Postnovo: Postprocessing Enables Accurate and FDR-Controlled de Novo Peptide Sequencing.

De novo sequencing offers an alternative to database search methods for peptide identification from mass spectra. Since it does not rely on a predetermined database of expected or potential sequences in the sample, de novo sequencing is particularly appropriate for samples lacking a well-defined or comprehensive reference database. However, the low accuracy of many de novo sequence predictions has prevented the widespread use of the variety of sequencing tools currently available. Here, we present a new open-source tool, Postnovo, that postprocesses de novo sequence predictions to find high-accuracy results. Postnovo uses a predictive model to rescore and rerank candidate sequences in a manner akin to database search postprocessing tools such as Percolator. Postnovo leverages the output from multiple de novo sequencing tools in its own analyses, producing many times the length of amino acid sequence information (including both full- and partial-length peptide sequences) at an equivalent false discovery rate (FDR) compared to any individual tool. We present a methodology to reliably screen the sequence predictions to a desired FDR given the Postnovo sequence score. We validate Postnovo with multiple data sets and demonstrate its ability to identify proteins that are missed by database search even in samples with paired reference databases.

Metaproteomics reveals functional partitioning and vegetational variation among permafrost-affected Arctic soil bacterial communities.

Microbial activity in Arctic soils controls the cycling of significant stores of organic carbon and nutrients. We studied in situ processes in Alaskan soils using original metaproteomic methods in order to relate important heterotrophic functions to microbial taxa and to understand the microbial response to Arctic greening. Major bacterial groups show strong metabolic specialization in organic topsoils. α-/ß-/γ-Proteobacteria specialized in the acquisition of small, soluble compounds, whereas Acidobacteria, Actinobacteria, and other detritosphere groups specialized in the degradation of plant-derived polymers. α-/ß-/γ-Proteobacteria dominated the expression of transporters for common root exudates and limiting nitrogenous compounds, supporting an ecological model of dependence upon plants for carbon and competition with plants for nitrogen. Detritosphere groups specialized in distinct substrates, with Acidobacteria producing the most enzymes for hemicellulose depolymerization. Acidobacteria was the most active group across the three plant ecotypes sampled-the largely nonvascular, lower biomass intertussock and the largely vascular, higher biomass tussock and shrub. Functional partitioning among bacterial groups was stable between plant ecotypes, but certain functions associated with α-/ß-/γ-Proteobacteria were more strongly expressed in higher biomass ecotypes. We show that refined metaproteomic approaches can elucidate soil microbial ecology as well as biogeochemical trajectories of major carbon stocks. IMPORTANCE The Arctic is warming twice as fast as the rest of the planet, and Arctic soils currently store twice as much carbon as the entire atmosphere-two facts that make understanding how Arctic soil microbial communities are responding to climate change particularly urgent. Greening of vegetation cover across the Arctic landscape is one of the most prominent climate-driven shifts in Arctic terrestrial ecology, with potentially profound effects on biogeochemical cycling by the soil microbiome. Here we use metaproteomics to document microbial metabolic functions that drive soil carbon and nutrient cycling processes in an Arctic tundra landscape. We identify functional roles among bacterial taxonomic groups that are largely stable across vegetation types, with certain functions strongly expressed by rhizosphere groups reflecting a community metabolic response to greening.

Structure-informed microbial population genetics elucidate selective pressures that shape protein evolution.

Comprehensive sampling of natural genetic diversity with metagenomics enables highly resolved insights into the interplay between ecology and evolution. However, resolving adaptive, neutral, or purifying processes of evolution from intrapopulation genomic variation remains a challenge, partly due to the sole reliance on gene sequences to interpret variants. Here, we describe an approach to analyze genetic variation in the context of predicted protein structures and apply it to a marine microbial population within the SAR11 subclade 1a.3.V, which dominates low-latitude surface oceans. Our analyses reveal a tight association between genetic variation and protein structure. In a central gene in nitrogen metabolism, we observe decreased occurrence of nonsynonymous variants from ligand-binding sites as a function of nitrate concentrations, revealing genetic targets of distinct evolutionary pressures maintained by nutrient availability. Our work yields insights into the governing principles of evolution and enables structure-aware investigations of microbial population genetics.

Water quality and plankton in the United States nearshore waters of Lake Huron.

Our goal in the development of a nearshore monitoring method has been to evaluate and refine an in situ mapping approach to assess the nearshore waters across the Great Lakes. The report here for Lake Huron is part of a broader effort being conducted across all five Great Lakes. We conducted an intensive survey for the United States nearshore of Lake Huron along a continuous shoreline transect (523 km) from Port Huron, Michigan, to Detour Passage. A depth contour of 20 m was towed with a conductivity-temperature depth profiler, fluorometer, transmissometer, and laser optical plankton counter. Multiple cross-contour tows (10-30 m) on the cruise dates were used to characterize the variability across a broader range of the nearshore. The cross-contour tows were comparable with the alongshore contour indicating that the 20-m contour does a good job of representing the nearshore region (10-30 m). Strong correlations were observed between water quality and spatially associated watershed land use. A repeat tow separated by several weeks investigated temporal variability in spatial patterns within a summer season. Strong correlations were observed across each variable for the temporal repeat across broad- and fine-scale spatial dimensions. The survey results for Lake Huron nearshore are briefly compared with a similar nearshore survey in Lake Superior. The biomass concentrations of lower food web components of Lake Huron were notably approximately 54-59 % of those in Lake Superior. The towed instrumentation survey supported the recent view of a change in Lake Huron to an ultra-oligotrophic state, which has been uncharacteristic in recent history.