Assessment of phylo-functional coherence along the bacterial phylogeny and taxonomy

In this report we use available curated phylogenies, taxonomy, and genome annotations to assess the phylogenetic and gene content similarity associated with each different taxon and taxonomic rank. Subsequently, we employ the same data to assess the frontiers of functional coherence along the bacterial phylogeny. Our results show that within-group phylogenetic and gene content similarity of taxa in the same rank are not homogenous, and that these values show extensive overlap between ranks. Functional coherence along the 16S rRNA gene-based phylogeny was limited to 44 particular nodes presenting large variations in phylogenetic depth. For instance, the deep subtree affiliated to class Actinobacteria presented functional coherence, while the shallower family Enterobacteriaceae-affiliated subtree did not. On the other hand, functional coherence along the genome-based phylogeny delimited deep subtrees affiliated to phyla Actinobacteriota, Deinococcota, Chloroflexota, Firmicutes, and a subtree containing the rest of the bacterial phyla. The results presented here can be used to guide the exploration of results in many microbial ecology and evolution research scenarios. Moreover, we provide dedicated scripts and files that can be used to continue the exploration of functional coherence along the bacterial phylogeny employing different parameters or input data (https://git.io/Jec5U).

Assessment of phylo-functional coherence along the bacterial phylogeny and taxonomy

ABSTRACTIn this report we use available curated phylogenies, taxonomy, and genome annotations to assess the phylogenetic and gene content similarity associated with each different taxa and taxonomic rank. Subsequently, we employ the same data to delimit the frontiers of functional coherence along the bacterial phylogeny. Our results show that within-group phylogenetic and gene content similarity of taxa in the same rank are not homogenous, and that these values show extensive overlap between ranks. Functional coherence along the 16S rRNA gene-based phylogeny was limited to 44 particular nodes presenting large variations in phylogenetic depth. For instance, the deep subtree affiliated to class Actinobacteria presented functional coherence, while the shallower family Enterobacteriaceae-affiliated subtree did not. On the other hand, functional coherence along the genome-based phylogeny delimited deep subtrees affiliated to phyla Actinobacteriota, Deinococcota, Chloroflexota, Firmicutes, and a subtree containing the rest of the bacterial phyla.IMPORTANCEWhile bacterial taxonomy and phylogeny resources as well as related bioinformatic tools continue to improve, the question remains as to how they should best be employed in studies using 16S rRNA gene surveys to assess bacteria-ecosystem relationships, a widespread approach. The results contained herein lead to the recommendation that all ranks from genus to class/phylum be employed if using taxonomic binning in the analysis of 16S rRNA gene surveys. With regards to the use of phylogeny or clustering-based approaches, single or arbitrary tree topology or sequence distance thresholds should not be employed. Instead, the results presented here can be used to obtain more meaningful results in many microbial ecology and evolution research scenarios. Moreover, we provide dedicated scripts and files that can be used to continue the exploration of functional coherence along the bacterial phylogeny employing different parameters or input data.

A Contribuição dos Recursos de Coesão para o Leitor Durante o Processo de Construção da Representação Textual

Partindo do pressuposto de que, a partir de fragmentos do texto, o usuário da língua aplica estratégias para compreendê-lo (DIJK e KINTSCH, 1983), notamos que os conectivos podem influenciar na construção representacional do texto. A representação textual, construída durante a leitura (processamento) do texto, precisa ser coerente, neste sentido, os conectivos, existindo em função coerência textual, manifestam, explicitamente, como o leitor deverá relacionar os conteúdos dispostos em um texto, por isso devem ser relevantes para o leitor durante o processo de estabelecimento da coerência textual. A fim de refletirmos sobre a contribuição dos recursos de coesão durante a compreensão do texto, propomos, no presente trabalho, um diálogo entre os textos Strategies of Discourse Comprehension (DIJK e KINTSCH,1983) e The Semantics and Pragmatics of Functional Coherence in Discourse. (DIJK, 1980)- no que concerne à necessidade de construção representacional do texto- e a pesquisa psicolinguística sobre processamento textual, mais especificamente o processamento de conectivos, proposta e reportada por Sanders e Noordman e Vonk (1996). Por meio dos resultados encontrados pelos autores (NOORDMAN e VONK, 1996) percebemos contribuições- significativas estatisticamente- dos recursos de coesão, do tipo conectivos, durante o processamento textual que atestariam a relevância destes itens linguísticos na construção da representação mental do texto.

Modules of co-occurrence in the cyanobacterial pan-genome

ABSTRACTThe increasing availability of fully sequenced cyanobacterial genomes opens unprecedented opportunities to investigate the manifold adaptations and functional relationships that determine the genetic content of individual bacterial species. Here, we use comparative genome analysis to investigate the cyanobacterial pan-genome based on 77 strains whose complete genome sequence is available. Our focus is the co-occurrence of likely ortholog genes, denoted as CLOGs. We conjecture that co-occurrence CLOGs is indicative of functional relationships between the respective genes. Going beyond the analysis of pair-wise co-occurrences, we introduce a novel network approach to identify modules of co-occurring ortholog genes. Our results demonstrate that these modules exhibit a high degree of functional coherence and reveal known as well as previously unknown functional relationships. We argue that the high functional coherence observed for the extracted modules is a consequence of the similar-yet-diverse nature of the cyanobacterial phylum. We provide a simple toolbox that facilitates further analysis of our results with respect to specific cyanobacterial genes of interest.