Search for: All records

Stromatolites are complex microbial mats that form lithified layers. Fossilized stromatolites are the oldest evidence of cellular life on Earth, dating back over 3.4 billion years. Modern stromatolites are relatively rare but may provide clues about the function and evolution of their ancient counterparts. In this study, we focus on peritidal stromatolites occurring at Cape Recife and Schoenmakerskop on the southeastern South African coastline, the former being morphologically and structurally similar to fossilized phosphatic stromatolites formations. Using assembled shotgun metagenomic analysis, we obtained 183 genomic bins, of which the most dominant taxa were from the Cyanobacteria phylum. We identified functional gene sets in genomic bins conserved across two geographically isolated stromatolite formations, which included relatively high copy numbers of genes involved in the reduction of nitrates and phosphatic compounds. Additionally, we found little evidence of Archaeal species in these stromatolites, suggesting that they may not play an important role in peritidal stromatolite formations, as proposed for hypersaline formations.

 

Abstract Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.