Proteogenomics-Guided Evaluation of RNA-Seq Assembly and Protein Database Construction for Emergent Model Organisms

Water stress modulates terpene biosynthesis and morphophysiology at different ploidal levels in Lippia alba (Mill.) N. E. Brown (Verbenaceae)

Monoterpenes are the main component in essential oils of Lippia alba. In this species, the chemical composition of essential oils varies with genome size: citral (geraniol and neral) is dominant in diploids and tetraploids, and linalool in triploids. Because environmental stress impacts various metabolic pathways, we hypothesized that stress responses in L. alba could alter the relationship between genome size and essential oil composition. Water stress affects the flowering, production, and reproduction of plants. Here, we evaluated the effect of water stress on morphophysiology, essential oil production, and the expression of genes related to monoterpene synthesis in diploid, triploid, and tetraploid accessions of L. alba cultivated in vitro for 40 days. First, using transcriptome data, we performed de novo gene assembly and identified orthologous genes using phylogenetic and clustering-based approaches. The expression of candidate genes related to terpene biosynthesis was estimated by real-time quantitative PCR. Next, we assessed the expression of these genes under water stress conditions, whereby 1% PEG-4000 was added to MS medium. Water stress modulated L. alba morphophysiology at all ploidal levels. Gene expression and essential oil production were affected in triploid accessions. Polyploid accessions showed greater growth and metabolic tolerance under stress compared to diploids. These results confirm the complex regulation of metabolic pathways such as the production of essential oils in polyploid genomes. In addition, they highlight aspects of genotype and environment interactions, which may be important for the conservation of tropical biodiversity.

Characterization of natural peptides in Pheretima by integrating proteogenomics and label-free peptidomics

Pheretima, also called "earthworms", is a well-known animal-derived traditional Chinese medicine that is extensively used in over 50 Chinese patent medicines (CPMs) in Chinese Pharmacopoeia (2020 edition). However, its zoological origin is unclear, both in the herbal market and CPMs. In this study, a strategy for integrating in-house annotated protein databases constructed from close evolutionary relationship-sourced RNA sequencing data from public archival resources and various sequencing algorithms (restricted search, open search, and de novo) was developed to characterize the phenotype of natural peptides of three major commercial species of Pheretima, including Pheretima aspergillum (PA), Pheretima vulgaris (PV), and Metaphire magna (MM). We identified 10,477 natural peptides in the PA, 7,451 in PV, and 5,896 in MM samples. Five specific signature peptides were screened and then validated using synthetic peptides; these demonstrated robust specificity for the authentication of PA, PV, and MM. Finally, all marker peptides were successfully applied to identify the zoological origins of Brain Heart capsules and Xiaohuoluo pills, revealing the inconsistent Pheretima species used in these CPMs. In conclusion, our integrated strategy could be used for the in-depth characterization of natural peptides of other animal-derived traditional Chinese medicines, especially non-model species with poorly annotated protein databases.

Characterization of the natural peptidome of four leeches by integrated proteogenomics and pseudotargeted peptidomics

Animal-derived drugs are an indispensable part of folk medicine worldwide. However, their chemical constituents are poorly approached, which leads to the low level of the quality standard system of animal-derived drugs and further causes a chaotic market. Natural peptides are ubiquitous throughout the organism, especially in animal-derived drugs. Thus, in this study, we used multi-source leeches, including Hirudo nipponica (HN), Whitmania pigra (WP), Whitmania acranulata (WA), and Poecilobdella manillensis (PM), as a model. A strategy integrating proteogenomics and novel pseudotargeted peptidomics was developed to characterize the natural peptide phenotype and screen for signature peptides of four leech species. First, natural peptides were sequenced against an in-house annotated protein database of closely related species constructed from RNA-seq data from the Sequence Read Archive (SRA) website, which is an open-sourced public archive resource. Second, a novel pseudotargeted peptidomics integrating peptide ion pair extraction and retention time transfer was established to achieve high coverage and quantitative accuracy of the natural peptides and to screen for signature peptides for species authentication. In all, 2323 natural peptides were identified from four leech species whose databases were poorly annotated. The strategy was shown to significantly improve peptide identification. In addition, 36 of 167 differential peptides screened by pseudotargeted proteomics were identified, and about one-third of them came from the leucine-rich repeat domain (LRR) proteins, which are widely distributed in organisms. Furthermore, six signature peptides were screened with good specificity and stability, and four of them were validated by synthetic standards. Finally, a dynamic multiple reaction monitoring (dMRM) method based on these signature peptides was established and revealed that one-half of the commercial samples and all of the Tongxinluo capsules were derived from WP. All in all, the strategy developed in this study was effective for natural peptide characterization and signature peptide screening, which could also be applied to other animal-derived drugs, especially for modelless species that are less studied in protein database annotation.

Increasing the power of interpretation for soil metaproteomics data

BACKGROUND

Soil and sediment microorganisms are highly phylogenetically diverse but are currently largely under-represented in public molecular databases. Their functional characterization by means of metaproteomics is usually performed using metagenomic sequences acquired for the same sample. However, such hugely diverse metagenomic datasets are difficult to assemble; in parallel, theoretical proteomes from isolates available in generic databases are of high quality. Both these factors advocate for the use of theoretical proteomes in metaproteomics interpretation pipelines. Here, we examined a number of database construction strategies with a view to increasing the outputs of metaproteomics studies performed on soil samples.

RESULTS

The number of peptide-spectrum matches was found to be of comparable magnitude when using public or sample-specific metagenomics-derived databases. However, numbers were significantly increased when a combination of both types of information was used in a two-step cascaded search. Our data also indicate that the functional annotation of the metaproteomics dataset can be maximized by using a combination of both types of databases.

CONCLUSIONS

A two-step strategy combining sample-specific metagenome database and public databases such as the non-redundant NCBI database and a massive soil gene catalog allows maximizing the metaproteomic interpretation both in terms of ratio of assigned spectra and retrieval of function-derived information. Video abstract.