High-throughput proteomics and the fight against pathogens

Shotgun Proteomics as a Powerful Tool for the Study of the Proteomes of Plants, Their Pathogens, and Plant-Pathogen Interactions

The interaction between plants and pathogenic microorganisms is a multifaceted process mediated by both plant- and pathogen-derived molecules, including proteins, metabolites, and lipids. Large-scale proteome analysis can quantify the dynamics of proteins, biological pathways, and posttranslational modifications (PTMs) involved in the plant-pathogen interaction. Mass spectrometry (MS)-based proteomics has become the preferred method for characterizing proteins at the proteome and sub-proteome (e.g., the phosphoproteome) levels. MS-based proteomics can reveal changes in the quantitative state of a proteome and provide a foundation for understanding the mechanisms involved in plant-pathogen interactions. This review is intended as a primer for biologists that may be unfamiliar with the diverse range of methodology for MS-based shotgun proteomics, with a focus on techniques that have been used to investigate plant-pathogen interactions. We provide a summary of the essential steps required for shotgun proteomic studies of plants, pathogens and plant-pathogen interactions, including methods for protein digestion, identification, separation, and quantification. Finally, we discuss how protein PTMs may directly participate in the interaction between a pathogen and its host plant.

Host gene expression in wildlife disease: making sense of species-level responses

Emerging infectious diseases are significant threats to wildlife conservation, yet the impacts of pathogen exposure and infection can vary widely among host species. As such, conservation biologists and disease ecologists have increasingly aimed to understand species-specific host susceptibility using molecular methods. In particular, comparative gene expression assays have been used to contrast the transcriptomic responses of disease-resistant and disease-susceptible hosts to pathogen exposure. This work usually assumes that the gene expression responses of disease-resistant species will reveal the activation of molecular pathways contributing to host defence. However, results often show that disease-resistant hosts undergo little gene expression change following pathogen challenge. Here, we discuss the mechanistic implications of these "null" findings and offer methodological suggestions for future molecular studies of wildlife disease. First, we highlight that muted transcriptomic responses with minimal immune system recruitment may indeed be protective for nonsusceptible hosts if they limit immunopathology and promote pathogen tolerance in systems where susceptible hosts suffer from genetic dysregulation. Second, we argue that overly narrow investigation of responses to pathogen exposure may overlook important, constitutively active molecular pathways that underlie species-specific defences. Finally, we outline alternative study designs and approaches that complement interspecific transcriptomic comparisons, including intraspecific gene expression studies and genomic methods to detect signatures of selection. Collectively, these insights will help ecologists extract maximal information from conservation-relevant transcriptomic data sets, leading to a deeper understanding of host defences and, ultimately, the implementation of successful conservation interventions.

Plasma proteomic profiles differ between European and North American myotid bats colonized by Pseudogymnoascus destructans

Emerging fungal diseases have become challenges for wildlife health and conservation. North American hibernating bat species are threatened by the psychrophilic fungus Pseudogymnoascus destructans (Pd) causing the disease called white-nose syndrome (WNS) with unprecedented mortality rates. The fungus is widespread in North America and Europe, however, disease is not manifested in European bats. Differences in epidemiology and pathology indicate an evolution of resistance or tolerance mechanisms towards Pd in European bats. We compared the proteomic profile of blood plasma in healthy and Pd-colonized European Myotis myotis and North American Myotis lucifugus in order to identify pathophysiological changes associated with Pd colonization, which might also explain the differences in bat survival. Expression analyses of plasma proteins revealed differences in healthy and Pd-colonized M. lucifugus, but not in M. myotis. We identified differentially expressed proteins for acute phase response, constitutive and adaptive immunity, oxidative stress defence, metabolism and structural proteins of exosomes and desmosomes, suggesting a systemic response against Pd in North American M. lucifugus but not European M. myotis. The differences in plasma proteomic profiles between European and North American bat species colonized by Pd suggest European bats have evolved tolerance mechanisms towards Pd infection.

Identification of the proteins of Borrelia garinii interacting with human brain microvascular endothelial cells

Lyme borreliosis is one of the major tick-borne diseases in Europe. Events of the translocation of Borrelia across the blood-brain barrier (BBB) involve multiple interactions between borrelial surface proteins and receptors on the brain microvascular endothelial cells (hBMECs). In this study, we aimed to identify proteins of Borrelia that plausibly interact with hBMECs. The surface proteome of live Borrelia (a neuroinvasive strain of B. garinii) was crosslinked with biotin prior to its incubation with hBMECs. The interacting proteins were recovered by affinity purification, followed by SWATH-MS. Twenty-four interacting candidates were grouped into outer membrane proteins (n = 12) and inner membrane proteins (n = 12) based on the subcellular location as per the predictions of LocateP. Other algorithms like TMHMM 2.0 and LipoP, ontology search and literature review were subsequently applied to each of the identified protein candidates to shortlist the most probable interactors. Six proteins namely, LysM domain protein, BESBP-5, Antigen S1, CRASP-1 (Bg071), Erp23 protein and Mlp family Lipoprotein were selected to produce their recombinant forms and experimentally validate their interaction with hBMECs. All the recombinant proteins interacted with hBMECs, in ELISA and immunocytochemistry. We present here a high-throughput approach of generating a dataset of plausible borrelial ligands followed by a systematic bioinformatic pipeline to categorize the proteins for experimental validation.

Biomarkers of health and welfare: A One Health perspective from the laboratory side

A biomarker is any measurement reflecting an interaction between a biological system and a potential hazard, which may be chemical, physical, or biological. The One World, One Health concept established that human and animal health and the environmental state are highly interconnected, sharing common aspects that can be applied globally in these three components. In this paper, we review how the concept of One Health can be applied to biomarkers of health and welfare, with a special focus on five points that can be applied to any biomarker when it is expected to be used to evaluate the human, animal or environmental health. Three of these points are: (1) the different biomarkers that can be used, (2) the different sample types where the biomarkers can be analysed, and (3) the main methods that can be used for their measurement. In addition, we will evaluate two key points needed for adequate use of a biomarker in any situation: (4) a proper analytical validation in the sample that it is going to be used, and (5) a correct selection of the biomarker. It is expected that this knowledge will help to have a broader idea about the use of biomarkers of health and welfare and also will contribute to a better and more accurate use of these biomarkers having in mind their One Health perspective.

Proteomic and bioinformatic pipeline to screen the ligands of S. pneumoniae interacting with human brain microvascular endothelial cells

The mechanisms by which Streptococcus pneumoniae penetrates the blood-brain barrier (BBB), reach the CNS and causes meningitis are not fully understood. Adhesion of bacterial cells on the brain microvascular endothelial cells (BMECs), mediated through protein-protein interactions, is one of the crucial steps in translocation of bacteria across BBB. In this work, we proposed a systematic workflow for identification of cell wall associated ligands of pneumococcus that might adhere to the human BMECs. The proteome of S. pneumoniae was biotinylated and incubated with BMECs. Interacting proteins were recovered by affinity purification and identified by data independent acquisition (DIA). A total of 44 proteins were identified from which 22 were found to be surface-exposed. Based on the subcellular location, ontology, protein interactive analysis and literature review, five ligands (adhesion lipoprotein, endo-β-N-acetylglucosaminidase, PhtA and two hypothetical proteins, Spr0777 and Spr1730) were selected to validate experimentally (ELISA and immunocytochemistry) the ligand-BMECs interaction. In this study, we proposed a high-throughput approach to generate a dataset of plausible bacterial ligands followed by systematic bioinformatics pipeline to categorize the protein candidates for experimental validation. The approach proposed here could contribute in the fast and reliable screening of ligands that interact with host cells.

Vaccines Meet Big Data: State-of-the-Art and Future Prospects. From the Classical 3Is ("Isolate-Inactivate-Inject") Vaccinology 1.0 to Vaccinology 3.0, Vaccinomics, and Beyond: A Historical Overview

Vaccines are public health interventions aimed at preventing infections-related mortality, morbidity, and disability. While vaccines have been successfully designed for those infectious diseases preventable by preexisting neutralizing specific antibodies, for other communicable diseases, additional immunological mechanisms should be elicited to achieve a full protection. “New vaccines” are particularly urgent in the nowadays society, in which economic growth, globalization, and immigration are leading to the emergence/reemergence of old and new infectious agents at the animal–human interface. Conventional vaccinology (the so-called “vaccinology 1.0”) was officially born in 1796 thanks to the contribution of Edward Jenner. Entering the twenty-first century, vaccinology has shifted from a classical discipline in which serendipity and the Pasteurian principle of the three Is (isolate, inactivate, and inject) played a major role to a science, characterized by a rational design and plan (“vaccinology 3.0”). This shift has been possible thanks to Big Data, characterized by different dimensions, such as high volume, velocity, and variety of data. Big Data sources include new cutting-edge, high-throughput technologies, electronic registries, social media, and social networks, among others. The current mini-review aims at exploring the potential roles as well as pitfalls and challenges of Big Data in shaping the future vaccinology, moving toward a tailored and personalized vaccine design and administration.

Surface Proteome Biotinylation Combined with Bioinformatic Tools as a Strategy for Predicting Pathogen Interacting Proteins

Constant advancements in methodology and mass spectrometry instrumentation, genome sequencing and bioinformatic tools have enabled the identification of numerous pathogen proteomes. Identifying the pathogen interacting proteins by means of high-throughput techniques is key for understanding pathogen invasion and survival mechanisms and in such a way proposing specific proteins as pharmaceutical targets. Herein we describe the methodology for the enrichment and identification of pathogen surface proteome using cell surface protein biotinylation followed by LC-MS/MS and bioinformatic analyses of such data. This strategy is to be employed for the determination of protein subcellular localization and prediction of potential pathogen interacting proteins.

Exoproteomics of Pathogens: Analysis of Toxins and Other Virulence Factors by Proteomics

Pathogens are known to release in their environment a large range of toxins and other virulence factors. Their pathogenicity relies on this arsenal of exoproteins and their orchestrated release upon changing environmental conditions. Exoproteomics aims at describing and quantifying the proteins found outside of the cells, thus takes advantage of the most recent methodologies of next-generation proteomics. This approach has been applied with great success to a variety of pathogens increasing the fundamental knowledge on pathogenicity. In this chapter, we describe how the exoproteome should be prepared and handled for high-throughput identification of exoproteins and their quantitation by label-free shotgun proteomics. We also mentioned some bioinformatics tools for extracting information such as toxin similarity search.