Evolutionary origins and diversification of proteobacterial mutualists.

Mutualistic bacteria infect most eukaryotic species in nearly every biome. Nonetheless, two dilemmas remain unresolved about bacterial-eukaryote mutualisms: how do mutualist phenotypes originate in bacterial lineages and to what degree do mutualists traits drive or hinder bacterial diversification? Here, we reconstructed the phylogeny of the hyperdiverse phylum Proteobacteria to investigate the origins and evolutionary diversification of mutualistic bacterial phenotypes. Our ancestral state reconstructions (ASRs) inferred a range of 34-39 independent origins of mutualist phenotypes in Proteobacteria, revealing the surprising frequency with which host-beneficial traits have evolved in this phylum. We found proteobacterial mutualists to be more often derived from parasitic than from free-living ancestors, consistent with the untested paradigm that bacterial mutualists most often evolve from pathogens. Strikingly, we inferred that mutualists exhibit a negative net diversification rate (speciation minus extinction), which suggests that mutualism evolves primarily via transitions from other states rather than diversification within mutualist taxa. Moreover, our ASRs infer that proteobacterial mutualist lineages exhibit a paucity of reversals to parasitism or to free-living status. This evolutionary conservatism of mutualism is contrary to long-standing theory, which predicts that selection should often favour mutants in microbial mutualist populations that exploit or abandon more slowly evolving eukaryotic hosts.

Benchmarking Single-Cell mRNA-Sequencing Technologies Uncovers Differences in Sensitivity and Reproducibility in Cell Types With Low RNA Content.

Single-cell RNA sequencing (scRNA-seq) has the ability to classify each cell and determine the transcriptomic profile of specific cell types and cells of a given disease state; however, sensitivity of the gene count for each cell can be a critical component to the success of a single-cell study. The recently introduced SMART-Seq Single Cell PLUS Kit (SSsc PLUS) claims to provide higher sensitivity and reproducibility versus popular methods for the sequencing analysis of single cells. Here, the cDNA-generation component of the kit, SMART-Seq Single Cell Kit (SSsc), was compared with the popular homebrew protocol, Smart-seq2, and its update, Smart-seq3. The SMART-Seq Library Prep Kit from SSsc PLUS was benchmarked against a commonly used scRNA-seq library preparation method, Illumina Nextera XT. Finally, the SSsc chemistry was tested in both full and fractional volumes on 2 popular liquid-handler devices to investigate whether the high sensitivity was maintained in miniaturization. We demonstrate that SSsc PLUS outperforms these other full-length methods in convenience, sensitivity, gene identification, and reproducibility while also offering full compatibility with automation platforms.