Understanding the factors that modulate bacterial community assembly in natural soils is a longstanding challenge in microbial community ecology. In this work, we compared two microbial co-occurrence networks representing bacterial soil communities from two different sections of a pH, temperature and humidity gradient occurring along a western slope of the Andes in the Atacama Desert. In doing so, a topological graph alignment of co-occurrence networks was used to determine the impact of a shift in environmental variables on OTUs taxonomic composition and their relationships. We observed that a fraction of association patterns identified in the co-occurrence networks are persistent despite large environmental variation. This apparent resilience seems to be due to: (1) a proportion of OTUs that persist across the gradient and maintain similar association patterns within the community and (2) bacterial community ecological rearrangements, where an important fraction of the OTUs come to fill the ecological roles of other OTUs in the other network. Actually, potential functional features suggest a fundamental role of persistent OTUs along the soil gradient involving nitrogen fixation. Our results allow identifying factors that induce changes in microbial assemblage configuration, altering specific bacterial soil functions and interactions within the microbial communities in natural environments.

Background: Grapevine (Vitis viniferaL.) is the most important Mediterranean fruit crop, used to produce both wine and spirits as well as table grape and raisins. Wine and table grape cultivars represent two divergent germplasm pools with different origins and domestication history, as well as differential characteristics for berry size, cluster architecture and berry chemical profile, among others. ‘Sultanina’ plays a pivotal role in modern table grape breeding providing the main source of seedlessness. This cultivar is also one of the most planted for fresh consumption and raisins production. Given its importance, we sequenced it and implemented a novel strategy for thede novoassembly of its highly heterozygous genome.Results: Our approach produced a draft genome of 466 Mb, recovering 82% of the genes present in the grapevine reference genome; in addition, we identified 240 novel genes. A large number of structural variants and SNPs were identified. Among them, 45 (21 SNPs and 24 INDELs) were experimentally confirmed in ‘Sultanina’ and six SNPs in other 23 table grape varieties. Transposable elements corresponded toca.80% of the repetitive sequences involved in structural variants and more than 2,000 genes were affected in their structure by these variants. Some of these genes are likely involved in embryo development, suggesting that they may contribute to seedlessness, a key trait for table grapes.Conclusions: This work produced the first structural variants and SNPs catalog for grapevine, constituting a novel and very powerful tool for genomic studies in this key fruit crop, particularly useful to support marker assisted breeding in table grapes.

Piscirickettsiosis or Salmonid Rickettsial Septicaemia (SRS) is a bacterial disease that has a major economic impact on the Chilean salmon farming industry. Despite the fact that Piscirickettsia salmonis has been recognized as a major fish pathogen for over 20 years, the molecular strategies underlying the fish response to infection and the bacterial mechanisms of pathogenesis are poorly understood. We analysed and compared the head kidney transcriptional response of Atlantic salmon (Salmo salar) families with different levels of susceptibility to P. salmonis infection in order to reveal mechanisms that might confer infection resistance. We ranked forty full-sibling Atlantic salmon families according to accumulated mortality after a challenge with P. salmonis and selected the families with the lowest and highest cumulative mortalities for microarray gene expression analysis. A comparison of the response to P. salmonis infection between low and high susceptibility groups identified biological processes presumably involved in natural resistance to the pathogen. In particular, expression changes of genes linked to cellular iron depletion, as well as low iron content and bacterial load in the head kidney of fish from low susceptibility families, suggest that iron-deprivation is an innate immunity defence mechanism against P. salmonis. To complement these results, we predicted a set of iron acquisition genes from the P. salmonis genome. Identification of putative Fur boxes and expression of the genes under iron-depleted conditions revealed that most of these genes form part of the Fur regulon of P. salmonis. This study revealed, for the first time, differences in the transcriptional response to P. salmonis infection among Atlantic salmon families with varied levels of susceptibility to the infection. These differences correlated with changes in the abundance of transcripts encoding proteins directly and indirectly involved in the immune response; changes that highlighted the role of nutritional immunity through iron deprivation in host defence mechanisms against P. salmonis. Additionally, we found that P. salmonis has several mechanisms for iron acquisition, suggesting that this bacterium can obtain iron from different sources, including ferric iron through capturing endogenous and exogenous siderophores and ferrous iron. Our results contribute to determining the underlying resistance mechanisms of Atlantic salmon to P. salmonis infection and to identifying future treatment strategies.

Nannochloropsis salina (= Eustigmatophyceae) is a marine microalga which has become a biotechnological target because of its high capacity to produce polyunsaturated fatty acids and triacylglycerols. It has been used as a source of biofuel, pigments and food supplements, like Omega 3. Only some Nannochloropsis species have been sequenced, but none of them benefit from a genome-scale metabolic model (GSMM), able to predict its metabolic capabilities. We present iNS934, the first GSMM for N. salina, including 2345 reactions, 934 genes and an exhaustive description of lipid and nitrogen metabolism. iNS934 has a 90% of accuracy when making simple growth/no-growth predictions and has a 15% error rate in predicting growth rates in different experimental conditions. Moreover, iNS934 allowed us to propose 82 different knockout strategies for strain optimization of triacylglycerols. iNS934 provides a powerful tool for metabolic improvement, allowing predictions and simulations of N. salina metabolism under different media and genetic conditions. It also provides a systemic view of N. salina metabolism, potentially guiding research and providing context to -omics data.