Proteomic analysis of the lake trout (Salvelinus namaycush) heart and blood: The beginning of a comprehensive lake trout protein database.

Lake trout (Salvelinus namaycush) are a top-predator species in the Laurentian Great Lakes that are often used as bioindicators of chemical stressors in the ecosystem. Although many studies are done using these fish to determine concentrations of stressors like legacy persistent, bioaccumulative and toxic chemicals, there are currently no proteomic studies on the biological effects these stressors have on the ecosystem. This lack of proteomic studies on Great Lakes lake trout is because there is currently no complete, comprehensive protein database for this species. Here, we employed proteomics approaches to develop a lake trout protein database that could aid in future research on this fish, in particular exposomics and adductomics. The current study utilized heart tissue and blood from two lake trout. Our previous work using lake trout liver revealed 4194 potential protein hits in the NCBI databases and 3811 potential protein hits in the UniProtKB databases. In the current study, using the NCBI databases we identified 838 proteins for the heart and 580 proteins for the blood tissues in the biological replicate 1 (BR1) and 1180 potential protein hits for the heart and 561 potential protein hits for the blood in BR2. Similar results were obtained using the UniProtKB databases. This study builds on our previous work by continuing to build the first comprehensive lake trout protein database and provides insight into protein homology through evolutionary relationships. This data is available via the PRIDE partner repository with the dataset identifier PXD023970.

Mass Spectrometric (MS) Analysis of Proteins and Peptides.

The human genome is sequenced and comprised of ~30,000 genes, making humans just a little bit more complicated than worms or flies. However, complexity of humans is given by proteins that these genes code for because one gene can produce many proteins mostly through alternative splicing and tissue-dependent expression of particular proteins. In addition, post-translational modifications (PTMs) in proteins greatly increase the number of gene products or protein isoforms. Furthermore, stable and transient interactions between proteins, protein isoforms/proteoforms and PTM-ed proteins (protein-protein interactions, PPI) add yet another level of complexity in humans and other organisms. In the past, all of these proteins were analyzed one at the time. Currently, they are analyzed by a less tedious method: mass spectrometry (MS) for two reasons: 1) because of the complexity of proteins, protein PTMs and PPIs and 2) because MS is the only method that can keep up with such a complex array of features. Here, we discuss the applications of mass spectrometry in protein analysis.

A Critical Review of Bottom-Up Proteomics: The Good, the Bad, and the Future of this Field.

Proteomics is the field of study that includes the analysis of proteins, from either a basic science prospective or a clinical one. Proteins can be investigated for their abundance, variety of proteoforms due to post-translational modifications (PTMs), and their stable or transient protein-protein interactions. This can be especially beneficial in the clinical setting when studying proteins involved in different diseases and conditions. Here, we aim to describe a bottom-up proteomics workflow from sample preparation to data analysis, including all of its benefits and pitfalls. We also describe potential improvements in this type of proteomics workflow for the future.

Proteomic Analysis of the Lake Trout (Salvelinus namaycush) Liver Identifies Proteins from Evolutionarily Close and -Distant Fish Relatives.

Lake trout are used as bioindicators for toxics exposure in the Great Lakes ecosystem. Here the first lake trout (Salvelinus namaycush) liver proteomics study is performed and searched against specific databases: (NCBI and UniProtKB) Salvelinus, Salmonidae, Actinopterygii, and Oncorhynchus mykiss, and the more distant relative, Danio rerio. In the biological replicate 1 (BR1), technical replicate 1 (TR1), (BR1TR1), a large number of lake trout liver proteins are not in the Salvelinus protein database, suggesting that lake trout liver proteins have homology to some proteins from the Salmonidae family and Actinopterygii class, and to Oncorhynchus mykiss and Danio rerio, two more highly studied fish. In the NCBI search, 4194 proteins are identified: 3069 proteins in Actinopterygii, 1617 in Salmonidae, 68 in Salvelinus, 568 in Oncorhynchus mykiss, and 946 in Danio rerio protein databases. Similar results are observed in the UniProtKB searches of BR1RT1, as well as in a technical replicate (BR1TR2), and then in a second biological replicate experiment, with two technical replicates (BR2TR1 and BR2TR2). This study opens the possibility of identifying evolutionary relationships (i.e., adaptive mutations) between various groups (i.e., zebrafish, rainbow trout, Salmonidae, Salvelinus and lake trout) through evolutionary proteomics. Data are available via the PRIDE Q2 (PXD011924).

Mass Spectrometry for Proteomics-Based Investigation.

Within the past years, we have witnessed a great improvement is mass spectrometry (MS) and proteomics approaches in terms of instrumentation, protein fractionation, and bioinformatics. With the current technology, protein identification alone is no longer sufficient. Both scientists and clinicians want not only to identify the proteins, but also to identify the protein's post-translational modifications (PTMs), protein isoforms, protein truncation, protein-protein interactions (PPI), and protein quantitation. Here, we describe the principle of MS and proteomics, and strategies to identify proteins, protein's PTMs, protein isoforms, protein truncation, PPIs, and protein quantitation. We also discuss the strengths and weaknesses within this field. Finally, in our concluding remarks we assess the role of mass spectrometry and proteomics in the scientific and clinical settings, in the near future. This chapter provides an introduction and overview for subsequent chapters that will discuss specific MS proteomic methodologies and their application to specific medical conditions. Other chapters will also touch upon areas that expand beyond proteomics, such as lipidomics and metabolomics.

Proteomics and Non-proteomics Approaches to Study Stable and Transient Protein-Protein Interactions.

Of the 25,000-30,000 human genes, about 2 % code for proteins. However, there are about 1-2 million protein entities. This is primarily due to alternative splicing, post-translational modifications (PTMs) or protein-protein interactions. Proteomics sets out to identify proteins, their sequence and known modifications as well as their quantitation in a biological sample for the purpose of understanding biological processes, protein cellular functions, and their physiological and pathological involvement in diseases.Proteins interact at the molecular level with other proteins, nucleic acids, lipids, carbohydrates and metabolites to perform numerous cellular activities. Protein complexes can consist of sets of more stably (stable PPIs) and less stably (transient PPIs) interacting proteins or combination of both. Here, we discuss the proteomics and non-proteomics approaches to study stable and transient PPIs.

Developing Well-Annotated Species-Specific Protein Databases Using Comparative Proteogenomics.

Proteomics is a mass spectrometry-based discipline that aims to analyze proteomes and their functions. Many proteomic studies require well-developed protein databases for reference. However, most proteomes are not well-annotated, aside from model organisms. Techniques like six-frame translation, ab initio gene prediction, and EST databases can aid in maximizing the amount of proteins identified in proteomics experiments, however, each of these has its downfalls. Proteogenomics is a term used to describe the union of proteomics, genomics and transcriptomics to assist in the identification of peptides which would help build better annotated proteome databases. Here, current proteomic and proteogenomic methods will be reviewed, and an example of a comparative proteomics method using lake trout liver samples will be described.

Exploration of Nicotine Metabolism in Paenarthrobacter nicotinovorans pAO1 by Microbial Proteomics.

Proteomics, or the large-scale study of proteins, is a post-genomics field that, together with transcriptomics and metabolomics, has moved the study of bacteria to a new era based on system-wide understanding of bacterial metabolic and regulatory networks. The study of bacterial proteins or microbial proteomics has found a wide array of applications in many fields of microbiology, from food, clinical, and industrial microbiology to microbial ecology and physiology. The current chapter makes a brief technical introduction into the available approaches for the large-scale study of bacterial proteins using mass-spectrometry. Furthermore, the advantages and disadvantages of using bacteria for proteomics studies are indicated as well as several example studies where MS-based bacterial proteomics had a fundamental role in deciphering the scientific question. Finally, the proteomics study of nicotine catabolism in Paenarthrobacter nicotinovorans pAO1 using nanoLC-MS/MS is given as an in-depth example for possible applications of microbial proteomics.The nicotine degradation pathway functioning in Paenarthrobacter nicotinovorans is encoded by the catabolic megaplasmid pAO1 that contains about 40 nicotine-related genes making out the nic-gens cluster. Despite the promising biotechnological potential for the production of green-chemicals, only half of the nic-genes have been experimentally linked to nicotine. In an attempt to systematically identify all the proteins involved in nicotine degradation, a gel-based proteomics approach was used to identify a total of 801 proteins when Paenarthrobacter nicotinovorans was grown on three carbon sources: citrate, nicotine and nicotine and citrate. The differences in protein abundance showed that the bacterium is able to switch between deamination and demethylation in the lower nicotine pathway based on the available C source. Several pAO1 putative genes including a hypothetical polyketide cyclase have been shown to have a nicotine-dependent expression and we hypothesize that the polyketide cyclase would hydrolyze the N1-C6 bond from the pyridine ring with the formation of alpha-keto-glutaramate. Two chromosomal proteins, a malate dehydrogenase, and a D-3-phosphoglycerate dehydrogenase were shown to be strongly upregulated when nicotine was the sole carbon source and could be related to the production of the alpha-keto-glutaramate by the polyketide cyclase.

A Pilot Exploratory Proteomics Investigation of Mental Fatigue and Mental Energy.

Fatigue is a common and poorly understood problem that impacts approximately 45% of the United States (US) population. Fatigue has also been associated with fatigue-related driving accidents, school absences, decline in school performance and negative health outcomes. Fatigue has been linked to many diseases and is consistently underreported in medical care. Despite these high financial and societal costs, fatigue is a poorly understood problem and there is no consensus on how to measure fatigue. Proteomics is one of the most unbiased approach to measure differences in the protein levels from various biological fluids in two conditions, i.e. before and after mental exercise, aka fatigue. There are, however, challenges associated with such analyses: proteomics experiments are usually expensive and time consuming and also require a large number of participants. Here, we performed a proteomics experiment of three (pre- and post-fatigue) samples and also three matched controls (pre- and post-non-fatigue). We found no particular protein that has significant changes in fatigue sample upon treatment. We did note a potential association between changes in mental energy and Annexin A1. However, the study has value simply because it is an extra study in the field of fatigue, but also allows other to correlate our results with their results.

Trends in Analysis of Cortisol and Its Derivatives.

Determination of concentration of cortisol in various biological fluids can provide extensive information about a person's health. Historically, cortisol and its derivatives were (and still are) determined using immunoaffinity-based methods such as colorimetric ELISA assay, chemiluminescent immunoassay, fluorescence assays, radioimmunoassay, electrochemiluminescence immunoassay, immunochromatographic test, or sensors and immunosensors. Recently, mass spectrometry (MS)-based methods started to be used in determination of cortisol and its derivatives. These MS methods are net superior to immunoaffinity-based assays, but are not easily applicable and are also time-consuming and price prohibitive. Furthermore the standard MS instruments used are triple quadrupole instruments. Here we review the literature on the MS and non-MS based methods for determination of cortisol and its derivatives and also explore the use of a less used quadrupole-time of flight instrument in determination of these compounds.

Salivary proteomics and biomarkers in neurology and psychiatry.

Biomarkers are greatly needed in the fields of neurology and psychiatry, to provide objective and earlier diagnoses of CNS conditions. Proteomics and other omics MS-based technologies are tools currently being utilized in much recent CNS research. Saliva is an interesting alternative biomaterial for the proteomic study of CNS disorders, with several advantages. Collection is noninvasive and saliva has many proteins. It is easier to collect than blood and can be collected by professionals without formal medical training. For psychiatric and neurological patients, supplying a saliva sample is less anxiety-provoking than providing a blood sample, and is less embarrassing than producing a urine specimen. The use of saliva as a biomaterial has been researched for the diagnosis of and greater understanding of several CNS conditions, including neurodegenerative diseases, autism, and depression. Salivary biomarkers could be used to rule out nonpsychiatric conditions that are often mistaken for psychiatric/neurological conditions, such as fibromyalgia, and potentially to assess cognitive ability in individuals with compromised brain function. As MS and omics technology advances, the sensitivity and utility of assessing CNS conditions using distal human biomaterials such as saliva is becoming increasingly possible.