RESUMEN
Traditionally, the healthy urinary bladder has been considered to be sterile. Several teams have used metagenomic (DNA-dependent) and metaculturomic (culture-dependent) methods to debunk this longstanding dogma. In fact, resident microbial communities (urobiome) have been detected in both adult females and males. Although the field is young, several observations have been made. For example, the urobiome differs between men and women, likely due to anatomical and hormonal differences. Importantly, the urobiome has been associated with a variety of lower urinary tract disorders, including overactive bladder and post-operative urinary tract infection, raising the possibility that clinicians might one day treat symptoms by modifying the urobiome instead of killing the suspected uropathogen. Little is known concerning the relationship between the urobiome and host genetics; so far, only a single paper has reported such a study. However, major efforts have gone into understanding the genomics of the urobiome itself, a process facilitated by the fact that many urobiome studies have used metaculturomic methods to detect and identify microbes. In this narrative review, we will introduce the urobiome with separate sections on the female and male urobiomes, discuss challenges specific to the urobiome, describe newly discovered associations between the urobiome and lower urinary tract symptoms, and highlight the one study that has attempted to relate host genetics and the urobiome. We will finish with a section on how metagenomic surveys and whole genome sequencing of bacterial isolates are improving our understanding of the urobiome and its relationship to lower urinary tract health and disorders.
Asunto(s)
Metagenómica , Microbiota/genética , Vejiga Urinaria/microbiología , Femenino , Humanos , Masculino , ARN Ribosómico 16S/genéticaRESUMEN
Algorithms for motif identification in sequence space have predominately been focused on recognizing patterns of a fixed length containing regions of perfect conservation with possible regions of unconstrained sequence. Such motifs can be found in everything from proteins with distinct active sites to non-coding RNAs with specific structural elements that are necessary to maintain functionality. In the event that an insertion/deletion has occurred within an unconstrained portion of the pattern, it is possible that the pattern retains its functionality. In such a case the length of the pattern is now variable and may be overlooked when utilizing existing motif detection methods. The Pattern Island Detection Algorithm (PIDA) presented here has been developed to recognize patterns that have occurrences of varying length within sequences of any size alphabet. PIDA works by identifying all regions of perfect conservation (for lengths longer than a user-specified threshold), and then builds those conservation "islands" into fixed-length patterns. Next the algorithm modifies these fixed-length patterns by identifying additional (and different) islands that can be incorporated into each pattern through insertions/deletions within the "water" separating the islands. To provide some benchmarks for this analysis, PIDA was used to search for patterns within randomly generated sequences as well as sequences known to contain conserved patterns. For each of the patterns found, the statistical significance is calculated based upon the pattern's likelihood to appear by chance, thus providing a means to determine those patterns which are likely to have a functional role. The PIDA approach to motif finding is designed to perform best when searching for patterns of variable length although it is also able to identify patterns of a fixed length. PIDA has been created to be as generally applicable as possible since there are a variety of sequence problems of this type. The algorithm was implemented in C++ and is freely available upon request from the authors.
RESUMEN
It is shown that the presence/absence pattern of 1000 random oligomers of length 12-13 in a bacterial genome is sufficiently characteristic to readily and unambiguously distinguish any known bacterial genome from any other. Even genomes of extremely closely-related organisms, such as strains of the same species, can be thus distinguished. One evident way to implement this approach in a practical assay is with hybridization arrays. It is envisioned that a single universal array can be readily designed that would allow identification of any bacterium that appears in a database of known patterns. We performed in silico experiments to test this idea. Calculations utilizing 105 publicly-available completely-sequenced microbial genomes allowed us to determine appropriate values of the test oligonucleotide length, n, and the number of probe sequences. Randomly chosen n-mers with a constant G + C content were used to form an in silico array and verify (a) how many n-mers from each genome would hybridize on this chip, and (b) how different the fingerprints of different genomes would be. With the appropriate choice of random oligomer length, the same approach can also be used to identify viral or eukaryotic genomes.