Contrasting patterns of genome-level diversity across distinct co-occurring bacterial populations.
General Material Designation
[Article]
First Statement of Responsibility
Garcia, Sarahi LStevens, Sarah LRCrary, BenjaminMartinez-Garcia, ManuelStepanauskas, RamunasWoyke, TanjaTringe, Susannah GAndersson, Siv GEBertilsson, StefanMalmstrom, Rex RMcMahon, Katherine D
SUMMARY OR ABSTRACT
Text of Note
To understand the forces driving differentiation and diversification in wild bacterial populations, we must be able to delineate and track ecologically relevant units through space and time. Mapping metagenomic sequences to reference genomes derived from the same environment can reveal genetic heterogeneity within populations, and in some cases, be used to identify boundaries between genetically similar, but ecologically distinct, populations. Here we examine population-level heterogeneity within abundant and ubiquitous freshwater bacterial groups such as the acI Actinobacteria and LD12 Alphaproteobacteria (the freshwater sister clade to the marine SAR11) using 33 single-cell genomes and a 5-year metagenomic time series. The single-cell genomes grouped into 15 monophyletic clusters (termed "tribes") that share at least 97.9% 16S rRNA identity. Distinct populations were identified within most tribes based on the patterns of metagenomic read recruitments to single-cell genomes representing these tribes. Genetically distinct populations within tribes of the acI Actinobacterial lineage living in the same lake had different seasonal abundance patterns, suggesting these populations were also ecologically distinct. In contrast, sympatric LD12 populations were less genetically differentiated. This suggests that within one lake, some freshwater lineages harbor genetically discrete (but still closely related) and ecologically distinct populations, while other lineages are composed of less differentiated populations with overlapping niches. Our results point at an interplay of evolutionary and ecological forces acting on these communities that can be observed in real time.