clubber: removing the bioinformatics bottleneck in big data analyses

Snow microbiome functional analyses reveal novel aspects of microbial metabolism of complex organic compounds

Microbes active in extreme cold are not as well explored as those of other extreme environments. Studies have revealed a substantial microbial diversity and identified cold-specific microbiome molecular functions. We analyzed the metagenomes and metatranscriptomes of 20 snow samples collected in early and late spring in Svalbard, Norway using mi-faser, our read-based computational microbiome function annotation tool. Our results reveal a more diverse microbiome functional capacity and activity in the early- vs. late-spring samples. We also find that functional dissimilarity between the same-sample metagenomes and metatranscriptomes is significantly higher in early than late spring samples. These findings suggest that early spring samples may contain a larger fraction of DNA of dormant (or dead) organisms, while late spring samples reflect a new, metabolically active community. We further show that the abundance of sequencing reads mapping to the fatty acid synthesis-related microbial pathways in late spring metagenomes and metatranscriptomes is significantly correlated with the organic acid levels measured in these samples. Similarly, the organic acid levels correlate with the pathway read abundances of geraniol degradation and inversely correlate with those of styrene degradation, suggesting a possible nutrient change. Our study thus highlights the activity of microbial degradation pathways of complex organic compounds previously unreported at low temperatures.

funtrp: identifying protein positions for variation driven functional tuning

Evaluating the impact of non-synonymous genetic variants is essential for uncovering disease associations and mechanisms of evolution. An in-depth understanding of sequence changes is also fundamental for synthetic protein design and stability assessments. However, the variant effect predictor performance gain observed in recent years has not kept up with the increased complexity of new methods. One likely reason for this might be that most approaches use similar sets of gene and protein features for modeling variant effects, often emphasizing sequence conservation. While high levels of conservation highlight residues essential for protein activity, much of the variation observable in vivo is arguably weaker in its impact, thus requiring evaluation at a higher level of resolution. Here, we describe functionNeutral/Toggle/Rheostatpredictor (funtrp), a novel computational method that categorizes protein positions based on the position-specific expected range of mutational impacts: Neutral (weak/no effects), Rheostat (function-tuning positions), or Toggle (on/off switches). We show that position types do not correlate strongly with familiar protein features such as conservation or protein disorder. We also find that position type distribution varies across different protein functions. Finally, we demonstrate that position types can improve performance of existing variant effect predictors and suggest a way forward for the development of new ones.

Functional sequencing read annotation for high precision microbiome analysis

The vast majority of microorganisms on Earth reside in often-inseparable environment-specific communities—microbiomes. Meta-genomic/-transcriptomic sequencing could reveal the otherwise inaccessible functionality of microbiomes. However, existing analytical approaches focus on attributing sequencing reads to known genes/genomes, often failing to make maximal use of available data. We created faser (functional annotation of sequencing reads), an algorithm that is optimized to map reads to molecular functions encoded by the read-correspondent genes. The mi-faser microbiome analysis pipeline, combining faser with our manually curated reference database of protein functions, accurately annotates microbiome molecular functionality. mi-faser’s minutes-per-microbiome processing speed is significantly faster than that of other methods, allowing for large scale comparisons. Microbiome function vectors can be compared between different conditions to highlight environment-specific and/or time-dependent changes in functionality. Here, we identified previously unseen oil degradation-specific functions in BP oil-spill data, as well as functional signatures of individual-specific gut microbiome responses to a dietary intervention in children with Prader–Willi syndrome. Our method also revealed variability in Crohn's Disease patient microbiomes and clearly distinguished them from those of related healthy individuals. Our analysis highlighted the microbiome role in CD pathogenicity, demonstrating enrichment of patient microbiomes in functions that promote inflammation and that help bacteria survive it.