Bioinformatic discovery of type 11 secretion system (T11SS) cargo across the Proteobacteria

利用生物信息学方法发现变形菌中 11 型分泌系统 (T11SS) 的货物

阅读:3

Abstract

Type 11 secretion systems (T11SS) are broadly distributed amongst Proteobacteria, with more than 3,000 T11SS family outer membrane proteins (OMPs) comprising ten major sequence similarity network clusters. Of these, only seven, all from animal-associated cluster 1, have been experimentally verified as secretins of cargo, including adhesins, haemophores and metal-binding proteins. To identify novel cargo of a more diverse set of T11SS, we identified gene families co-occurring in gene neighbourhoods with either cluster 1 or marine microbe-associated cluster 3 T11SS OMP genes. We developed bioinformatic controls to ensure that perceived co-occurrences are specific to T11SS, and not general to OMPs. We found that both cluster 1 and cluster 3 T11SS OMPs frequently co-occur with single-carbon metabolism and nucleotide synthesis pathways, but that only cluster 1 T11SS OMPs had significant co-occurrence with metal and haem pathways, as well as with mobile genetic islands, potentially indicating the diversified function of this cluster. Cluster 1 T11SS co-occurrences included 2,556 predicted cargo proteins, unified by the presence of a C-terminal β-barrel domain, which fall into 141 predicted UniRef50 clusters and approximately ten different architectures: four similar to known cargo and six uncharacterized types. We experimentally demonstrate T11SS-dependent secretion of an uncharacterized cargo type with homology to plasmin-sensitive protein. Unexpectedly, genes encoding marine cluster 3 T11SS OMPs only rarely co-occurred with the C-terminal β-barrel domain and instead frequently co-occurred with DUF1194-containing genes. Overall, our results show that with sufficiently large-scale and controlled genomic data, T11SS-dependent cargo proteins can be accurately predicted.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。