Synonymous Genes Explore Different Evolutionary Landscapes

The evolutionary potential of a gene is constrained not only by the amino acid sequence of its product, but by its DNA sequence as well. The topology of the genetic code is such that half of the amino acids exhibit synonymous codons that can reach different subsets of amino acids from each other through single mutation. Thus, synonymous DNA sequences should access different regions of the protein sequence space through a limited number of mutations, and this may deeply influence the evolution of natural proteins. Here, we demonstrate that this feature can be of value for manipulating protein evolvability. We designed an algorithm that, starting from an input gene, constructs a synonymous sequence that systematically includes the codons with the most different evolutionary perspectives; i.e., codons that maximize accessibility to amino acids previously unreachable from the template by point mutation. A synonymous version of a bacterial antibiotic resistance gene was computed and synthesized. When concurrently submitted to identical directed evolution protocols, both the wild type and the recoded sequence led to the isolation of specific, advantageous phenotypic variants. Simulations based on a mutation isolated only from the synthetic gene libraries were conducted to assess the impact of sub-functional selective constraints, such as codon usage, on natural adaptation. Our data demonstrate that rational design of synonymous synthetic genes stands as an affordable improvement to any directed evolution protocol. We show that using two synonymous DNA sequences improves the overall yield of the procedure by increasing the diversity of mutants generated. These results provide conclusive evidence that synonymous coding sequences do experience different areas of the corresponding protein adaptive landscape, and that a sequence's codon usage effectively constrains the evolution of the encoded protein

High-Density Transcriptional Initiation Signals Underline Genomic Islands in Bacteria

Genomic islands (GIs), frequently associated with the pathogenicity of bacteria and having a substantial influence on bacterial evolution, are groups of “alien” elements which probably undergo special temporal–spatial regulation in the host genome. Are there particular hallmark transcriptional signals for these “exotic” regions? We here explore the potential transcriptional signals that underline the GIs beyond the conventional views on basic sequence composition, such as codon usage and GC property bias. It showed that there is a significant enrichment of the transcription start positions (TSPs) in the GI regions compared to the whole genome of Salmonella enterica and Escherichia coli. There was up to a four-fold increase for the 70% GIs, implying high-density TSPs profile can potentially differentiate the GI regions. Based on this feature, we developed a new sliding window method GIST, Genomic-island Identification by Signals of Transcription, to identify these regions. Subsequently, we compared the known GI-associated features of the GIs detected by GIST and by the existing method Islandviewer to those of the whole genome. Our method demonstrates high sensitivity in detecting GIs harboring genes with biased GI-like function, preferred subcellular localization, skewed GC property, shorter gene length and biased “non-optimal” codon usage. The special transcriptional signals discovered here may contribute to the coordinate expression regulation of foreign genes. Finally, by using GIST, we detected many interesting GIs in the 2011 German E. coli O104:H4 outbreak strain TY-2482, including the microcin H47 system and gene cluster ycgXEFZ-ymgABC that activates the production of biofilm matrix. The aforesaid findings highlight the power of GIST to predict GIs with distinct intrinsic features to the genome. The heterogeneity of cumulative TSPs profiles may not only be a better identity for “alien” regions, but also provide hints to the special evolutionary course and transcriptional regulation of GI regions

A Systematic Literature Review of Sport and Physical Activity Participation in Culturally and Linguistically Diverse (CALD) Migrant Populations

Culturally and linguistically diverse (CALD) migrants face significant health risks as they adapt to new cultures. These risks are exacerbated by their limited participation in preventative behaviours such as sports and physical activity. The review aimed to identify studies that examined the correlates of sport and physical activity participation in migrants. The systematic review identified 72 papers, including 6 interventions, 18 qualitative and 48 quantitative studies. The 44 identified correlates highlight the complexities involved in working with migrants. The correlates were grouped in four themes using the social ecological model; acculturation, demographic, psychosocial and environmental/organisational. The social ecological model identified general correlates such as social support and safety. However, there were unique correlates relating to individuals who are facing cultural changes such as acculturation and language. Overall, there is a lack of contextualisation of CALD migrants’ sport and physical activity experiences because many studies fail to consider acculturation comprehensively. Initially titled: A review of sport and physical activity in culturally and linguistically diverse migrant

Family-run farm enterprises, territories and policies in Argentina

Family-run farm enterprises, territories and policies in Argentin