Understanding the principles that govern community assemblages is a central goal of ecology. There is limited experimental evidence in natural settings showing that microbial assembly in communities are influenced by antagonistic interactions. We, therefore, analyzed antagonism among bacterial isolates from a taxonomically related bacterial guild obtained from five sites in sediments from a fresh water system. We hypothesized that if antagonistic interactions acted as a shaping force of the community assembly, then the frequency of resistance to antagonism among bacterial isolates originating from a given site would be higher than the resistance to conspecifics originating from a different assemblage. Antagonism assays were conducted between 78 thermoresistant isolates, of which 72 were Bacillus spp. Sensitive, resistant and antagonistic isolates co-occurred at each site, but the within-site frequency of resistance observed was higher than that observed when assessed across-sites. We found that antagonism results from bacteriocinlike substances aimed at the exclusion of conspecifics. More than 6000 interactions were scored and described by a directed network with hierarchical structure that exhibited properties that resembled a food chain, where the different Bacillus taxonomic groups occupied specific positions. For some tested interacting pairs, the unidirectional interaction could be explained by competition that inhibited growth or completely excluded one of the pair members. This is the first report on the prevalence and specificity of Bacillus interactions in a natural setting and provides evidence for the influence of bacterial antagonist interactions in the assemblage of a taxonomically related guild in local communities.

We present RegulomePA, a database that contains biological information on regulatory interactions between transcription factors (TFs), sigma factor (SFs) and target genes in Pseudomonas aeruginosa PAO1. RegulomePA consists of 4827 regulatory interactions between 2831 nodes, which represent the interactions of TFs and SFs with their target genes, from the total of predicted RegulomePA including 27.27% of the TFs, 54.16% of SFs and 50.8% of the total genes. Each entry in the database corresponds to one node in the network and provides comprehensive details about the gene and its regulatory interactions such as gene description, nucleotide sequence, genome-strand position and links to other databases as well as the type of regulation it exerts or to which it is being subject (repression or activation), the associated experimental evidence and references, and topological information. Additionally, RegulomePA provides a way to recover information on the regulatory circuits of the network to which a gene pertains and also makes available the source codes to analyze the topology of any other regulatory network. The database will be updated yearly, by our team, with the contributions from ourselves and users, since the users are provided with an interactive platform where they can add interactions to the regulatory network feeding it with their respective references. Database URL: www.regulome.pcyt.unam.mx.

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In this note we prove that the vertex energy of a graph, as defined in [2], can be calculated in terms of a Coulson integral formula. We present examples of how this formula can be used, and we show some applications to bipartite graphs.

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