How Many Peas in a Pod? Legume Genes Responsible for Mutualistic Symbioses Underground

The nitrogen-fixing symbiosis between legume plants and Rhizobium bacteria is the most prominent plant–microbe endosymbiotic system and, together with mycorrhizal fungi, has critical importance in agriculture. The introduction of two model legume species, Lotus japonicus and Medicago truncatula, has enabled us to identify a number of host legume genes required for symbiosis. A total of 26 genes have so far been cloned from various symbiotic mutants of these model legumes, which are involved in recognition of rhizobial nodulation signals, early symbiotic signaling cascades, infection and nodulation processes, and regulation of nitrogen fixation. These accomplishments during the past decade provide important clues to understanding not only the molecular mechanisms underlying plant–microbe endosymbiotic associations but also the evolutionary aspects of nitrogen-fixing symbiosis between legume plants and Rhizobium bacteria. In this review we survey recent progress in molecular genetic studies using these model legumes

In Silico Insights into the Symbiotic Nitrogen Fixation in Sinorhizobium meliloti via Metabolic Reconstruction

BACKGROUND: Sinorhizobium meliloti is a soil bacterium, known for its capability to establish symbiotic nitrogen fixation (SNF) with leguminous plants such as alfalfa. S. meliloti 1021 is the most extensively studied strain to understand the mechanism of SNF and further to study the legume-microbe interaction. In order to provide insight into the metabolic characteristics underlying the SNF mechanism of S. meliloti 1021, there is an increasing demand to reconstruct a metabolic network for the stage of SNF in S. meliloti 1021. RESULTS: Through an iterative reconstruction process, a metabolic network during the stage of SNF in S. meliloti 1021 was presented, named as iHZ565, which accounts for 565 genes, 503 internal reactions, and 522 metabolites. Subjected to a novelly defined objective function, the in silico predicted flux distribution was highly consistent with the in vivo evidences reported previously, which proves the robustness of the model. Based on the model, refinement of genome annotation of S. meliloti 1021 was performed and 15 genes were re-annotated properly. There were 19.8% (112) of the 565 metabolic genes included in iHZ565 predicted to be essential for efficient SNF in bacteroids under the in silico microaerobic and nutrient sharing condition. CONCLUSIONS: As the first metabolic network during the stage of SNF in S. meliloti 1021, the manually curated model iHZ565 provides an overview of the major metabolic properties of the SNF bioprocess in S. meliloti 1021. The predicted SNF-required essential genes will facilitate understanding of the key functions in SNF and help identify key genes and design experiments for further validation. The model iHZ565 can be used as a knowledge-based framework for better understanding the symbiotic relationship between rhizobia and legumes, ultimately, uncovering the mechanism of nitrogen fixation in bacteroids and providing new strategies to efficiently improve biological nitrogen fixation

Behavioural indicators of welfare in farmed fish

Behaviour represents a reaction to the environment as fish perceive it and is therefore a key element of fish welfare. This review summarises the main findings on how behavioural changes have been used to assess welfare in farmed fish, using both functional and feeling-based approaches. Changes in foraging behaviour, ventilatory activity, aggression, individual and group swimming behaviour, stereotypic and abnormal behaviour have been linked with acute and chronic stressors in aquaculture and can therefore be regarded as likely indicators of poor welfare. On the contrary, measurements of exploratory behaviour, feed anticipatory activity and reward-related operant behaviour are beginning to be considered as indicators of positive emotions and welfare in fish. Despite the lack of scientific agreement about the existence of sentience in fish, the possibility that they are capable of both positive and negative emotions may contribute to the development of new strategies (e. g. environmental enrichment) to promote good welfare. Numerous studies that use behavioural indicators of welfare show that behavioural changes can be interpreted as either good or poor welfare depending on the fish species. It is therefore essential to understand the species-specific biology before drawing any conclusions in relation to welfare. In addition, different individuals within the same species may exhibit divergent coping strategies towards stressors, and what is tolerated by some individuals may be detrimental to others. Therefore, the assessment of welfare in a few individuals may not represent the average welfare of a group and vice versa. This underlines the need to develop on-farm, operational behavioural welfare indicators that can be easily used to assess not only the individual welfare but also the welfare of the whole group (e. g. spatial distribution). With the ongoing development of video technology and image processing, the on-farm surveillance of behaviour may in the near future represent a low-cost, noninvasive tool to assess the welfare of farmed fish.Fundação para a Ciência e Tecnologia, Portugal [SFRH/BPD/42015/2007]info:eu-repo/semantics/publishedVersio