Larval Geoduck (Panopea generosa) Proteomic Response to Ciliates.

The innate immune response is active in invertebrate larvae from early development. Induction of immune response pathways may occur as part of the natural progression of larval development, but an up-regulation of pathways can also occur in response to a pathogen. Here, we took advantage of a protozoan ciliate infestation of a larval geoduck clam culture in a commercial hatchery to investigate the molecular underpinnings of the innate immune response of the larvae to the pathogen. Larval proteomes were analyzed on days 4-10 post-fertilization; ciliates were present on days 8 and 10 post-fertilization. Through comparisons with larval cultures that did not encounter ciliates, proteins implicated in the response to ciliate presence were identified using mass spectrometry-based proteomics. Ciliate response proteins included many associated with ribosomal synthesis and protein translation, suggesting the importance of protein synthesis during the larval immune response. There was also an increased abundance of proteins typically associated with the stress and immune responses during ciliate exposure, such as heat shock proteins, glutathione metabolism, and the reactive oxygen species response. These findings provide a basic understanding of the bivalve molecular response to a mortality-inducing ciliate and improved characterization of the ontogenetic development of the innate immune response.

MS analysis of a dilution series of bacteria:phytoplankton to improve detection of low abundance bacterial peptides.

Assigning links between microbial activity and biogeochemical cycles in the ocean is a primary objective for ecologists and oceanographers. Bacteria represent a small ecosystem component by mass, but act as the nexus for both nutrient transformation and organic matter recycling. There are limited methods to explore the full suite of active bacterial proteins largely responsible for degradation. Mass spectrometry (MS)-based proteomics now has the potential to document bacterial physiology within these complex systems. Global proteome profiling using MS, known as data dependent acquisition (DDA), is limited by the stochastic nature of ion selection, decreasing the detection of low abundance peptides. The suitability of MS-based proteomics methods in revealing bacterial signatures outnumbered by phytoplankton proteins was explored using a dilution series of pure bacteria (Ruegeria pomeroyi) and diatoms (Thalassiosira pseudonana). Two common acquisition strategies were utilized: DDA and selected reaction monitoring (SRM). SRM improved detection of bacterial peptides at low bacterial cellular abundance that were undetectable with DDA from a wide range of physiological processes (e.g. amino acid synthesis, lipid metabolism, and transport). We demonstrate the benefits and drawbacks of two different proteomic approaches for investigating species-specific physiological processes across relative abundances of bacteria that vary by orders of magnitude.

An Alignment-Free "Metapeptide" Strategy for Metaproteomic Characterization of Microbiome Samples Using Shotgun Metagenomic Sequencing.

In principle, tandem mass spectrometry can be used to detect and quantify the peptides present in a microbiome sample, enabling functional and taxonomic insight into microbiome metabolic activity. However, the phylogenetic diversity constituting a particular microbiome is often unknown, and many of the organisms present may not have assembled genomes. In ocean microbiome samples, with particularly diverse and uncultured bacterial communities, it is difficult to construct protein databases that contain the bulk of the peptides in the sample without losing detection sensitivity due to the overwhelming number of candidate peptides for each tandem mass spectrum. We describe a method for deriving "metapeptides" (short amino acid sequences that may be represented in multiple organisms) from shotgun metagenomic sequencing of microbiome samples. In two ocean microbiome samples, we constructed site-specific metapeptide databases to detect more than one and a half times as many peptides as by searching against predicted genes from an assembled metagenome and roughly three times as many peptides as by searching against the NCBI environmental proteome database. The increased peptide yield has the potential to enrich the taxonomic and functional characterization of sample metaproteomes.