Challenges and prospects of proteomics of non-model organisms

Novel model organisms and proteomics for a better biological understanding

The concept of « model organisms » is being revisited in the light of the latest advances in multi-omics technologies that can now capture the full range of molecular events that occur over time, regardless of the organism studied. Classic, well-studied models, such as Escherichia coli, Saccharomyces cerevisiae, to name a few, have long been valuable for hypothesis testing, reproducibility, and sharing common platforms among researchers. However, they are not suitable for all types of research. The complexity of unanswered questions in biology demands more elaborated systems, particularly to study plant and animal biodiversity, microbial ecosystems and their interactions with their hosts if any. More integrated systems, known as « holobionts », are emerging to describe and unify host organisms and associated microorganisms, providing an overview of all their possible interactions and trajectories. Comparative evolutionary proteomics offers interesting prospects for extrapolating knowledge from a few selected model organisms to others. This approach enables a deeper characterization of the diversity of proteins and proteoforms across the three branches of the tree of life, i.e. Bacteria, Archaea, and Eukarya. It also provides a powerful means to address remaining biological questions, such as identifying the key molecular players in organisms when they are confronted to environmental challenges, like anthropogenic toxicants, pathogens, dietary shifts or climate stressors, and proposing long-term sustainable solutions. SIGNIFICANCE: In this commentary, we reevaluated the concept of "model organisms" in light of advancements in multi-omics technologies. Traditional models have proven invaluable for hypothesis testing, reproducibility, and fostering shared research frameworks. However, we discussed that they are not universally applicable. To address complexities such as biodiversity and understand microbial ecosystems and their host interactions, integrated systems like "holobionts," which encompass host organisms and their associated microbes, are gaining prominence. Comparative evolutionary proteomics further enhances our understanding by enabling detailed exploration of protein diversity across organisms. This approach also facilitates the identification of critical molecular players in organisms facing environmental challenges, such as pollutants, pathogens, dietary changes, or climate stress, and contributes to developing sustainable long-term solutions.

Quantification of snake venom proteomes by mass spectrometry-considerations and perspectives

The advent of soft ionization mass spectrometry-based proteomics in the 1990s led to the development of a new dimension in biology that conceptually allows for the integral analysis of whole proteomes. This transition from a reductionist to a global-integrative approach is conditioned to the capability of proteomic platforms to generate and analyze complete qualitative and quantitative proteomics data. Paradoxically, the underlying analytical technique, molecular mass spectrometry, is inherently nonquantitative. The turn of the century witnessed the development of analytical strategies to endow proteomics with the ability to quantify proteomes of model organisms in the sense of "an organism for which comprehensive molecular (genomic and/or transcriptomic) resources are available." This essay presents an overview of the strategies and the lights and shadows of the most popular quantification methods highlighting the common misuse of label-free approaches developed for model species' when applied to quantify the individual components of proteomes of nonmodel species (In this essay we use the term "non-model" organisms for species lacking comprehensive molecular (genomic and/or transcriptomic) resources, a circumstance that, as we detail in this review-essay, conditions the quantification of their proteomes.). We also point out the opportunity of combining elemental and molecular mass spectrometry systems into a hybrid instrumental configuration for the parallel identification and absolute quantification of venom proteomes. The successful application of this novel mass spectrometry configuration in snake venomics represents a proof-of-concept for a broader and more routine application of hybrid elemental/molecular mass spectrometry setups in other areas of the proteomics field, such as phosphoproteomics, metallomics, and in general in any biological process where a heteroatom (i.e., any atom other than C, H, O, N) forms integral part of its mechanism.

β-1,3-Glucan recognition by Acanthamoeba castellanii as a putative mechanism of amoeba-fungal interactions

In this study, we conducted an in-depth analysis to characterize potential Acanthamoeba castellanii (Ac) proteins capable of recognizing fungal β-1,3-glucans. Ac specifically anchors curdlan or laminarin, indicating the presence of surface β-1,3-glucan-binding molecules. Using optical tweezers, strong adhesion of laminarin- or curdlan-coated beads to Ac was observed, highlighting their adhesive properties compared to controls (characteristic time τ of 46.9 and 43.9 s, respectively). Furthermore, Histoplasma capsulatum (Hc) G217B, possessing a β-1,3-glucan outer layer, showed significant adhesion to Ac compared to a Hc G186 strain with an α-1,3-glucan outer layer (τ of 5.3 s vs τ 83.6 s). The addition of soluble β-1,3-glucan substantially inhibited this adhesion, indicating the involvement of β-1,3-glucan recognition. Biotinylated β-1,3-glucan-binding proteins from Ac exhibited higher binding to Hc G217B, suggesting distinct recognition mechanisms for laminarin and curdlan, akin to macrophages. These observations hinted at the β-1,3-glucan recognition pathway's role in fungal entrance and survival within phagocytes, supported by decreased fungal viability upon laminarin or curdlan addition in both phagocytes. Proteomic analysis identified several Ac proteins capable of binding β-1,3-glucans, including those with lectin/glucanase superfamily domains, carbohydrate-binding domains, and glycosyl transferase and glycosyl hydrolase domains. Notably, some identified proteins were overexpressed upon curdlan/laminarin challenge and also demonstrated high affinity to β-1,3-glucans. These findings underscore the complexity of binding via β-1,3-glucan and suggest the existence of alternative fungal recognition pathways in Ac.IMPORTANCEAcanthamoeba castellanii (Ac) and macrophages both exhibit the remarkable ability to phagocytose various extracellular microorganisms in their respective environments. While substantial knowledge exists on this phenomenon for macrophages, the understanding of Ac's phagocytic mechanisms remains elusive. Recently, our group identified mannose-binding receptors on the surface of Ac that exhibit the capacity to bind/recognize fungi. However, the process was not entirely inhibited by soluble mannose, suggesting the possibility of other interactions. Herein, we describe the mechanism of β-1,3-glucan binding by A. castellanii and its role in fungal phagocytosis and survival within trophozoites, also using macrophages as a model for comparison, as they possess a well-established mechanism involving the Dectin-1 receptor for β-1,3-glucan recognition. These shed light on a potential parallel evolution of pathways involved in the recognition of fungal surface polysaccharides.

A Primer and Guidelines for Shotgun Proteomic Analysis in Non-model Organisms

During the last decade, we have witnessed outstanding advances in proteomics led mostly by great technological improvements in mass spectrometry field allowing high-throughput production of high-quality data used for massive protein identification and quantification. From a practical viewpoint, these advances have been mainly exploited in research projects involving model organisms with abundant genomic and proteomic information available in public databases. However, there is a growing number of organisms of high interest in different disciplines, such as ecological, biotechnological, and evolutionary research, yet poorly represented in these databases. Important advances in massive parallel sequencing technology and easy accessibility of this technology to many research laboratories have made nowadays possible to produce customized genomic and proteomic databases of any organism. Along this line, the use of proteogenomic approaches by combining in the same analysis the data obtained from different omic levels has emerged as a very useful and powerful strategy to run shotgun proteomic experiments specially focused on non-model organisms. In this chapter, we provide detailed procedures to undertake shotgun quantitative proteomic experiments following either a label-free or an isobaric labeling approach in non-model organisms, emphasizing also a few key aspects related to experimental design and data analysis.

Help, there are ‘omics’ in my comparative physiology!

‘Omics’ methods, such as transcriptomics, proteomics, lipidomics or metabolomics, yield simultaneous measurements of many related molecules in a sample. These approaches have opened new opportunities to generate and test hypotheses about the mechanisms underlying biochemical and physiological phenotypes. In this Commentary, we discuss general approaches and considerations for successfully integrating omics into comparative physiology. The choice of omics approach will be guided by the availability of existing resources and the time scale of the process being studied. We discuss the use of whole-organism extracts (common in omics experiments on small invertebrates) because such an approach may mask underlying physiological mechanisms, and we consider the advantages and disadvantages of pooling samples within biological replicates. These methods can bring analytical challenges, so we describe the most easily analyzed omics experimental designs. We address the propensity of omics studies to digress into ‘fishing expeditions’ and show how omics can be used within the hypothetico-deductive framework. With this Commentary, we hope to provide a roadmap that will help newcomers approach omics in comparative physiology while avoiding some of the potential pitfalls, which include ambiguous experiments, long lists of candidate molecules and vague conclusions.

Microbial symbionts affect Pisum sativum proteome and metabolome under Didymella pinodes infection

The long cultivation of field pea led to an enormous diversity which, however, seems to hold just little resistance against the ascochyta blight disease complex. The potential of below ground microbial symbiosis to prime the immune system of Pisum for an upcoming pathogen attack has hitherto received little attention. This study investigates the effect of beneficial microbes on the leaf proteome and metabolome as well as phenotype characteristics of plants in various symbiont interactions (mycorrhiza, rhizobia, co-inoculation, non-symbiotic) after infestation by Didymella pinodes. In healthy plants, mycorrhiza and rhizobia induced changes in RNA metabolism and protein synthesis. Furthermore, metal handling and ROS dampening was affected in all mycorrhiza treatments. The co-inoculation caused the synthesis of stress related proteins with concomitant adjustment of proteins involved in lipid biosynthesis. The plant's disease infection response included hormonal adjustment, ROS scavenging as well as synthesis of proteins related to secondary metabolism. The regulation of the TCA, amino acid and secondary metabolism including the pisatin pathway, was most pronounced in rhizobia associated plants which had the lowest infection rate and the slowest disease progression.

BIOLOGICAL SIGNIFICANCE

A most comprehensive study of the Pisum sativum proteome and metabolome infection response to Didymella pinodes is provided. Several distinct patterns of microbial symbioses on the plant metabolism are presented for the first time. Upon D. pinodes infection, rhizobial symbiosis revealed induced systemic resistance e.g. by an enhanced level of proteins involved in pisatin biosynthesis.

Application of de Novo Sequencing to Large-Scale Complex Proteomics Data Sets

Dependent on concise, predefined protein sequence databases, traditional search algorithms perform poorly when analyzing mass spectra derived from wholly uncharacterized protein products. Conversely, de novo peptide sequencing algorithms can interpret mass spectra without relying on reference databases. However, such algorithms have been difficult to apply to complex protein mixtures, in part due to a lack of methods for automatically validating de novo sequencing results. Here, we present novel metrics for benchmarking de novo sequencing algorithm performance on large-scale proteomics data sets and present a method for accurately calibrating false discovery rates on de novo results. We also present a novel algorithm (LADS) that leverages experimentally disambiguated fragmentation spectra to boost sequencing accuracy and sensitivity. LADS improves sequencing accuracy on longer peptides relative to that of other algorithms and improves discriminability of correct and incorrect sequences. Using these advancements, we demonstrate accurate de novo identification of peptide sequences not identifiable using database search-based approaches.