Cross species proteomics

Unfolding and identification of membrane proteins in situ

Single-molecule force spectroscopy (SMFS) uses the cantilever tip of an AFM to apply a force able to unfold a single protein. The obtained force-distance curve encodes the unfolding pathway, and from its analysis it is possible to characterize the folded domains. SMFS has been mostly used to study the unfolding of purified proteins, in solution or reconstituted in a lipid bilayer. Here, we describe a pipeline for analyzing membrane proteins based on SMFS, that involves the isolation of the plasma membrane of single cells and the harvesting of force-distance curves directly from it. We characterized and identified the embedded membrane proteins combining, within a Bayesian framework, the information of the shape of the obtained curves, with the information from Mass Spectrometry and proteomic databases. The pipeline was tested with purified/reconstituted proteins and applied to five cell types where we classified the unfolding of their most abundant membrane proteins. We validated our pipeline by overexpressing 4 constructs, and this allowed us to gather structural insights of the identified proteins, revealing variable elements in the loop regions. Our results set the basis for the investigation of the unfolding of membrane proteins in situ, and for performing proteomics from a membrane fragment.

Comparison of plasma and cerebrospinal fluid proteomes identifies gene products guiding adult neurogenesis and neural differentiation in birds

Cerebrospinal fluid (CSF) proteins regulate neurogenesis, brain homeostasis and participate in signalling during neuroinflammation. Even though birds represent valuable models for constitutive adult neurogenesis, current proteomic studies of the avian CSF are limited to chicken embryos. Here we use liquid chromatography-tandem mass spectrometry (nLC-MS/MS) to explore the proteomic composition of CSF and plasma in adult chickens (Gallus gallus) and evolutionarily derived parrots: budgerigar (Melopsittacus undulatus) and cockatiel (Nymphicus hollandicus). Because cockatiel lacks a complete genome information, we compared the cross-species protein identifications using the reference proteomes of three model avian species: chicken, budgerigar and zebra finch (Taeniopygia guttata) and found the highest identification rates when mapping against the phylogenetically closest species, the budgerigar. In total, we identified 483, 641 and 458 unique proteins consistently represented in the CSF and plasma of all chicken, budgerigar and cockatiel conspecifics, respectively. Comparative pathways analyses of CSF and blood plasma then indicated clusters of proteins involved in neurogenesis, neural development and neural differentiation overrepresented in CSF in each species. This study provides the first insight into the proteomics of adult avian CSF and plasma and brings novel evidence supporting the adult neurogenesis in birds.

Untangling the fibre ball: Proteomic characterization of South American camelid hair fibres by untargeted multivariate analysis and molecular networking

The proteomic analysis of hairs, yarns or textiles has emerged as a powerful method to determine species of origin, mainly used in archaeozoological research and fraud control. Differentiation between the South American camelid (SAC) species (the wild guanaco and vicuña and their respective domesticates the llama and alpaca) is particularly challenging due to poor database information and significant hybridization between species. In this study, we analysed 41 modern and 4 archaeological samples from the four SACs species. Despite strong similarities with Old World Camelidae, we identified 7 peptides specific to SACs assigned to keratin K86 and the keratin-associated proteins KAP13-1 and KAP11-1. Untargeted multivariate analysis of the LC-MS data permitted to distinguish SAC species and propose discriminant features. MS/MS-based molecular networking combined with database-assisted de novo sequencing permitted to identify 5 new taxonomic peptides assigned to K33a, K81 and/or K83 keratins and KAP19-1. These peptides differentiate the two wild species, guanaco and vicuña. These results show the value of combining database search and untargeted metabolomic approaches for paleoproteomics, and reveal for the first time the potential of molecular networks to highlight deamidation related to diagenesis and cluster highly similar peptides related to interchain homologies or intra- or inter-specific polymorphism. SIGNIFICANCE: This study used an innovative approach combining multivariate analysis of LC-MS data together with molecular networking and database-assisted de novo sequencing to identify taxonomic peptides in palaeoproteomics. It constitutes the first attempt to differentiate between hair fibres from the four South American camelids (SACs) based on proteomic analysis of modern and archaeological samples. It provides different proteomic signatures for each of the four SAC species and proposes new SAC taxonomic peptides of interest in archaeozoology and fraud control. SACs have been extensively exploited since human colonization of South America but have not been studied to the extent of their economic, cultural and heritage importance. Applied to the analysis of ancient Andean textiles, our results should permit a better understanding of cultural and pastoral practices in South America. The wild SACs are endangered by poaching and black-market sale of their fibre. For the first time, our results provide discriminant features for the determination of species of origin of contraband fibre.

Changes in the proteome of sea urchin Paracentrotus lividus coelomocytes in response to LPS injection into the body cavity

Background

The immune system of echinoderm sea urchins is characterised by a high degree of complexity that is not completely understood. The Mediterranean sea urchin Paracentrotus lividus coelomocytes mediate immune responses through phagocytosis, encapsulation of non-self particles, and production of diffusible factors including antimicrobial molecules. Details of these processes, and molecular pathways driving these mechanisms, are still to be fully elucidated.

Principal findings

In the present study we treated the sea urchin P. lividus with the bacterial lipopolysaccharide (LPS) and collected coelomocytes at different time-points (1, 3, 6 and 24 hours). We have shown, using label-free quantitative mass spectrometry, how LPS is able to modulate the coelomocyte proteome and to effect cellular pathways, such as endocytosis and phagocytosis, as soon as the immunomodulating agent is injected. The present study has also shown that treatment can modulate various cellular processes such as cytoskeleton reorganisation, and stress and energetic homeostasis.

Conclusions

Our data demonstrates, through mass spectrometry and the following functional annotation bioinformatics analysis, how the bacterial wall constituent is sufficient to set off an immune response inducing cytoskeleton reorganisation, the appearance of clusters of heat shock proteins (Hsp) and histone proteins and the activation of the endocytic and phagocytic pathways. Data are available via ProteomeXchange with identifier PXD008439.

Bioinformatics approaches for improving seminal plasma proteome analysis

Reproduction efficiency of male animals is one of the key factors influencing the sustainability of livestock. Mass spectrometry (MS) based proteomics has become an important tool for studying seminal plasma proteomes. In this review, we summarize bioinformatics analysis strategies for current proteomics approaches, for identifying novel biomarkers of reproductive robustness.

The Secretome and N-Glycosylation Profiles of the Charophycean Green Alga, Penium margaritaceum, Resemble Those of Embryophytes

The secretome can be defined as the population of proteins that are secreted into the extracellular environment. Many proteins that are secreted by eukaryotes are N-glycosylated. However, there are striking differences in the diversity and conservation of N-glycosylation patterns between taxa. For example, the secretome and N-glycosylation structures differ between land plants and chlorophyte green algae, but it is not clear when this divergence took place during plant evolution. A potentially valuable system to study this issue is provided by the charophycean green algae (CGA), which is the immediate ancestors of land plants. In this study, we used lectin affinity chromatography (LAC) coupled with mass spectrometry to characterize the secretome including secreted N-glycoproteins of Penium margaritaceum, which is a member of the CGA. The identified secreted proteins and N-glycans were compared to those known from the chlorophyte green alga Chlamydomonas reinhardtii and the model land plant, Arabidopsis thaliana, to establish their evolutionary context. Our approach allowed the identification of cell wall proteins and proteins modified with N-glycans that are identical to those of embryophytes, which suggests that the P. margaritaceum secretome is more closely related to those of land plants than to those of chlorophytes. The results of this study support the hypothesis that many of the proteins associated with plant cell wall modification as well as other extracellular processes evolved prior to the colonization of terrestrial habitats.

Elucidation of cross-species proteomic effects in human and hominin bone proteome identification through a bioinformatics experiment

BACKGROUND

The study of ancient protein sequences is increasingly focused on the analysis of older samples, including those of ancient hominins. The analysis of such ancient proteomes thereby potentially suffers from "cross-species proteomic effects": the loss of peptide and protein identifications at increased evolutionary distances due to a larger number of protein sequence differences between the database sequence and the analyzed organism. Error-tolerant proteomic search algorithms should theoretically overcome this problem at both the peptide and protein level; however, this has not been demonstrated. If error-tolerant searches do not overcome the cross-species proteomic issue then there might be inherent biases in the identified proteomes. Here, a bioinformatics experiment is performed to test this using a set of modern human bone proteomes and three independent searches against sequence databases at increasing evolutionary distances: the human (0 Ma), chimpanzee (6-8 Ma) and orangutan (16-17 Ma) reference proteomes, respectively.

RESULTS

Incorrectly suggested amino acid substitutions are absent when employing adequate filtering criteria for mutable Peptide Spectrum Matches (PSMs), but roughly half of the mutable PSMs were not recovered. As a result, peptide and protein identification rates are higher in error-tolerant mode compared to non-error-tolerant searches but did not recover protein identifications completely. Data indicates that peptide length and the number of mutations between the target and database sequences are the main factors influencing mutable PSM identification.

CONCLUSIONS

The error-tolerant results suggest that the cross-species proteomics problem is not overcome at increasing evolutionary distances, even at the protein level. Peptide and protein loss has the potential to significantly impact divergence dating and proteome comparisons when using ancient samples as there is a bias towards the identification of conserved sequences and proteins. Effects are minimized between moderately divergent proteomes, as indicated by almost complete recovery of informative positions in the search against the chimpanzee proteome (≈90%, 6-8 Ma). This provides a bioinformatic background to future phylogenetic and proteomic analysis of ancient hominin proteomes, including the future description of novel hominin amino acid sequences, but also has negative implications for the study of fast-evolving proteins in hominins, non-hominin animals, and ancient bacterial proteins in evolutionary contexts.

Mitochondrial thioredoxin reductase 2 is elevated in long-lived primate as well as rodent species and extends fly mean lifespan

In a survey of enzymes related to protein oxidation and cellular redox state, we found activity of the redox enzyme thioredoxin reductase (TXNRD) to be elevated in cells from long‐lived species of rodents, primates, and birds. Elevated TXNRD activity in long‐lived species reflected increases in the mitochondrial form, TXNRD2, rather than the cytosolic forms TXNRD1 and TXNRD3. Analysis of published RNA‐Seq data showed elevated TXNRD2 mRNA in multiple organs of longer‐lived primates, suggesting that the phenomenon is not limited to skin‐derived fibroblasts. Elevation of TXNRD2 activity and protein levels was also noted in liver of three different long‐lived mutant mice, and in normal male mice treated with a drug that extends lifespan in males. Overexpression of mitochondrial TXNRD2 in Drosophila melanogaster extended median (but not maximum) lifespan in female flies with a small lifespan extension in males; in contrast, overexpression of the cytosolic form, TXNRD1, did not produce a lifespan extension.

The impact of sequence database choice on metaproteomic results in gut microbiota studies

BACKGROUND

Elucidating the role of gut microbiota in physiological and pathological processes has recently emerged as a key research aim in life sciences. In this respect, metaproteomics, the study of the whole protein complement of a microbial community, can provide a unique contribution by revealing which functions are actually being expressed by specific microbial taxa. However, its wide application to gut microbiota research has been hindered by challenges in data analysis, especially related to the choice of the proper sequence databases for protein identification.

RESULTS

Here, we present a systematic investigation of variables concerning database construction and annotation and evaluate their impact on human and mouse gut metaproteomic results. We found that both publicly available and experimental metagenomic databases lead to the identification of unique peptide assortments, suggesting parallel database searches as a mean to gain more complete information. In particular, the contribution of experimental metagenomic databases was revealed to be mandatory when dealing with mouse samples. Moreover, the use of a "merged" database, containing all metagenomic sequences from the population under study, was found to be generally preferable over the use of sample-matched databases. We also observed that taxonomic and functional results are strongly database-dependent, in particular when analyzing the mouse gut microbiota. As a striking example, the Firmicutes/Bacteroidetes ratio varied up to tenfold depending on the database used. Finally, assembling reads into longer contigs provided significant advantages in terms of functional annotation yields.

CONCLUSIONS

This study contributes to identify host- and database-specific biases which need to be taken into account in a metaproteomic experiment, providing meaningful insights on how to design gut microbiota studies and to perform metaproteomic data analysis. In particular, the use of multiple databases and annotation tools has to be encouraged, even though this requires appropriate bioinformatic resources.

Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks

Peptide and protein identification remains challenging in organisms with poorly annotated or rapidly evolving genomes, as are commonly encountered in environmental or biofuels research. Such limitations render tandem mass spectrometry (MS/MS) database search algorithms ineffective as they lack corresponding sequences required for peptide-spectrum matching. We address this challenge with the spectral networks approach to (1) match spectra of orthologous peptides across multiple related species and then (2) propagate peptide annotations from identified to unidentified spectra. We here present algorithms to assess the statistical significance of spectral alignments (Align-GF), reduce the impurity in spectral networks, and accurately estimate the error rate in propagated identifications. Analyzing three related Cyanothece species, a model organism for biohydrogen production, spectral networks identified peptides from highly divergent sequences from networks with dozens of variant peptides, including thousands of peptides in species lacking a sequenced genome. Our analysis further detected the presence of many novel putative peptides even in genomically characterized species, thus suggesting the possibility of gaps in our understanding of their proteomic and genomic expression. A web-based pipeline for spectral networks analysis is available at http://proteomics.ucsd.edu/software.

Evaluating the impact of different sequence databases on metaproteome analysis: insights from a lab-assembled microbial mixture

Metaproteomics enables the investigation of the protein repertoire expressed by complex microbial communities. However, to unleash its full potential, refinements in bioinformatic approaches for data analysis are still needed. In this context, sequence databases selection represents a major challenge. This work assessed the impact of different databases in metaproteomic investigations by using a mock microbial mixture including nine diverse bacterial and eukaryotic species, which was subjected to shotgun metaproteomic analysis. Then, both the microbial mixture and the single microorganisms were subjected to next generation sequencing to obtain experimental metagenomic- and genomic-derived databases, which were used along with public databases (namely, NCBI, UniProtKB/SwissProt and UniProtKB/TrEMBL, parsed at different taxonomic levels) to analyze the metaproteomic dataset. First, a quantitative comparison in terms of number and overlap of peptide identifications was carried out among all databases. As a result, only 35% of peptides were common to all database classes; moreover, genus/species-specific databases provided up to 17% more identifications compared to databases with generic taxonomy, while the metagenomic database enabled a slight increment in respect to public databases. Then, database behavior in terms of false discovery rate and peptide degeneracy was critically evaluated. Public databases with generic taxonomy exhibited a markedly different trend compared to the counterparts. Finally, the reliability of taxonomic attribution according to the lowest common ancestor approach (using MEGAN and Unipept software) was assessed. The level of misassignments varied among the different databases, and specific thresholds based on the number of taxon-specific peptides were established to minimize false positives. This study confirms that database selection has a significant impact in metaproteomics, and provides critical indications for improving depth and reliability of metaproteomic results. Specifically, the use of iterative searches and of suitable filters for taxonomic assignments is proposed with the aim of increasing coverage and trustworthiness of metaproteomic data.

Proteomics of nonmodel plant species

Until recently, large scale proteomic investigations in the plant field have only been possible for a few model species for which the whole genome sequence had been fully determined. In contrast, for many other species with a strong economic interest as sources of human food and animal feed, as well as industrial and pharmacological molecules, little was known about their genome sequence and identifying the proteome in these species was still considered challenging. However, progress has been made as a result of several recent advances in proteomics tools, e.g. in MS technology and data search programs, and the increasing availability of genomic and cDNA sequences from various species. Moreover, next-generation sequencing technologies now make it possible to rapidly determine, at a reasonable cost, the genome or RNA sequence of species not currently considered as models, thus considerably expanding the plant sequence databases. This review will show how these advances make it possible to identify a large set of proteins, even for species for which few sequences are currently available.

Overcoming species boundaries in peptide identification with Bayesian information criterion-driven error-tolerant peptide search (BICEPS)

Currently, the reliable identification of peptides and proteins is only feasible when thoroughly annotated sequence databases are available. Although sequencing capacities continue to grow, many organisms remain without reliable, fully annotated reference genomes required for proteomic analyses. Standard database search algorithms fail to identify peptides that are not exactly contained in a protein database. De novo searches are generally hindered by their restricted reliability, and current error-tolerant search strategies are limited by global, heuristic tradeoffs between database and spectral information. We propose a Bayesian information criterion-driven error-tolerant peptide search (BICEPS) and offer an open source implementation based on this statistical criterion to automatically balance the information of each single spectrum and the database, while limiting the run time. We show that BICEPS performs as well as current database search algorithms when such algorithms are applied to sequenced organisms, whereas BICEPS only uses a remotely related organism database. For instance, we use a chicken instead of a human database corresponding to an evolutionary distance of more than 300 million years (International Chicken Genome Sequencing Consortium (2004) Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution. Nature 432, 695–716). We demonstrate the successful application to cross-species proteomics with a 33% increase in the number of identified proteins for a filarial nematode sample of Litomosoides sigmodontis.

Divide and conquer: the application of organelle proteomics to heart failure

Chronic heart failure is a worldwide cause of mortality and morbidity and is the final outcome of a number of different etiologies. This reflects both the complexity of the disease and our incomplete understanding of its underlying molecular mechanisms. One experimental approach to address this is to study subcellular organelles and how their functions are activated and synchronized under physiological and pathological conditions. In this review, we discuss the application of proteomic technologies to organelles and how this has deepened our perception of the cellular proteome and its alterations with heart failure. The use of proteomics to monitor protein quantity and posttranslational modifications has revealed a highly intricate and sophisticated level of protein regulation. Posttranslational modifications have the potential to regulate organelle function and interplay most likely by targeting both structural and signaling proteins throughout the cell, ultimately coordinating their responses. The potentials and limitations of existing proteomic technologies are also discussed emphasizing that the development of novel methods will enhance our ability to further investigate organelles and decode intracellular communication.