Metagenomics and Other Omics Approaches to Bacterial Communities and Antimicrobial Resistance Assessment in Aquacultures

The shortage of wild fishery resources and the rising demand for human nutrition has driven a great expansion in aquaculture during the last decades in terms of production and economic value. As such, sustainable aquaculture production is one of the main priorities of the European Union’s 2030 agenda. However, the intensification of seafood farming has resulted in higher risks of disease outbreaks and in the increased use of antimicrobials to control them. The selective pressure exerted by these drugs provides the ideal conditions for the emergence of antimicrobial resistance hotspots in aquaculture facilities. Omics technology is an umbrella term for modern technologies such as genomics, metagenomics, transcriptomics, proteomics, culturomics, and metabolomics. These techniques have received increasing recognition because of their potential to unravel novel mechanisms in biological science. Metagenomics allows the study of genomes in microbial communities contained within a certain environment. The potential uses of metagenomics in aquaculture environments include the study of microbial diversity, microbial functions, and antibiotic resistance genes. A snapshot of these high throughput technologies applied to microbial diversity and antimicrobial resistance studies in aquacultures will be presented in this review.info:eu-repo/semantics/publishedVersio

CPVIB-1, a GAGA Regulator of TOR Signaling Pathways in the Chestnut Blight Pathogen Cryphonectria Parasitica

Cryphonectria parasitica is the causal agent of chestnut blight, which devastated the American Chestnut tree population in the early 20th century. The discovery of hypoviruses that reduce the severity of the chestnut blight infection offers the potential for biological control. However, the spread of the hypoviruses is hampered by a diverse genetically controlled nonself-recognition system, vegetative incompatibility (vic). CPVIB-1 was identified as a transcription regulator playing an important role in the programmed cell death response to this stimulus. In this study, we have found that CPVIB-1 is ubiquitin-decorated which might lead to its degradation in the proteasome pathway. RNA-Seq and ChIP-Seq were used to further explore the downstream targets of CPVIB-1 that mediate the various metabolic changes that lead to the altered phenotype of the Δcpvib-1 mutant. Due to inaccuracies in the prior annotation, we performed a genome re-annotation to improve the accuracy using a MAKER2-two-pass pipeline. To validate the improvement a second pipeline, PEPA, was developed to compare quality metrics between the old and new annotations. Approximately 1/3 of the original annotations from 2009 were found to be inaccurate. Experimental confirmation by testing 27 predicted genes using a diagnostic PCR protocol to differentiate between prior and new transcript structures showed that over 80 % of tested genome locations supported for the new annotation. Using rapamycin treatment to mimic stimulation of the vic response and applying the RNA-seq and ChIP-seq data to this new information, we found that CPVIB-1 is related to TOR signaling pathways, promoting autophagy and the proteasome pathway, but repressing carbon metabolism, protein and lipid biosynthesis. In depth analysis of CPVIB-1-bound DNA targets showed that this protein is a member of the GAGA regulator family, a group of multifaceted transcription factors with diverse roles in gene activation and repression, maintenance of mitosis, and cell development. Following treatment with rapamycin the recognition sequence bound by CPBVIB-1 was altered leading to the regulation of different suite of genes with diverse metabolic functions. Ultimately, we have developed a revised model of TOR signaling pathway where TORC1 and TORC2 signaling pathways are connected by the action of CPVIB1

Reconstructing of the metabolic network of Lactobacillus rhamnosus

Dissertação de mestrado em BioinformaticsWith the recent growth in genomics research, complete genomic sequences of a multitude of species are assembled at an unprecedented rate(The Cost of Sequencing a Human Genome n.d.). Therefore, it is evident that full comprehension of encoded functionality is displaced from that increased knowledge rate. Genome-scale metabolic network reconstructions try to achieve a complete understanding of the metabolic features of an organism by assembly a network of metabolic reactions catalyzed by enzymes and transporters found on the annotations made for the genome sequence(Palsson 2009). Such gene annotations are often generated by applying prior knowledge to the genomic sequence The reconstruction process of a genome-scale metabolic model encompasses four steps, namely: (1) Genome Sequencing; (2) assembling the genome-wide metabolic network; (3) Conversion of the network to a stoichiometric model ; (4)metabolic model validation(Merlin Homepage n.d.). In this thesis, the main aim is to use the genome sequence of Lactobacillus rhamnosus GG and data generated at LNEG to reconstruct the metabolic network of L. rhamnosus. The main tasks was the accomplishment of the metabolically annotate the genome and perform a preliminary analysis of the resulting metabolic network(Lin, Bennett, and San 2005; Lopes da Silva et al. 2013). In spite of the work done, there is still a long way to go until the construction of a functional model. The main steps still to be taken are the Transport prediction, removal of the dead ends, compartmentalization and the assembly of model. Another improvement for this work would be the validation of the model whit real data for L. rhamnosus GG, instead of the data from the Lactobacillus rhamnosus strain C83.Com o recente crescimento da pesquisa ao nível genómico, tem levado ao aparecimento inúmeras sequencias genómicas completas das mais variadas espécies(The Cost of Sequencing a Human Genome n.d.). Portanto, é evidente que a compreensão completa da funcionalidade do genoma é desproporcional à taxa que se gera o conhecimento. As reconstruções de redes metabólicas à escala genómica tentam alcançar uma compreensão completa das características metabólicas de um organismo através da montagem de uma rede de reações metabólicas catalisadas por enzimas e transportadores encontradas nas anotações feitas para o genoma(Palsson 2009). O processo de construção de um modelo metabólico à escala genómica abrange quatro etapas: (1) Sequenciamento do Genoma/Anotação; (2) montagem da rede metabólica do genoma; (3) Conversão da rede para um modelo estequiométrico; (4) validação do modelo metabólico(Merlin Homepage n.d.). O principal objetivo desta tese é usando a sequência genómica d Lactobacillus rhamnosus GG e os dados gerados na LNEG para construir a rede metabólica de L. rhamnosus. As principais tarefas foram a anotação do genoma e realização uma análise preliminar da rede metabólica resultante(Lin, Bennett, and San 2005; Lopes da Silva et al. 2013). Apesar do trabalho realizado, ainda há um longo caminho a percorrer até a construção de um modelo funcional. Os principais passos a serem tomados são a previsão dos transportes, a remoção dos dead ends, a compartimentalização e a criação do modelo. Outra melhoria para este trabalho seria a validação do modelo com dados reais para L. rhamnosus GG, ao invés dos dados da strain Lactobacillus rhamnosus C83