Species-specific transcriptomic network inference of interspecies interactions

Abstract

The advent of high-throughput 'omics approaches coupled with computational analyses to reconstruct individual genomes from metagenomes provides a basis for species-resolved functional studies. Here, a mutual information approach was applied to build a gene association network of a commensal consortium, in which a unicellular cyanobacterium Thermosynechococcus elongatus BP1 supported the heterotrophic growth of Meiothermus ruber strain A. Specifically, we used the context likelihood of relatedness (CLR) algorithm to generate a gene association network from 25 transcriptomic datasets representing distinct growth conditions. The resulting interspecies network revealed a number of linkages between genes in each species. While many of the linkages were supported by the existing knowledge of phototroph-heterotroph interactions and the metabolism of these two species several new interactions were inferred as well. These include linkages between amino acid synthesis and uptake genes, as well as carbohydrate and vitamin metabolism, terpenoid metabolism and cell adhesion genes. Further topological examination and functional analysis of specific gene associations suggested that the interactions are likely to center around the exchange of energetically costly metabolites between T. elongatus and M. ruber. Both the approach and conclusions derived from this work are widely applicable to microbial communities for identification of the interactions between species and characterization of community functioning as a whole.

Fig. 1

Methodology of Cross-Species Network. Both T. elongatus and M. ruber were cultured under 25 different environmental conditions and RNA-seq data was collected. Transcriptomic data was used to build 500 incident networks with random removals of 20% of the data for each incident network. These 500 incident networks were then combined into a single consensus network that averaged mutual information scores for all gene pairs. Transcriptomic data was also used to generate a Pearson correlation coefficient dataset. Both data types were combined to assign positive (orange) or negative (blue) values to the edges in the CLR network

Fig. 2

Degree values of T. elongatus and M. ruber functions. a Average normalized degree values for genes in each of the functions shown on the x-axis were calculated for a network comprised only of M. ruber genes (red hatched bars), comprised only of T. elongatus genes (hatched green bars) or for M. ruber (filled red bars) or T. elongatus (filled green bars) genes in the cross-species network. Degree values are shown on the y-axis and are normalized to the total nodes in the network. b Same as a but using betweenness as a measure of centrality rather than degree

Fig. 3

Number of edges between functions of T. elongatus and M. ruber. a A network with a Z-score cutoff of 2.5 was used to increase total edges and gain a more detailed view of interactions. The number of positive edges for each function in T. elongatus (x-axis) and M. ruber (y-axis) is indicated, darker colors indicate more edges. Meio refers to M. ruber and BP1 to T. elongatus. b Identical to a but showing negative edges for each function in T. elongatus (x-axis) and M. ruber (y-axis), darker colors indicate more edges

Fig. 4

Specific edges between nitrogen metabolism and unknown genes of M. ruber and T. elongatus. a Ammonium transporters of M. ruber (amt) show negative edges to amino acid synthesis genes of T. elongatus (green circles) while M. ruber peptide transporters had positive edges to amino acid synthesis genes of T. elongatus. b Uncharacterized genes of M. ruber (red circles) show a large number of edges indicating positive correlation (direct edges, orange lines) and negative correlation (inverse edges, blue lines). Many of these edges are to the same T. elongatus genes

Fig. 5

Conceptual model of putative interactions and coordination between T. elongatus and M. ruber. Genes with specific edges in M. ruber and T. elongatus are shown, as well as the putative metabolite and nutrient transfers they are involved in. Amino acid synthesis genes of T. elongatus are linked to peptide transporters of M. ruber as are B12 synthesis genes in T. elongatus and B12 scavenging genes of M. ruber. Certain uncharacterized genes of M. ruber had a larger number of edges to a variety of T. elongatus genes, specifically those involved in sugar synthesis, suggested that these uncharacterized heterotroph genes may be involved in sugar metabolism or transport in M. ruber