Identification of nine sequence types of the 16S rRNA genes of Campylobacter jejuni subsp. jejuni isolated from broilers

<p>Abstract</p> <p>Background</p> <p>Campylobacter is the most commonly reported bacterial cause of enteritis in humans in the EU Member States and other industrialized countries. One significant source of infection is broilers and consumption of undercooked broiler meat. <it>Campylobacter jejuni </it>is the <it>Campylobacter </it>sp. predominantly found in infected humans and colonized broilers. Sequence analysis of the 16S rRNA gene is very useful for identification of bacteria to genus and species level. The objectives in this study were to determine the degree of intraspecific variation in the 16S rRNA genes of <it>C. jejuni </it>and <it>C. coli </it>and to determine whether the 16S rRNA sequence types correlated with genotypes generated by PFGE analysis of <it>Sma</it>I restricted genomic DNA of the strains.</p> <p>Methods</p> <p>The 16S rRNA genes of 45 strains of <it>C. jejuni </it>and two <it>C. coli </it>strains isolated from broilers were sequenced and compared with 16S rRNA sequences retrieved from the Ribosomal Database Project or GenBank. The strains were also genotyped by PFGE after digestion with <it>Sma</it>I.</p> <p>Results</p> <p>Sequence analyses of the 16S rRNA genes revealed nine sequence types of the <it>Campylobacter </it>strains and the similarities between the different sequence types were in the range 99.6–99.9%. The number of nucleotide substitutions varied between one and six among the nine 16S rRNA sequence types. One of the nine 16S rRNA sequence profiles was common to 12 of the strains from our study and two of these were identified as <it>Campylobacter coli </it>by PCR/REA. The other 10 strains were identified as <it>Campylobacter jejuni</it>. Five of the nine sequence types were also found among the <it>Campylobacter </it>sequences deposited in GenBank. The three 16S rRNA genes in the analysed strains were identical within each individual strain for all 47 strains.</p> <p>Conclusion</p> <p><it>C. jejuni </it>and <it>C. coli </it>seem to lack polymorphisms in their 16S rRNA gene, but phylogenetic analysis based on 16S rRNA sequences was not always sufficient for differentiation between <it>C. jejuni </it>and <it>C. coli</it>. The strains were grouped in two major clusters according to 16S rRNA, one cluster with only <it>C. jejuni </it>and the other with both <it>C. jejuni </it>and <it>C. coli</it>. Genotyping of the 47 strains by PFGE after digestion with <it>Sma</it>I resulted in 22 subtypes. A potential correlation was found between the <it>Sma</it>I profiles and the 16S rRNA sequences, as a certain <it>Sma</it>I type only appeared in one of the two major phylogenetic groups.</p

Structural Analysis of Mutations in the Mitochondrial Ribosomal Rna of Homo Sapiens Found in Patients With Hearing Loss

[Resumen] Debido a la importancia de las mitocondrias en los procesos de respiración y supervivencia celular, así como a la de los ribosomas en la traducción de proteínas, las mutaciones en las secuencias de ADN mitocondrial que codifican los ARN ribosómicos mitocondriales podrían causar disfunciones mitocondriales y, en última instancia, patologías como la sordera. Gracias al creciente número de estructuras tridimensionales de alta resolución de mitorribosomas de mamíferos y ribosomas heterólogos, al desarrollo de programas informáticos de análisis estructural y al establecimiento de métodos de estudio como el Análisis Inferencial Heterólogo, podemos examinar las mutaciones encontradas e incluso inferir su poder disruptivo y su relación con la enfermedad. Partiendo de la premisa de que las mutaciones ototóxicas encontradas en los ARN ribosomales mitocondriales humanos podrían causar una disminución de la fidelidad mitocondrial debido a un aumento de las tasas de error durante el proceso de descodificación, y dado que hasta ahora no ha sido posible medir la fidelidad mitocondrial in vivo debido a las barreras físicas y metodológicas para estudiar a las mitocondrias dentro de los sistemas celulares, nuestro grupo se propuso determinar el potencial poder disruptivo de una cohorte de 78 mutaciones encontradas en los genes 12S y 16S del ARN ribosómico mitocondrial que se han relacionado (o al menos se sospecha que están relacionadas) con la sordera. De las 78 mutaciones (véase el Anexo), en las que nos centramos casi exclusivamente en realizar un análisis de conservación, se descartaron todas aquellas que no pueden considerarse universalmente conservadas para así continuar con un análisis estructural algo más profundo. De las cuatro mutaciones finalmente seleccionadas, mt. A801G, mt. A827G, mt. C1226G y mt. A1557C, pudimos confirmar el poder disruptivo previamente predicho de la mutación mt. A1557C en las estructuras mitorribosómicas. En cuanto a las otras tres mutaciones analizadas, sospechamos que la mt. A801G tiene poco, o ningún, poder disruptivo. Finalmente, sobre las mutaciones mt. A827G y mt. C1226G no podemos afirmar más allá del hecho de que los datos apuntan a un potencial poder disruptivo en ambos casos, aunque serían necesarios más análisis tanto a nivel molecular en Homo sapiens como en organismos heterólogos, como a nivel estructural mediante Análisis Inferencial Heterólogo.[Resumo] Debido á importancia das mitocondrias nos procesos de respiración e supervivencia celular, así como a dos ribosomas na tradución de proteínas, as mutacións nas secuencias de ADN mitocondrial que codifican os ARN ribosómicos mitocondriais poden provocar a disfunción mitocondrial e, en definitiva, conducir a patoloxías como a xordeira. Grazas ao crecente número de estruturas tridimensionais de alta resolución de mitorribosomas de mamíferos e ribosomas heterólogos, ao desenvolvemento de software de análise estrutural e ao establecemento de métodos de estudo como a Análise Inferencial Heteróloga, podemos examinar as mutacións atopadas e mesmo inferir o seu potencial poder disruptivo e a súa relación coa enfermidade. Partindo da premisa de que as mutacións ototóxicas atopadas nos ARN ribosómicos mitocondriais humanos poderían provocar unha diminución da fidelidade mitocondrial debido ao aumento das taxas de erro durante o proceso de decodificación, e dado que non foi posible medir a fidelidade mitocondrial in vivo debido as barreiras físicas e metodolóxicas que impiden estudar as mitocondrias dentro dos sistemas celulares, o noso grupo decidiu determinar o potencial poder disruptivo dunha cohorte de 78 mutacións atopadas nos xenes 12S e 16S do ARN ribosómico mitocondrial que están relacionadas (ou, polo menos, son sospeitosas de estalo) coa xordeira. Das 78 mutacións (ver Anexo), nas que nos centramos case exclusivamente na realización de análises de conservación, descartáronse todas aquelas que non poden considerarse como universalmente conservadas para así continuar con unha posterior análise estrutural. Así, das catro mutacións finalmente seleccionadas, mt. A801G, mt. A827G, mt. C1226G e mt. A1557C, puidemos confirmar o poder disruptivo previamente previsto da mutación mt. A1557C en estruturas mitoribosómicas. Para as outras tres mutacións analizadas, sospeitamos que a mt. A801G ten pouco, ou ningún, poder disruptivo. Finalmente, sobre as mutacións mt. A827G e mt. C1226G non podemos afirmar máis aló do feito de que os datos apuntan a un potencial poder disruptivo en ámbolos dous casos, aínda que son necesarias máis análises tanto a nivel molecular en Homo sapiens como en organismos heterólogos, como a nivel estrutural mediante Análise Inferencial Heteróloga.[Abstract] Due to mitochondria's importance in the processes of cellular respiration and survival as well as ribosomes' importance in protein translation, mutations in mitochondrial DNA sequences coding for mitochondrial ribosomal RNAs could cause mitochondrial dysfunction and, ultimately, pathologies such as deafness. As a result of the growing number of three-dimensional structures of high-resolution mammalian mitoribosomes and heterologous ribosomes, the development of structural analysis software, and the establishment of study methods such as Heterologous Inferential Analysis, we can examine the mutations found and even infer their disruptive power and relationship with disease. Based on the premise that the ototoxic mutations found in human mitochondrial ribosomal RNAs could cause decreased mitochondrial fidelity due to increased error rates during the decoding process, and since it has so far not been possible to measure mitochondrial fidelity in vivo due to physical and methodological barriers to studying mitochondria within cellular systems, our group set out to determine the potential disruptive power of a cohort of 78 mutations found in the 12S and 16S mitochondrial ribosomal RNA genes that have been linked (or at least are suspected to be linked) to deafness. Of the 78 mutations (see Appendix) on which we focused almost exclusively on performing a conservation analysis, all those that cannot be considered universally conserved were discarded in order to continue with a slightly more in-depth structural analysis. Thus, of the four mutations finally selected, mt. A801G, mt. A827G, mt. C1226G and mt. A1557C, we could confirm the previously predicted disruptive power of the mt. A1557C mutation in the mitoribosomal structures. For the other three mutations analyzed, we suspect that mt. A801G has little, if any, disruptive power. Finally, regarding the mt. A827G and mt. C1226G mutations, we couldn´t affirm beyond the fact that the data point to a potential disruptive power in both cases, although further analysis would be necessary both at the molecular level in Homo sapiens and in heterologous organisms, as well as at the structural level using Heterologous Inferential Analysis.Traballo fin de mestrado (UDC.CIE). Bioloxía molecular, celular e xenética. Curso 2021/202

Classificação taxonómica de procariotas com base em sequências simuladas do gene 16S rRNA

Tese de mestrado, Bioinformática e Biologia Computacional (Bioinformática) Universidade de Lisboa, Faculdade de Ciências, 2017O estudo de fragmentos de DNA obtidos directamente de uma amostra ambiental é designado por metagenómica. A determinação da sequência de bases desses fragmentos pode ser obtida através da sequenciação de todos os fragmentos da amostra (sequenciação shotgun) ou de amplicões de genes marcadores, como por exemplo o gene 16S rRNA. Nos últimos anos, os estudos de metagenómica têm tido um desenvolvimento crescente em resultado da introdução de novas plataformas de sequenciação paralela massiva, que permitem obter várias centenas de gigabases de sequência por ensaio. Apesar do potencial de conhecimento científico que estes estudos vieram permitir, colocaram também novos desafios na análise do grande volume de dados obtido. Assim, a necessidade de análise de dados de sequenciação shotgun ou de amplicões do gene 16S rRNA despoletou o aparecimento de múltiplas ferramentas bioinformáticas que cobrem os diferentes níveis de análise de metagenomas, desde a avaliação da qualidade das leituras de sequenciação até à identificação de novos genes com relevância funcional. No presente trabalho reviram-se mais de uma centena de programas disponíveis no domínio público que podem ser aplicados à análise de dados de sequenciação de metagenomas, incluindo 91 programas que permitem a identificação taxonómica das leituras obtidas na sequenciação. No entanto, é um facto que programas distintos, aplicados ao mesmo conjunto de dados, podem produzir resultados diferentes. De forma a testar e comparar a performance dos programas de classificação taxonómica de leituras do gene 16S rRNA, foi desenvolvido um programa (sim16S) em linguagem Matlab que permite obter leituras simuladas de amplicões deste gene, escolhidos a partir de uma base de dados de sequências de referência usando oligonucleótidos introduzidos pelo utilizador. O sim16S produz outros ficheiros de dados, incluindo o número de leituras atribuídas a cada táxon dos 5 níveis taxonómicos desde o filo até ao género, e um relatório com diversas estatísticas. Neste trabalho, o sim16S foi utilizado para produzir diversos conjuntos de leituras de 2 amplicões do gene 16S rRNA e introduzir substituições de bases, de acordo com um modelo estatístico que simula a distribuição de erros de sequenciação. Com base nestes conjuntos de leituras, foram efectuadas 20 análises de classificação taxonómica em paralelo com os programas QIIME e mothur, que constituem os 2 programas mais citados neste âmbito na literatura científica. A análise de leituras sem erros de sequenciação mostrou que a exactidão da classificação taxonómica decresce em direcção aos níveis taxonómicos inferiores, mesmo utilizando as sequências que deram origem às leituras simuladas como base de dados de referência. A utilização de outras bases de dados nos 2 programas conduziu a um aumento significativo de táxones sem classificação taxonómica completa, em todos os níveis taxonómicos. A presença de 1, 2 ou 4 erros de sequenciação nas leituras não afectou a classificação taxonómica das leituras nos níveis de filo, classe e ordem em ambos os programas, relativamente à classificação das leituras sem erros. No entanto, a exactidão da classificação no mothur, nos restantes níveis taxonómicos, foi afectada na presença de ~1%, ~10% e 100% de leituras com 1 erro de sequenciação por leitura ou ~10% de leituras com 2 ou 4 erros por leitura. Pelo contrário, o QIIME apenas revelou uma exactidão inferior a 99% nos conjuntos de leituras com 100% de leituras com 1 erro, sugerindo que este programa é menos sensível à presença de erros de sequenciação do que o mothur. As análises efectuadas mostraram que o sim16S é uma ferramenta bioinformática útil para testar a performance da classificação taxonómica de diferentes programas existentes no domínio público. Além disso, o sim16S pode facilmente ser adaptado a outros genes procariotas ou eucariotas para os quais estejam disponíveis bases de dados de sequências de referência, podendo assim funcionar como uma ferramenta de âmbito geral no contexto dos estudos de metagenómica.The study of DNA fragments obtained directly from an environmental sample is called metagenomics. Determination of the sequence of bases of these fragments can be achieved by sequencing all fragments in the sample (shotgun sequencing) or amplicons derived from marker genes, such as the 16S rRNA gene. In recent years, metagenomics studies have been growing as a result of the introduction of new massive parallel sequencing platforms, which allow for several hundred gigabases of sequence per assay. Despite the potential of scientific knowledge that these studies allowed, they also posed new difficulties in the analysis of the large volume of data obtained. Thus, the need for analysis of shotgun sequencing or 16S rRNA gene amplicons triggered the emergence of multiple bioinformatics tools covering the different levels of metagenome analysis, ranging from the quality evaluation of sequencing reads to the identification of new genes with functional relevance. In the present work, more than 100 publicly available programs that can be applied to the analysis of metagenome sequencing data were analyzed, including 91 programs that allow taxonomic identification of sequencing reads. However, it is a fact that distinct programs, applied to the same set of data, can produce different results. In order to test and compare the performance of the 16S rRNA gene taxonomic classification tools, a program (sim16S) was developed in Matlab language that allows obtaining simulated reads of gene amplicons, chosen from a database of sequences using oligonucleotides introduced by the user. sim16S produces several data files, including the number of reads assigned to each taxon from the 5 taxonomic levels from phylum to genus, and a report with various statistics. In this work, sim16S was used to produce several sets of reads of 2 amplicons of the 16S rRNA gene, in which base substitutions were introduced according to a statistical model that simulates the distribution of sequencing errors. Based on sim16S datasets, 20 taxonomic classification analyzes were carried out in parallel with QIIME and mothur, which constitute the 2 most cited programs in the scientific literature in this field. Analysis of reads without sequencing errors showed that the accuracy of the taxonomic classification decreases toward the lower taxonomic levels, even using the sequences that gave rise to the simulated reads as a reference sequence database. The use of other databases in the two programs led to a significant increase in incomplete classified taxa at all taxonomic levels. The presence of 1, 2 or 4 sequencing errors in the reads did not affect the taxonomic classification at the phylum, class and order levels in both programs, relative to the classification of error-free reads. However, the accuracy of mothur classification at the remaining taxonomic levels was affected in the presence of ~1%, ~10% and 100% of reads with 1 sequencing error per read or in the presence of ~10% of reads with 2 or 4 errors per read. In contrast, QIIME only showed an accuracy of less than 99% in read sets with 100% of reads with 1 error, suggesting that this program is less sensitive to the presence of sequencing errors than mothur. These studies showed that sim16S is a useful bioinformatics tool to test the accuracy of the taxonomic classification of different programs available in the public domain. In addition, sim16S can easily be adapted to other prokaryotic or eukaryotic genes for which sequence databases are available and can thus function as a general tool in the context of metagenomics studies

The Antibiotic Resistance Growth Plate (ARGP) as an experimental evolution tool to explore the phenotypic and genotypic mutational pathways underlying the emergence of antimicrobial resistance in 'Escherichia coli'

The increasing threat of an antimicrobial resistance crisis is a significant global concern. Antimicrobial treatment failures are worsened by the rapid evolution of resistance amongst bacterial pathogens. Therefore, in addition to developing novel antimicrobial agents, there is growing interest in exploring the underlying genotypic factors of resistance evolution. Traditionally, such studies have focused heavily on well-established mechanisms of acquired resistance involving horizontal gene transfer, yet the evolution of resistance through the acquisitions of mutations is yet to be fully elucidated. Adaptive laboratory evolution studies have provided insights into the genetic basis of adaptation through the direct observation of the evolutionary process. Experimental evolution has advanced from serial passage in well mixed systems to the incorporation of spatiotemporal antibiotic concentration gradients. During this study the Antibiotic Resistance Growth Plate (ARGP) was developed as a simple experimental tool to explore the ability of bacteria to evolve resistance across an antibiotic landscape. The device (90mm × 15mm) facilitates the direct observation of the evolutionary trajectories of mutational lineages within a circular format supporting the radial growth and the exploration of phenotypic space within bacterial populations. Whole genome sequencing of the evolved resistant strains, identified key mutations in the 16s rRNA genes and the fusA gene encoding elongation factor-G, specific to antimicrobial agent gentamicin. Additional gene sequencing revealed parallel gentamicin resistant bacterial populations, evolved identical mutations within the fusA gene. Combined bioinformatic, phylogenetic and molecular docking analysis uncovered the biological significance of the fusA gene in the mutational pathways of gentamicin resistance in E. coli MG1655 in vitro. In contrast, the observed biological fitness costs associated with the acquisition of resistance conferring mutations, emphasised why such costly resistant genotypes were unidentified in natural and clinical settings. This study has established an experimental evolution model to explore the mutational pathways underlying antimicrobial resistance development in vitro. The ARGP offers a platform for the continued research into the acquisition of antimicrobial resistance through mutations, for more complex bacterial pathogens selected against a range of antimicrobial agents. As a tool, the ARGP can be utilised to inform therapeutic decisions based on the evolutionary risk management, provide new opportunities within the field of drug development and holds scope for its application within an educational setting