its ability to prevent colonization. In this study, we demonstrated that C. difficile altered pathogenesis between hosts pretreated with antibiotics from separate classes and exploited different nutrient sources across these environments. Our metabolite score calculation also provides a platform to study nutrient requirements of pathogens during an infection. Our results suggest that C. difficile colonization resistance is mediated by multiple groups of bacteria competing for several subsets of nutrients and could explain why total reintroduction of competitors through fecal microbial transplant currently is the most effective treatment for recurrent CDI. This work could ultimately contribute to the identification of targeted, context-dependent measures that prevent or reduce C. difficile colonization, including pre- and probiotic therapies.

scholarly journals Pathogenicity Locus, Core Genome, and Accessory Gene Contributions to Clostridium difficile Virulence

mBio ◽  
2017 ◽  
Vol 8 (4) ◽  
Author(s):  
Brittany B. Lewis ◽  
Rebecca A. Carter ◽  
Lilan Ling ◽  
Ingrid Leiner ◽  
Ying Taur ◽  
...  
Keyword(s):  
United States ◽  
Clostridium Difficile ◽  
Disease Severity ◽  
Immune Status ◽  
Toxin Production ◽  
The United States ◽  
Microbiome Composition ◽  
Intestinal Infections ◽  
Severe Colitis

ABSTRACT Clostridium difficile is a spore-forming anaerobic bacterium that causes colitis in patients with disrupted colonic microbiota. While some individuals are asymptomatic C. difficile carriers, symptomatic disease ranges from mild diarrhea to potentially lethal toxic megacolon. The wide disease spectrum has been attributed to the infected host’s age, underlying diseases, immune status, and microbiome composition. However, strain-specific differences in C. difficile virulence have also been implicated in determining colitis severity. Because patients infected with C. difficile are unique in terms of medical history, microbiome composition, and immune competence, determining the relative contribution of C. difficile virulence to disease severity has been challenging, and conclusions regarding the virulence of specific strains have been inconsistent. To address this, we used a mouse model to test 33 clinical C. difficile strains isolated from patients with disease severities ranging from asymptomatic carriage to severe colitis, and we determined their relative in vivo virulence in genetically identical, antibiotic-pretreated mice. We found that murine infections with C. difficile clade 2 strains (including multilocus sequence type 1/ribotype 027) were associated with higher lethality and that C. difficile strains associated with greater human disease severity caused more severe disease in mice. While toxin production was not strongly correlated with in vivo colonic pathology, the ability of C. difficile strains to grow in the presence of secondary bile acids was associated with greater disease severity. Whole-genome sequencing and identification of core and accessory genes identified a subset of accessory genes that distinguish high-virulence from lower-virulence C. difficile strains. IMPORTANCE Clostridium difficile is an important cause of hospital-associated intestinal infections, and recent years have seen an increase in the number and severity of cases in the United States. A patient’s antibiotic history, immune status, and medical comorbidities determine, in part, the severity of C. difficile infection. The relative virulence of different clinical C. difficile strains, although postulated to determine disease severity in patients, has been more difficult to consistently associate with mild versus severe colitis. We tested 33 distinct clinical C. difficile isolates for their ability to cause disease in genetically identical mice and found that C. difficile strains belonging to clade 2 were associated with higher mortality. Differences in survival were not attributed to differences in toxin production but likely resulted from the distinct gene content in the various clinical isolates. IMPORTANCE Clostridium difficile is an important cause of hospital-associated intestinal infections, and recent years have seen an increase in the number and severity of cases in the United States. A patient’s antibiotic history, immune status, and medical comorbidities determine, in part, the severity of C. difficile infection. The relative virulence of different clinical C. difficile strains, although postulated to determine disease severity in patients, has been more difficult to consistently associate with mild versus severe colitis. We tested 33 distinct clinical C. difficile isolates for their ability to cause disease in genetically identical mice and found that C. difficile strains belonging to clade 2 were associated with higher mortality. Differences in survival were not attributed to differences in toxin production but likely resulted from the distinct gene content in the various clinical isolates.

scholarly journals First Genome-Scale Metabolic Model of Dolosigranulum pigrum Confirms Multiple Auxotrophies

Metabolites ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 232
Author(s):  
Alina Renz ◽  
Lina Widerspick ◽  
Andreas Dräger
Keyword(s):  
Minimal Medium ◽  
Laboratory Experiments ◽  
Carbon Sources ◽  
Metabolic Model ◽  
High Quality ◽  
High Importance ◽  
Manual Curation ◽  
A Genome ◽  
Severe Infections ◽  
Genome Scale

Dolosigranulum pigrum is a quite recently discovered Gram-positive coccus. It has gained increasing attention due to its negative correlation with Staphylococcus aureus, which is one of the most successful modern pathogens causing severe infections with tremendous morbidity and mortality due to its multiple resistances. As the possible mechanisms behind its inhibition of S. aureus remain unclear, a genome-scale metabolic model (GEM) is of enormous interest and high importance to better study its role in this fight. This article presents the first GEM of D. pigrum, which was curated using automated reconstruction tools and extensive manual curation steps to yield a high-quality GEM. It was evaluated and validated using all currently available experimental data of D. pigrum. With this model, already predicted auxotrophies and biosynthetic pathways could be verified. The model was used to define a minimal medium for further laboratory experiments and to predict various carbon sources’ growth capacities. This model will pave the way to better understand D. pigrum’s role in the fight against S. aureus.

scholarly journals Reconstruction and analysis of genome-scale metabolic model of weak Crabtree positive yeast Lachancea kluyveri

2020 ◽  
Author(s):  
Piyush Nanda ◽  
Pradipta Patra ◽  
Manali Das ◽  
Amit Ghosh
Keyword(s):  
Ethyl Acetate ◽  
Metabolic Flux ◽  
Carbon Sources ◽  
Growth Dynamics ◽  
Dry Weight ◽  
Metabolic Model ◽  
Flux Analysis ◽  
Specific Rate ◽  
A Genome ◽  
Genome Scale

Abstract Background Lachancea kluyveri, a weak Crabtree positive yeast, has been extensively studied for its unique URC pyrimidine catabolism pathway. It produces more biomass than Saccharomyces cerevisiae due to the underlying weak Crabtree effect and resorts to optimal fermentation only in oxygen limiting conditions that render it a suitable host for industrial-scale protein production. Ethyl acetate, an important industrial chemical, has been demonstrated to be a major overflow metabolite during aerobic batch cultivation with a specific rate of 0.12 g per g dry weight per hour. Here, we reconstruct a genome-scale metabolic model of the yeast to better explain the observed phenotypes and aid further hypothesis generation. Results We report the first genome-scale metabolic model, iPN730, using Build Fungal Model in KBase workspace. The inconsistencies in the draft model were semi-automatically corrected using literature and published datasets. The curated model comprises of 1235 reactions, 1179 metabolites, and 730 genes distributed in 8 compartments (organelles). The in silico viability in different media conditions and the growth characteristics in various carbon sources show good agreement with experimental data. Dynamic flux balance analysis describes the growth dynamics, substrate utilization and product formation kinetics in various oxygen-limited conditions. The URC pyrimidine degradation pathway incorporated into the model enables it to grow on uracil or urea as the sole nitrogen source. Conclusion The genome-scale metabolic construction of L. kluyveri will provide a better understanding of metabolism, particularly that of pyrimidine metabolism and ethyl acetate production. Metabolic flux analysis using the model will enable hypotheses generation to gain a deeper understanding of metabolism in weakly Crabtree positive yeast and in fungal biodiversity in general.

scholarly journals Pseudomonas aeruginosa reverse diauxie is a multidimensional, optimized, resource utilization strategy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
S. Lee McGill ◽  
Yeni Yung ◽  
Kristopher A. Hunt ◽  
Michael A. Henson ◽  
Luke Hanley ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Systems Biology ◽  
In Silico ◽  
Carbon Sources ◽  
Opportunistic Pathogen ◽  
Metabolic Model ◽  
Wide Distribution ◽  
Overflow Metabolism ◽  
A Genome

AbstractPseudomonas aeruginosa is a globally-distributed bacterium often found in medical infections. The opportunistic pathogen uses a different, carbon catabolite repression (CCR) strategy than many, model microorganisms. It does not utilize a classic diauxie phenotype, nor does it follow common systems biology assumptions including preferential consumption of glucose with an ‘overflow’ metabolism. Despite these contradictions, P. aeruginosa is competitive in many, disparate environments underscoring knowledge gaps in microbial ecology and systems biology. Physiological, omics, and in silico analyses were used to quantify the P. aeruginosa CCR strategy known as ‘reverse diauxie’. An ecological basis of reverse diauxie was identified using a genome-scale, metabolic model interrogated with in vitro omics data. Reverse diauxie preference for lower energy, nonfermentable carbon sources, such as acetate or succinate over glucose, was predicted using a multidimensional strategy which minimized resource investment into central metabolism while completely oxidizing substrates. Application of a common, in silico optimization criterion, which maximizes growth rate, did not predict the reverse diauxie phenotypes. This study quantifies P. aeruginosa metabolic strategies foundational to its wide distribution and virulence including its potentially, mutualistic interactions with microorganisms found commonly in the environment and in medical infections.

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