Melissa Doud

Dynamics of Pseudomonas aeruginosa genome evolution

One of the hallmarks of the Gram-negative bacterium Pseudomonas aeruginosa is its ability to thrive in diverse environments that includes humans with a variety of debilitating diseases or immune deficiencies. Here we report the complete sequence and comparative analysis of the genomes of two representative P. aeruginosa strains isolated from cystic fibrosis (CF) patients whose genetic disorder predisposes them to infections by this pathogen. The comparison of the genomes of the two CF strains with those of other P. aeruginosa presents a picture of a mosaic genome, consisting of a conserved core component, interrupted in each strain by combinations of specific blocks of genes. These strain-specific segments of the genome are found in limited chromosomal locations, referred to as regions of genomic plasticity. The ability of P. aeruginosa to shape its genomic composition to favor survival in the widest range of environmental reservoirs, with corresponding enhancement of its metabolic capacity is supported by the identification of a genomic island in one of the sequenced CF isolates, encoding enzymes capable of degrading terpenoids produced by trees. This work suggests that niche adaptation is a major evolutionary force influencing the composition of bacterial genomes. Unlike genome reduction seen in host-adapted bacterial pathogens, the genetic capacity of P. aeruginosa is determined by the ability of individual strains to acquire or discard genomic segments, giving rise to strains with customized genomic repertoires. Consequently, this organism can survive in a wide range of environmental reservoirs that can serve as sources of the infecting organisms.

Approaches to analyse dynamic microbial communities such as those seen in cystic fibrosis lung

Microbial communities play vital roles in many aspects of our lives, although our understanding of microbial biogeography and community profiles remains unclear. The number of microbes or the diversity of the microbes, even in small environmental niches, is staggering. Current microbiological methods used to analyse these communities are limited, in that many microorganisms cannot be cultured. Even for the isolates that can be cultured, the expense of identifying them definitively is much too high to be practical. Many recent molecular technologies, combined with bioinformatic tools, are raising the bar by improving the sensitivity and reliability of microbial community analysis. These tools and techniques range from those that attempt to understand a microbial community from their length heterogeneity profiles to those that help to identify the strains and species of a random sampling of the microbes in a given sample. These technologies are reviewed here, using the microbial communities present in the lungs of cystic fibrosis patients as a paradigm.

Combination of 16S rRNA variable regions provides a detailed analysis of bacterial community dynamics in the lungs of cystic fibrosis patients

Chronic bronchopulmonary bacterial infections remain the most common cause of morbidity and mortality among patients with cystic fibrosis (CF). Recent community sequencing work has now shown that the bacterial community in the CF lung is polymicrobial. Identifying bacteria in the CF lung through sequencing can be costly and is not practical for many laboratories. Molecular techniques such as terminal restriction fragment length polymorphism or amplicon length heterogeneity-polymerase chain reaction (LH-PCR) can provide many laboratories with the ability to study CF bacterial communities without costly sequencing. The aim of this study was to determine if the use of LH-PCR with multiple hypervariable regions of the 16S rRNA gene could be used to identify organisms found in sputum DNA. This work also determined if LH-PCR could be used to observe the dynamics of lung infections over a period of time. Nineteen samples were analysed with the V1 and the V1_V2 region of the 16S rRNA gene. Based on the amplicon size present in the V1_V2 region, Pseudomonas aeruginosa was confirmed to be in all 19 samples obtained from the patients. The V1 region provided a higher power of discrimination between bacterial profiles of patients. Both regions were able to identify trends in the bacterial population over a period of time. LH profiles showed that the CF lung community is dynamic and that changes in the community may in part be driven by the patients antibiotic treatment. LH-PCR is a tool that is well suited for studying bacterial communities and their dynamics.

Neurotrophic and neuroimmune responses to early-life Pseudomonas aeruginosa infection in rat lungs

Early-life respiratory infection with Pseudomonas aeruginosa is common in children with cystic fibrosis or immune deficits. Although many of its clinical manifestations involve neural reflexes, little information is available on the peripheral nervous system of infected airways. This study sought to determine whether early-life infection triggers a neurogenic-mediated immunoinflammatory response, the mechanisms of this response, and its relationship with other immunoinflammatory pathways. Weanling and adult rats were inoculated with suspensions containing P. aeruginosa (PAO1) coated on alginate microspheres suspended in Tris-CaCl(2) buffer. Five days after infection, rats were injected with capsaicin to stimulate nociceptive nerves in the airway mucosa, and microvascular permeability was measured using Evans blue as a tracer. PAO1 increased neurogenic inflammation in the extra- and intrapulmonary compartments of weanlings but not in adults. The mechanism involves selective overexpression of NGF, which is critical for the local increase in microvascular permeability and for the infiltration of polymorphonuclear leukocytes into infected lung parenchyma. These effects are mediated in part by induction of downstream inflammatory cytokines and chemokines, especially IL-1beta, IL-18, and leptin. Our data suggest that neurogenic-mediated immunoinflammatory mechanisms play important roles in airway inflammation and hyperreactivity associated with P. aeruginosa when infection occurs early in life.

Long-Term Organic Nutrient Management Fosters the Eubacterial Community Diversity in the Indian Semi-arid Alfisol as Revealed by Length Heterogeneity–PCR

Agricultural practices influence the community structure and functional diversity of soil microorganisms. In the present study, the impact of nutrient-management systems on the changes in the biological properties of Indian semi-arid Alfisol was assessed. The long-term organically managed (OGF) and inorganically fertilized (IGF) soils from century-old experimental plots were compared for eubacterial diversity using amplicon length heterogeneity PCR (LH-PCR) targeting three hypervariable domains (V1, V1_V2, and V3) of 16S rRNA gene. Of these domains, V1_V2 could discriminate the bacterial communities between the soil types. The relative ratios of amplicons differed between OGF and ICF soils, and eubacterial diversity was decreased substantially because of the inorganic chemical fertilizers, as compared to organic amendments. The Bray–Curtis similarity index and diversity indices of amplicons were greater in OGF soil than in ICF soil. This polyphasic approach revealed that the diversity and functionality of the soil eubacterial community were encouraged by long-term organic manures more than inorganic chemical fertilizers.

Computer-Assisted Bacterial Identification Using 16S rRNA Sequence Data

Most microorganisms cannot be cultured and are difficult to identify. One of the most widely used markers to help identify bacteria is the ribosomal RNA gene. A component of the small ribosomal subunit, 16S rRNA is composed of alternating evolutionarily conserved and hypervariable regions. One strategy is to exploit the length heterogeneity in the highly variable regions and to use it for microbial identification. Techniques based on the polymerase chain reaction (PCR) are ideally suited for studying length heterogeneity of the 16S rRNA hypervariable regions. PCR primers were designed using the conserved regions (V1 and V1_V2) of the gene and the lengths of the resulting amplicons were estimated in the laboratory. The aim of this project is to design a computer program that takes as input the amplicon lengths arising from a PCR experiment with a given pair of primers and to output the set of known bacteria that can result in those sequence lengths. However, there are thousands of microbial organisms that display the exact same amplicon length for a given pair of primers. If two or more pairs of primers are used and the amplicon lengths estimated using PCR, then there is a much better chance of correctly identifying the bacterial organisms present in a sample. AmpliQue is a BioPerl program that addresses this problem. AmpliQue receives as input two pairs of primers and the lengths of the amplicons from the PCR experiment. It then reports all the microbial organisms that would result in those amplicon lengths. It uses the 16S rRNA sequence database from the Ribosomal Database Project (URL: http://rdp.cme.msu.edu/). Each set of primers was run independently against the 16S rRNA database using BLAST. Results from the BLAST hits were then merged into a single table. This resulting table was then queried with the observed amplicon lengths from the PCR experiments.