Comparison of label-free methods for quantifying human proteins by shotgun proteomics

Acid Sphingomyelinase regulates the localization and trafficking of palmitoylated proteins

In human, loss of acid sphingomyelinase (ASM/SMPD1) causes Niemann–Pick disease, type A. ASM hydrolyzes sphingomyelins to produce ceramides but protein targets of ASM remain largely unclear. Our mass spectrometry-based proteomic analyses have identified >100 proteins associated with the ASM-dependent, detergent-resistant membrane microdomains (lipid rafts), with >60% of these proteins being palmitoylated, including SNAP23, Src-family kinases Yes and Lyn, and Ras and Rab family small GTPases. Inactivation of ASM abolished the presence of these proteins in the plasma membrane, with many of them trapped in the Golgi. While palmitoylation inhibitors and palmitoylation mutants phenocopied the effects of ASM inactivation, we demonstrated that ASM is required for the transport of palmitoylated proteins, such as SNAP23 and Lyn, from the Golgi to the plasma membrane without affecting palmitoylation directly. Importantly, ASM delivered extracellularly can regulate the trafficking of SNAP23 from the Golgi to the plasma membrane. Our studies suggest that ASM, acting at the plasma membrane to produce ceramides, regulates the localization and trafficking of the palmitoylated proteins.

Summary: Acid sphingomyelinase (ASM) regulates palmitoylated protein trafficking and localization.

Probabilistic Limit of Detection for Ricin Identification Using a Shotgun Proteomics Assay

Robust and highly specific methods for the detection of the protein toxin ricin are of interest to the law enforcement community. In previous studies, methods based on liquid chromatography-tandem mass spectrometry shotgun proteomics have been proposed. The successful implementation of this approach relies on specific data evaluation criteria addressing (1) the quality of the mass spectrometric data, (2) the confidence of peptide identifications (peptide-spectrum matches), and (3) the number and sequence specificity of peptides detected. We present such data evaluation criteria and use a novel approach to establish the limit of detection for this ricin assay. Specifically, we use logistic regression to determine the probability of detection for individual ricin peptides at different concentrations. We then apply basic rules from probability theory, combining these individual peptide probabilities into an overall assay limit of detection. This procedure yields an assay limit of detection for ricin at 42.5 ng on column or 21.25 ng/μL for a 2-μL injection. We also show that, despite the conventional wisdom that detergents are deleterious to mass spectrometric analyses, the presence of Tween-20 did not prevent detection of ricin peptides, and indeed assays performed in buffers that included Tween-20 gave better results than assays performed using other buffer formulations with or without detergent removal.

Early urine proteome changes in the Walker-256 tail-vein injection rat model

Detection of cancer at its early stage is important for treatment. Urine, which is not regulated by homeostatic mechanisms, reflects early systemic changes throughout the whole body and can be used for the early detection of cancer. In this study, the Walker-256 tail-vein injection rat model was established to find whether the urine proteome could reflect early changes if tumor grown in lung. Urine samples from the control group (n = 7) and Walker-256 tail-vein injection group (n = 7) on days 2, 4, 6 and 9 were analyzed by label-free proteomic quantitative methods. On day 2, when lung tumor nodules did not appear, 62 differential proteins were identified. They were associated with epithelial cell differentiation, regulation of immune system processes and the classical complement activation pathway. On day 4, when lung tumor nodules appeared, 72 differential proteins were identified. They were associated with the innate immune response and positive regulation of phagocytosis. On day 6, when body weight began to decrease, 117 differential proteins were identified. On day 9, the identified 125 differential proteins were associated with the B cell receptor signaling pathway and the positive regulation of B cell activation. Our results indicate that (1) the urine proteome changed even on the second day after tail-vein injection of Walker-256 cells and that (2) compared to previous studies, the urine proteomes were different when the same cancer cells were grown in different organs.

Refinements of LC-MS/MS Spectral Counting Statistics Improve Quantification of Low Abundance Proteins

Mass spectrometry-based spectral count has been a common choice of label-free proteome quantification due to the simplicity for the sample preparation and data generation. The discriminatory nature of spectral count in the MS data-dependent acquisition, however, inherently introduces the spectral count variation for low-abundance proteins in multiplicative LC-MS/MS analysis, which hampers sensitive proteome quantification. As many low-abundance proteins play important roles in cellular processes, deducing low-abundance proteins in a quantitatively reliable manner greatly expands the depth of biological insights. Here, we implemented the Moment Adjusted Imputation error model in the spectral count refinement as a post PLGEM-STN for improving sensitivity for quantitation of low-abundance proteins by reducing spectral count variability. The statistical framework, automated spectral count refinement by integrating the two statistical tools, was tested with LC-MS/MS datasets of MDA-MB468 breast cancer cells grown under normal and glucose deprivation conditions. We identified about 30% more quantifiable proteins that were found to be low-abundance proteins, which were initially filtered out by the PLGEM-STN analysis. This newly developed statistical framework provides a reliable abundance measurement of low-abundance proteins in the spectral count-based label-free proteome quantification and enabled us to detect low-abundance proteins that could be functionally important in cellular processes.

Urine proteome changes in rats subcutaneously inoculated with approximately ten tumor cells

Background

Biomarkers are changes associated with the disease. Urine is not subject to homeostatic control and therefore accumulates very early changes, making it an ideal biomarker source. Usually, we have performed urinary biomarker studies involving at least thousands of tumor cells. However, no tumor starts from a thousand tumor cells. We therefore examined urine proteome changes in rats subcutaneously inoculated with approximately ten tumor cells.

Methods

Here, we serially diluted Walker-256 carcinosarcoma cells to a concentration of 10²/mL and subcutaneously inoculated 0.1 mL of these cells into nine rats. The urine proteomes on days 0, 13 and 21 were analyzed by liquid chromatography coupled with tandem mass spectrometry.

Results

Hierarchical clustering analysis showed that the urine proteome of each sample at three time points were clustered into three clusters, indicating the good consistency of these nine rats when inoculated with the same limited tumor cells. Differential proteins on days 13 and 21 were mainly associated with cell adhesion, autophagic cell death, changes in extracellular matrix organization, angiogenesis, and the pentose phosphate pathway. All of these enriched functional processes were reported to contribute to tumor progression and could not be enriched through random allocation analysis.

Conclusions

Our results indicated that (1) the urine proteome reflects changes associated with cancer even with only approximately ten tumor cells in the body and that (2) the urine proteome reflects pathophysiological changes in the body with extremely high sensitivity and provides potential for a very early screening process of clinical patients.

Contribution of Mass Spectrometry-Based Proteomics to Discoveries in Developmental Biology

Understanding multicellular organism development from a molecular perspective is no small feat, yet this level of comprehension affords clinician-scientists the ability to identify root causes and mechanisms of congenital diseases. Inarguably, the maturation of molecular biology tools has significantly contributed to the identification of genetic loci that underlie normal and aberrant developmental programs. In combination with cell biology approaches, these tools have begun to elucidate the spatiotemporal expression and function of developmentally-regulated proteins. The emergence of quantitative mass spectrometry (MS) for biological applications has accelerated the pace at which these proteins can be functionally characterized, driving the construction of an increasingly detailed systems biology picture of developmental processes. Here, we review the quantitative MS-based proteomic technologies that have contributed significantly to understanding the role of proteome regulation in developmental processes. We provide a brief overview of these methodologies, focusing on their ability to provide precise and accurate proteome measurements. We then highlight the use of discovery-based and targeted mass spectrometry approaches in model systems to study cellular differentiation states, tissue phenotypes, and spatiotemporal subcellular organization. We also discuss the current application and future perspectives of MS proteomics to study PTM coordination and the role of protein complexes during development.

Recent advances in mass spectrometry (MS)-based glycoproteomics in complex biological samples

Protein glycosylation plays a key role in various biological processes and disease-related pathological progression. Mass spectrometry (MS)-based glycoproteomics is a powerful approach that provides a system-wide profiling of the glycoproteome in a high-throughput manner. There have been numerous significant technological advances in this field, including improved glycopeptide enrichment, hybrid fragmentation techniques, emerging specialized software packages, and effective quantitation strategies, as well as more dedicated workflows. With increasingly sophisticated glycoproteomics tools on hand, researchers have extensively adapted this approach to explore different biological systems both in terms of in-depth glycoproteome profiling and comparative glycoproteome analysis. Quantitative glycoproteomics enables researchers to discover novel glycosylation-based biomarkers in various diseases with potential to offer better sensitivity and specificity for disease diagnosis. In this review, we present recent methodological developments in MS-based glycoproteomics and highlight its utility and applications in answering various questions in complex biological systems.

Affinity Purification of NF1 Protein-Protein Interactors Identifies Keratins and Neurofibromin Itself as Binding Partners

Neurofibromatosis Type 1 (NF1) is caused by pathogenic variants in the NF1 gene encoding neurofibromin. Definition of NF1 protein–protein interactions (PPIs) has been difficult and lacks replication, making it challenging to define binding partners that modulate its function. We created a novel tandem affinity purification (TAP) tag cloned in frame to the 3’ end of the full-length murine Nf1 cDNA (mNf1). We show that this cDNA is functional and expresses neurofibromin, His-Tag, and can correct p-ERK/ERK ratios in NF1 null HEK293 cells. We used this affinity tag to purify binding partners with Strep-Tactin^®XT beads and subsequently, identified them via mass spectrometry (MS). We found the tagged mNf1 can affinity purify human neurofibromin and vice versa, indicating that neurofibromin oligomerizes. We identify 21 additional proteins with high confidence of interaction with neurofibromin. After Metacore network analysis of these 21 proteins, eight appear within the same network, primarily keratins regulated by estrogen receptors. Previously, we have shown that neurofibromin levels negatively regulate keratin expression. Here, we show through pharmacological inhibition that this is independent of Ras signaling, as the inhibitors, selumetinib and rapamycin, do not alter keratin expression. Further characterization of neurofibromin oligomerization and binding partners could aid in discovering new neurofibromin functions outside of Ras regulation, leading to novel drug targets.

Proteomic analysis of urinary extracellular vesicles reveal biomarkers for neurologic disease

Background

Extracellular vesicles (EVs) harbor thousands of proteins that hold promise for biomarker development. Usually difficult to purify, EVs in urine are relatively easily obtained and have demonstrated efficacy for kidney disease prediction. Herein, we further characterize the proteome of urinary EVs to explore the potential for biomarkers unrelated to kidney dysfunction, focusing on Parkinson's disease (PD).

Methods

Using a quantitative mass spectrometry approach, we measured urinary EV proteins from a discovery cohort of 50 subjects. EVs in urine were classified into subgroups and EV proteins were ranked by abundance and variability over time. Enriched pathways and ontologies in stable EV proteins were identified and proteins that predict PD were further measured in a cohort of 108 subjects.

Findings

Hundreds of commonly expressed urinary EV proteins with stable expression over time were distinguished from proteins with high variability. Bioinformatic analyses reveal a striking enrichment of endolysosomal proteins linked to Parkinson's, Alzheimer's, and Huntington's disease. Tissue and biofluid enrichment analyses show broad representation of EVs from across the body without bias towards kidney or urine proteins. Among the proteins linked to neurological diseases, SNAP23 and calbindin were the most elevated in PD cases with 86% prediction success for disease diagnosis in the discovery cohort and 76% prediction success in the replication cohort.

Interpretation

Urinary EVs are an underutilized but highly accessible resource for biomarker discovery with particular promise for neurological diseases like PD.

LIM-domain transcription complexes interact with ring-finger ubiquitin ligases and thereby impact islet β-cell function

Diabetes is characterized by a loss of β-cell mass, and a greater understanding of the transcriptional mechanisms governing β-cell function is required for future therapies. Previously, we reported that a complex of the Islet-1 (Isl1) transcription factor and the co-regulator single-stranded DNA-binding protein 3 (SSBP3) regulates the genes necessary for β-cell function, but few proteins are known to interact with this complex in β-cells. To identify additional components, here we performed SSBP3 reverse-cross-linked immunoprecipitation (ReCLIP)- and MS-based experiments with mouse β-cell extracts and compared the results with those from our previous Isl1 ReCLIP study. Our analysis identified the E3 ubiquitin ligases ring finger protein 20 (RNF20) and RNF40, factors that in nonpancreatic cells regulate transcription through imparting monoubiquitin marks on histone H2B (H2Bub1), a precursor to histone H3 lysine 4 trimethylation (H3K4me3). We hypothesized that RNF20 and RNF40 regulate similar genes as those regulated by Isl1 and SSBP3 and are important for β-cell function. We observed that Rnf20 and Rnf40 depletion reduces β-cell H2Bub1 marks and uncovered several target genes, including glucose transporter 2 (Glut2), MAF BZIP transcription factor A (MafA), and uncoupling protein 2 (Ucp2). Strikingly, we also observed that Isl1 and SSBP3 depletion reduces H2Bub1 and H3K4me3 marks, suggesting that they have epigenetic roles. We noted that the RNF complex is required for glucose-stimulated insulin secretion and normal mitochondrial reactive oxygen species levels. These findings indicate that RNF20 and RNF40 regulate β-cell gene expression and insulin secretion and establish a link between Isl1 complexes and global cellular epigenetics.

Identification of key modules and hub genes for small-cell lung carcinoma and large-cell neuroendocrine lung carcinoma by weighted gene co-expression network analysis of clinical tissue-proteomes

Small-cell lung carcinoma (SCLC) and large-cell neuroendocrine lung carcinoma (LCNEC) are high-grade lung neuroendocrine tumors (NET). However, comparative protein expression within SCLC and LCNEC remains unclear. Here, protein expression profiles were obtained via mass spectrometry-based proteomic analysis. Weighted gene co-expression network analysis (WGCNA) identified co-expressed modules and hub genes. Of 34 identified modules, six were significant and selected for protein-protein interaction (PPI) network analysis and pathway enrichment. Within the six modules, the activation of cellular processes and complexes, such as alternative mRNA splicing, translation initiation, nucleosome remodeling and deacetylase (NuRD) complex, SWItch/Sucrose Non-Fermentable (SWI/SNF) superfamily-type complex, chromatin remodeling pathway, and mRNA metabolic processes, were significant to SCLC. Modules enriched in processes, including signal recognition particle (SRP)-dependent co-translational protein targeting to membrane, nuclear-transcribed mRNA catabolic process of nonsense-mediated decay (NMD), and cellular macromolecule catabolic process, were characteristically activated in LCNEC. Novel high-degree hub genes were identified for each module. Master and upstream regulators were predicted via causal network analysis. This study provides an understanding of the molecular differences in tumorigenesis and malignancy between SCLC and LCNEC and may help identify potential therapeutic targets.

Multi-Omics Profiling for NF1 Target Discovery in Neurofibromin (NF1) Deficient Cells

Loss of NF1 is an oncogenic driver. In efforts to define pathways responsible for the development of neurofibromas and other cancers, transcriptomic and proteomic changes are evaluated in a non-malignant NF1 null cell line. NF1 null HEK293 cells were created using CRISPR/Cas9 technology and they are compared to parental cells that express neurofibromin. A total of 1222 genes and 132 proteins are found to be differentially expressed. The analysis is integrated to identify eight transcripts/proteins that are differentially regulated in both analyses. Metacore Pathway analysis identifies Neurogenesis NGF/TrkA MAPK-mediated signaling alterations. Next, the data set is compared with other published studies that involve analysis of cells or tumors deficient for NF1 and it is found that 141 genes recur in the sample and others; only thirteen of these genes recur in two or more studies. Genes/proteins of interest are validated via q-RT-PCR or Western blot. It is shown that KRT8 and 14-3-3σ protein levels respond to exogenously introduced mNf1 cDNA. Hence, transcripts/proteins that respond to neurofibromin levels are identified and they can potentially be used as biomarkers.

Hair Proteome Variation at Different Body Locations on Genetically Variant Peptide Detection for Protein-Based Human Identification

Human hair contains minimal intact nuclear DNA for human identification in forensic and archaeological applications. In contrast, proteins offer a pathway to exploit hair evidence for human identification owing to their persistence, abundance, and derivation from DNA. Individualizing single nucleotide polymorphisms (SNPs) are often conserved as single amino acid polymorphisms in genetically variant peptides (GVPs). Detection of GVP markers in the hair proteome via high-resolution tandem mass spectrometry permits inference of SNPs with known statistical probabilities. To adopt this approach for forensic investigations, hair proteomic variation and its effects on GVP identification must first be characterized. This research aimed to assess variation in single-inch head, arm, and pubic hair, and discover body location-invariant GVP markers to distinguish individuals. Comparison of protein profiles revealed greater body location-specific variation in keratin-associated proteins and intracellular proteins, allowing body location differentiation. However, robust GVP markers derive primarily from keratins that do not exhibit body location-specific differential expression, supporting GVP identification independence from hair proteomic variation at the various body locations. Further, pairwise comparisons of GVP profiles with 8 SNPs demonstrated greatest interindividual variation and high intraindividual consistency, enabling similar differentiative potential of individuals using single hairs irrespective of body location origin.

Proteomics of diphtheria toxoid vaccines reveals multiple proteins that are immunogenic and may contribute to protection of humans against Corynebacterium diphtheriae

Introduced for mass immunization in the 1920s, vaccines against diphtheria are among the oldest and safest vaccines known. The basic principle of their production is the inactivation of purified diphtheria toxin by formaldehyde cross-linking, which converts the potentially fatal toxin in a completely harmless protein aggregate, which is still immunogenic. Since in addition to diphtheria toxin also other proteins may be secreted by Corynebacterium diphtheriae during cultivation, we assumed that diphtheria toxoid might not be the only component present in the vaccine. To address this question, we established a protocol to reverse formaldehyde cross-linking and carried out mass spectrometric analyses. Different secreted, membrane-associated and cytoplasmic proteins of C. diphtheriae were detected in several vaccine preparations from across the world. Based on these results, bioinformatics and Western blot analyses were applied to characterize if these proteins are immunogenic and may therefore support protection against C. diphtheriae. In frame of this study, we could show that the C. diphtheriae toxoid vaccines induce antibodies against different C. diphtheriae proteins and against diphtheria toxin secreted by Corynebacterium ulcerans, an emerging pathogen which is outnumbering C. diphtheriae as cause of diphtheria-like illness in Western Europe.

More than a Toxin: Protein Inventory of Clostridium tetani Toxoid Vaccines

Clostridium tetani is the etiological agent of tetanus, a life-threatening bacterial infection. The most efficient protection strategy against tetanus is a vaccination with the C. tetani neurotoxin, which is inactivated by formaldehyde-crosslinking. Since we assumed that besides the tetanus toxin, other proteins of C. tetani may also be present in toxoid preparations, we analyzed commercially available vaccines from different countries in respect to their protein content using mass spectrometry. In total 991 proteins could be identified in all five analyzed vaccines, 206 proteins were common in all analyzed vaccines and 54 proteins from the 206 proteins were potential antigens. The additionally present proteins may contribute at least partially to protection against C. tetani infection by supporting the function of the vaccine against the devastating effects of the tetanus toxin indirectly. Two different label-free protein quantification methods were applied for an estimation of protein contents. Similar results were obtained with a Total Protein Approach (TPA)-based method and Protein Discoverer 2.2 software package based on the minora algorithm. Depending on the tetanus toxoid vaccine and the quantification method used, tetanus neurotoxin contributes between 14 and 76 % to the total C. tetani protein content and varying numbers of other C. tetani proteins were detected.

Novel biomarkers distinguishing pancreatic head Cancer from distal cholangiocarcinoma based on proteomic analysis

BACKGROUND

The differentiation between pancreatic head cancer (PHC) and distal cholangiocarcinoma (DCC) can be challenging because of their anatomical and histopathological similarity. This is an important problem, because the distinction has important implications for the treatment of these malignancies. However, there are no biomarkers for the differential diagnosis of PHC and DCC. The present study aimed to identify novel diagnostic immunohistochemical biomarkers to distinguish PHC from DCC.

METHODS

Liquid chromatography tandem mass spectrometry (LC-MS/MS) was employed to detect candidate proteins. Ten PHC and 8 DCC specimens were analyzed by LC-MS/MS. Selected proteins were evaluated, using immunohistochemical analysis, to determine whether they would be appropriate biomarkers. Finally, we generated biomarker panels to improve diagnostic accuracy. We applied these panels to clinically difficult cases (cases in which different diagnoses were made before and after operation).

RESULTS

Consequently, 1820 proteins were detected using LC-MS/MS. Fifteen differentially expressed proteins were selected as candidates based on semi-quantitative comparison. We first performed immunohistochemical staining on samples from the small cohort group (12 PHCs and 12 DCCs) using 15 candidates. KRT17, ANXA10, TMEM109, PTMS, and ATP1B1 showed favorable performances and were tested in the next large cohort group (72 PHCs and 74 DCCs). Based on immunohistochemical analysis, KRT17 performed best for the diagnosis of PHC as a single marker; additionally, PTMS exhibited good performance for the diagnosis of DCCs. Moreover, we indicated the KRT17+/ANXA10+/PTMS- staining pattern as a biomarker panel for the correct diagnosis of PHC and KRT17-/ANXA10-/PTMS+ for the diagnosis of DCC. After immunohistochemical staining for examining samples from the clinically difficult cases, these panels showed satisfactory diagnostic performance with 85.7% (6/7) accuracy.

CONCLUSIONS

We conclude that 5 proteins and 2 biomarker panels are promising for distinguishing PHC from DCC, and patients with an equivocal diagnosis would benefit from the application of these biomarkers. Confirmatory studies are needed to generalize these findings to other populations.

Human and rodent temporal lobe epilepsy is characterized by changes in O-GlcNAc homeostasis that can be reversed to dampen epileptiform activity

Temporal Lobe Epilepsy (TLE) is frequently associated with changes in protein composition and post-translational modifications (PTM) that exacerbate the disorder. O-linked-β-N-acetyl glucosamine (O-GlcNAc) is a PTM occurring at serine/threonine residues that is derived from and closely associated with metabolic substrates. The enzymes O-GlcNActransferase (OGT) and O-GlcNAcase (OGA) mediate the addition and removal, respectively, of the O-GlcNAc modification. The goal of this study was to characterize OGT/OGA and protein O-GlcNAcylation in the epileptic hippocampus and to determine and whether direct manipulation of these proteins and PTM's alter epileptiform activity. We observed reduced global and protein specific O-GlcNAcylation and OGT expression in the kainate rat model of TLE and in human TLE hippocampal tissue. Inhibiting OGA with Thiamet-G elevated protein O-GlcNAcylation, and decreased both seizure duration and epileptic spike events, suggesting that OGA may be a therapeutic target for seizure control. These findings suggest that loss of O-GlcNAc homeostasis in the kainate model and in human TLE can be reversed via targeting of O-GlcNAc related pathways.

Dark-colored maple syrup treatment induces S-phase cell cycle arrest via reduced proliferating cell nuclear antigen expression in colorectal cancer cells

Maple syrup is a natural sweetener that is consumed worldwide. It has been previously reported that dark-colored maple syrup exerts an inhibitory effect on colorectal cancer (CRC) proliferation and invasion. In the present study, the underlying mechanism of CRC cell growth inhibition was examined with dark-colored maple syrup treatment using a shotgun liquid chromatography-tandem mass spectrometry-based global proteomic approach. Applying a semi-quantitative method based on spectral counting, 388 proteins were identified with expression changes of >1.5-fold following dark-colored maple syrup treatment. Gene Ontology analysis revealed that these proteins possessed cell cycle-associated functions. It was also indicated that CRC cells treated with dark-colored maple syrup exhibited decreased proliferating cell nuclear antigen (PCNA) expression and S-phase cell cycle arrest. Dark-colored maple syrup treatment also resulted in altered expression of cell cycle-associated genes, including cyclin-dependent kinase (CDK)4 and CDK6. In conclusion, these data suggested that dark-colored maple syrup induced S-phase cell cycle arrest in CRC cells by reducing the expression of PCNA and regulating cell cycle-associated genes. These findings suggest that dark-colored maple syrup may be a source of compounds for the development of novel drugs for colorectal cancer treatment.

The Methods Employed in Mass Spectrometric Analysis of Posttranslational Modifications (PTMs) and Protein-Protein Interactions (PPIs)

Mass Spectrometry (MS) has revolutionized the way we study biomolecules, especially proteins, their interactions and posttranslational modifications (PTM). As such MS has established itself as the leading tool for the analysis of PTMs mainly because this approach is highly sensitive, amenable to high throughput and is capable of assigning PTMs to specific sites in the amino acid sequence of proteins and peptides. Along with the advances in MS methodology there have been improvements in biochemical, genetic and cell biological approaches to mapping the interactome which are discussed with consideration for both the practical and technical considerations of these techniques. The interactome of a species is generally understood to represent the sum of all potential protein-protein interactions. There are still a number of barriers to the elucidation of the human interactome or any other species as physical contact between protein pairs that occur by selective molecular docking in a particular spatiotemporal biological context are not easily captured and measured.PTMs massively increase the complexity of organismal proteomes and play a role in almost all aspects of cell biology, allowing for fine-tuning of protein structure, function and localization. There are an estimated 300 PTMS with a predicted 5% of the eukaryotic genome coding for enzymes involved in protein modification, however we have not yet been able to reliably map PTM proteomes due to limitations in sample preparation, analytical techniques, data analysis, and the substoichiometric and transient nature of some PTMs. Improvements in proteomic and mass spectrometry methods, as well as sample preparation, have been exploited in a large number of proteome-wide surveys of PTMs in many different organisms. Here we focus on previously published global PTM proteome studies in the Apicomplexan parasites T. gondii and P. falciparum which offer numerous insights into the abundance and function of each of the studied PTM in the Apicomplexa. Integration of these datasets provide a more complete picture of the relative importance of PTM and crosstalk between them and how together PTM globally change the cellular biology of the Apicomplexan protozoa. A multitude of techniques used to investigate PTMs, mostly techniques in MS-based proteomics, are discussed for their ability to uncover relevant biological function.

Microwave supported hydrolysis prepares Bacillus spores for proteomic analysis

Rapid identification of Bacillus spores in the environment has depended primarily on a family of small acid soluble proteins (SASPs) as biomarkers. However, SASP sequences and molecular masses are similar or identical in some critical cases. For example, some strains of B. subtilis, and B. thuringiensis cannot be distinguished from strains of B. anthracis based on SASPs. Consequently, additional or alternative biomarkers should be sought. In this study microwave-assisted hot acid hydrolysis was coupled with mass spectrometry as a potentially powerful approach to the rapid automatable characterization of Bacillus spores. Hot acid provides lysis of the spores, Asp-selective hydrolysis of proteins, and peptides compatible with automated analysis of either peptide fingerprints or tandem mass spectra. Peptide biomarkers are compared here for a selection of Bacillus spores, and peptides unique to each spore type are identified.

Discovering cellular protein-protein interactions: Technological strategies and opportunities

The analysis of protein interaction networks is one of the key challenges in the study of biology. It connects genotypes to phenotypes, and disruption often leads to diseases. Hence, many technologies have been developed to study protein-protein interactions (PPIs) in a cellular context. The expansion of the PPI technology toolbox however complicates the selection of optimal approaches for diverse biological questions. This review gives an overview of the binary and co-complex technologies, with the former evaluating the interaction of two co-expressed genetically tagged proteins, and the latter only needing the expression of a single tagged protein or no tagged proteins at all. Mass spectrometry is crucial for some binary and all co-complex technologies. After the detailed description of the different technologies, the review compares their unique specifications, advantages, disadvantages, and applicability, while highlighting opportunities for further advancements.

A Guide to Mass Spectrometry-Based Quantitative Proteomics

Proteomics has become an attractive science in the postgenomic era, given its capacity to identify up to thousands of molecules in a single, complex sample and quantify them in an absolute and/or relative manner. The use of these techniques enables understanding of cellular and molecular mechanisms of diseases and other biological conditions, as well as identification and screening of protein biomarkers. Here we provide a straightforward, up-to-date compilation and comparison of the main quantitation techniques used in comparative proteomics such as in vitro and in vivo stable isotope labeling and label-free techniques. Additionally, this chapter includes common methods for data acquisition in proteomics and some appropriate methods for data processing. This compilation can serve as a reference for scientists who are new to, or already familiar with, quantitative proteomics.

Characterization of paucibacillary ileal lesions in sheep with subclinical active infection by Mycobacterium avium subsp. paratuberculosis

Paratuberculosis (PTB) or Johne's disease is a contagious enteritis of ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP). Ovine PTB is less understood than bovine PTB, especially concerning paucibacillary infection and its evolution into clinical disease. We combined shotgun proteomics, histopathology and immunohistochemistry for the characterization of ileal tissues collected from seven asymptomatic sheep negative to serum ELISA, positive to feces and tissue MAP IS900 and F57 PCR, histologically classified as paucibacillary, actively infected, together with 3 MAP-free controls (K). Following shotgun proteomics with label-free quantitation and differential analysis, 96 proteins were significantly changed in PTB vs K, and were mostly involved in immune defense processes and in the macrophage-MAP interaction. Principal component analysis (PCA) of protein abundances highlighted two PTB sample clusters, PTB1 and PTB2, indicating a dichotomy in their proteomic profiles. This was in line with the PCA of histopathology data and was related to features of type 2 (PTB1) and type 3a (PTB2) lesions, respectively. PTB2 proteomes differed more than PTB1 proteomes from K: 43 proteins changed significantly only in PTB2 and 11 only in PTB1. The differential proteins cathelicidin, haptoglobin, S100A8 and S100A9 were evaluated by immunohistochemistry. K tissues were negative to cathelicidin and haptoglobin and sparsely positive to S100A8 and S100A9. PTB tissues were positive to all four proteins, with significantly more cells in PTB2 than in PTB1. In conclusion, we described several pathways altered in paucibacillary PTB, highlighted some proteomic differences among paucibacillary PTB cases, and identified potential markers for disease understanding, staging, and detection.

Robust determination of differential abundance in shotgun proteomics using nonparametric statistics

Label-free shotgun mass spectrometry enables the detection of significant changes in protein abundance between different conditions. Due to often limited cohort sizes or replication, large ratios of potential protein markers to number of samples, as well as multiple null measurements pose important technical challenges to conventional parametric models. From a statistical perspective, a scenario similar to that of unlabeled proteomics is encountered in genomics when looking for differentially expressed genes. Still, the difficulty of detecting a large fraction of the true positives without a high false discovery rate is arguably greater in proteomics due to even smaller sample sizes and peptide-to-peptide variability in detectability. These constraints argue for nonparametric (or distribution-free) tests on normalized peptide values, thus minimizing the number of free parameters, as well as for measuring significance with permutation testing. We propose such a procedure with a class-based statistic, no parametric assumptions, and no parameters to select other than a nominal false discovery rate. Our method was tested on a new dataset which is available via ProteomeXchange with identifier PXD006447. The dataset was prepared using a standard proteolytic digest of a human protein mixture at 1.5-fold to 3-fold protein concentration changes and diluted into a constant background of yeast proteins. We demonstrate its superiority relative to other approaches in terms of the realized sensitivity and realized false discovery rates determined by ground truth, and recommend it for detecting differentially abundant proteins from MS data.

Changes in proteome solubility indicate widespread proteostatic disruption in mouse models of neurodegenerative disease

The deposition of pathologic misfolded proteins in neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, frontotemporal dementia and amyotrophic lateral sclerosis is hypothesized to burden protein homeostatic (proteostatic) machinery, potentially leading to insufficient capacity to maintain the proteome. This hypothesis has been supported by previous work in our laboratory, as evidenced by the perturbation of cytosolic protein solubility in response to amyloid plaques in a mouse model of Alzheimer's amyloidosis. In the current study, we demonstrate changes in proteome solubility are a common pathology to mouse models of neurodegenerative disease. Pathological accumulations of misfolded tau, α-synuclein and mutant superoxide dismutase 1 in CNS tissues of transgenic mice were associated with changes in the solubility of hundreds of CNS proteins in each model. We observed that changes in proteome solubility were progressive and, using the rTg4510 model of inducible tau pathology, demonstrated that these changes were dependent upon sustained expression of the primary pathologic protein. In all of the models examined, changes in proteome solubility were robust, easily detected, and provided a sensitive indicator of proteostatic disruption. Interestingly, a subset of the proteins that display a shift towards insolubility were common between these different models, suggesting that a specific subset of the proteome is vulnerable to proteostatic disruption. Overall, our data suggest that neurodegenerative proteinopathies modeled in mice impose a burden on the proteostatic network that diminishes the ability of neural cells to prevent aberrant conformational changes that alter the solubility of hundreds of abundant cellular proteins.

Differential protein expression in human knee articular cartilage and medial meniscus using two different proteomic methods: a pilot analysis

Background

Proteomics is an emerging field in the study of joint disease. Our two aims with this pilot analysis were to compare healthy human knee articular cartilage with meniscus, two tissues both known to become affected in the osteoarthritic disease process, and to compare two mass spectrometry (MS)-based methods: data-dependent acquisition (DDA) and data-independent acquisition (DIA).

Methods

Healthy knee articular cartilage taken from the medial tibial condyle and medial meniscus samples taken from the body region were obtained from three adult forensic medicine cases. Proteins were extracted from tissue pieces and prepared for MS analysis. Each sample was subjected to liquid chromatography (LC)-MS/MS analysis using an Orbitrap mass spectrometer, and run in both DDA and DIA mode. Linear mixed effects models were used for statistical analysis.

Results

A total of 653 proteins were identified in the DDA analysis, of which the majority was present in both tissue types. Only proteins with quantitation information in both tissues (n = 90) were selected for more detailed analysis, of which the majority did not statistically significantly differ in abundance between the two tissue types, in either of the MS analyses. However, 21 proteins were statistically significantly different (p < 0.05) between meniscus and cartilage in the DIA analysis. Out of these, 11 proteins were also significantly different in the DDA analysis. Aggrecan core protein was the most abundant protein in articular cartilage and significantly differed between the two tissues in both methods. The corresponding protein in meniscus was serum albumin. Dermatopontin exhibited the highest meniscus vs articular cartilage ratio among the statistically significant proteins. The DIA method led to narrower confidence intervals for the abundance differences between the two tissue types than DDA.

Conclusions

Although articular cartilage and meniscus had similar proteomic composition, we detected several differences by MS. Between the two analyses, DIA yielded more precise estimates and more statistically significant different proteins than DDA, and had no missing values, which makes it preferable for future LC-MS/MS analyses.

Electronic supplementary material

The online version of this article (10.1186/s12891-018-2346-6) contains supplementary material, which is available to authorized users.

A Proteomic Approach for Understanding the Mechanisms of Delayed Corneal Wound Healing in Diabetic Keratopathy Using Diabetic Model Rat

Diabetes mellitus is a widespread metabolic disorder, and long-term hyperglycemia in diabetics leads to diabetic keratopathy. In the present study, we used a shotgun liquid chromatography/mass spectrometry-based global proteomic approach using the cornea of streptozotocin-induced diabetic (STZ) rats to examine the mechanisms of delayed corneal wound healing in diabetic keratopathy. Applying a label-free quantitation method based on spectral counting, we identified 188 proteins that showed expression changes of >2.0-fold in the cornea of STZ rats. In particular, the level of lumican expression in the cornea of STZ rats was higher than that of the normal rats. In the cornea of the normal rat, the expression level of lumican was elevated during the wound healing process, and it returned to the same expression level as before cornea injury after the wound was healed completely. On the other hand, a high expression level of lumican in the cornea of STZ rats was still maintained even after the wound was healed completely. In addition, adhesion deficiency in corneal basal cells and Bowman’s membrane was observed in the STZ rat. Thus, abnormally overexpressed lumican may lead to adhesion deficiency in the cornea of STZ rats.

Label-Free Quantitative Proteomics in a Methylmalonyl-CoA Mutase-Silenced Neuroblastoma Cell Line

Methylmalonic acidemias (MMAs) are inborn errors of metabolism due to the deficient activity of methylmalonyl-CoA mutase (MUT). MUT catalyzes the formation of succinyl-CoA from methylmalonyl-CoA, produced from propionyl-CoA catabolism and derived from odd chain fatty acids β-oxidation, cholesterol, and branched-chain amino acids degradation. Increased methylmalonyl-CoA levels allow for the presymptomatic diagnosis of the disease, even though no approved therapies exist. MMA patients show hyperammonemia, ketoacidosis, lethargy, respiratory distress, cognitive impairment, and hepatomegaly. The long-term consequences concern neurologic damage and terminal kidney failure, with little chance of survival. The cellular pathways affected by MUT deficiency were investigated using a quantitative proteomics approach on a cellular model of MUT knockdown. Currently, a consistent reduction of the MUT protein expression was obtained in the neuroblastoma cell line (SH-SY5Y) by using small-interfering RNA (siRNA) directed against an MUT transcript (MUT siRNA). The MUT absence did not affect the cell viability and apoptotic process in SH-SY5Y. In the present study, we evaluate and quantify the alterations in the protein expression profile as a consequence of MUT-silencing by a mass spectrometry-based label-free quantitative analysis, using two different quantitative strategies. Both quantitative methods allowed us to observe that the expression of the proteins involved in mitochondrial oxido-reductive homeostasis balance was affected by MUT deficiency. The alterated functional mitochondrial activity was observed in siRNA_MUT cells cultured with a propionate-supplemented medium. Finally, alterations in the levels of proteins involved in the metabolic pathways, like carbohydrate metabolism and lipid metabolism, were found.

Circulating Candidate Biomarkers in Giant Cell Tumors of Bone

PURPOSE

Approximately 5% of giant cell tumors (GCT) of bone develop pulmonary metastases. Although many biomarkers have been proposed, identification of circulating low abundance molecules may be useful to predict malignant progression.

EXPERIMENTAL DESIGN

The hydrogel nanoparticle technique followed by MS was used to detect low molecular weight serum proteins or protein fragments in serum of 20 GCT patients with different clinical course and in ten healthy sera used as control. The most representative low-abundant de novo or differentially abundant proteins were submitted to String database that recognized interconnected activated pathways including protein activation cascade, wound healing, cell-substrate adhesion, and response to stress. Statistics were performed for identification of candidate prognostic factors.

RESULTS

Proteome cluster analysis separated metastasis-free from metastatic GCT patients in two well-defined groups where serum levels of signaling transduction mediators and regulators of kinase activity presented a high discriminatory power. Increased expression of proteins STAT5B, GRB2, and OXSR1 was related to a higher probability of metastasis. Multivariate analysis demonstrated that tumor grade and STAT5B were independent prognostic factors.

CONCLUSIONS AND CLINICAL RELEVANCE

By using a noninvasive technique, we identified differentially abundant serum candidate biomarkers, also providing prognostic information in patients with GCT of bone.

Isoform-Level Interpretation of High-Throughput Proteomics Data Enabled by Deep Integration with RNA-seq

Cellular control of gene expression is a complex process that is subject to multiple levels of regulation, but ultimately it is the protein produced that determines the biosynthetic state of the cell. One way that a cell can regulate the protein output from each gene is by expressing alternate isoforms with distinct amino acid sequences. These isoforms may exhibit differences in localization and binding interactions that can have profound functional implications. High-throughput liquid chromatography tandem mass spectrometry proteomics (LC-MS/MS) relies on enzymatic digestion and has lower coverage and sensitivity than transcriptomic profiling methods such as RNA-seq. Digestion results in predictable fragmentation of a protein, which can limit the generation of peptides capable of distinguishing between isoforms. Here we exploit transcript-level expression from RNA-seq to set prior likelihoods and enable protein isoform abundances to be directly estimated from LC-MS/MS, an approach derived from the principle that most genes appear to be expressed as a single dominant isoform in a given cell type or tissue. Through this deep integration of RNA-seq and LC-MS/MS data from the same sample, we show that a principal isoform can be identified in >80% of gene products in homogeneous HEK293 cell culture and >70% of proteins detected in complex human brain tissue. We demonstrate that the incorporation of translatome data from ribosome profiling further refines this process. Defining isoforms in experiments with matched RNA-seq/translatome and proteomic data increases the functional relevance of such data sets and will further broaden our understanding of multilevel control of gene expression.

Identification and Quantification of Murine Mitochondrial Proteoforms Using an Integrated Top-Down and Intact-Mass Strategy

The development of effective strategies for the comprehensive identification and quantification of proteoforms in complex systems is a critical challenge in proteomics. Proteoforms, the specific molecular forms in which proteins are present in biological systems, are the key effectors of biological function. Thus, knowledge of proteoform identities and abundances is essential to unraveling the mechanisms that underlie protein function. We recently reported a strategy that integrates conventional top-down mass spectrometry with intact-mass determinations for enhanced proteoform identifications and the elucidation of proteoform families and applied it to the analysis of yeast cell lysate. In the present work, we extend this strategy to enable quantification of proteoforms, and we examine changes in the abundance of murine mitochondrial proteoforms upon differentiation of mouse myoblasts to myotubes. The integrated top-down and intact-mass strategy provided an increase of ∼37% in the number of identified proteoforms compared to top-down alone, which is in agreement with our previous work in yeast; 1779 unique proteoforms were identified using the integrated strategy compared to 1301 using top-down analysis alone. Quantitative comparison of proteoform differences between the myoblast and myotube cell types showed 129 observed proteoforms exhibiting statistically significant abundance changes (fold change >2 and false discovery rate <5%).

A Novel Class of ER Membrane Proteins Regulates ER-Associated Endosome Fission

Endoplasmic reticulum (ER) membrane contact sites (MCSs) mark positions where endosomes undergo fission for cargo sorting. To define the role of ER at this unique MCS, we targeted a promiscuous biotin ligase to cargo-sorting domains on endosome buds. This strategy identified the ER membrane protein TMCC1, a member of a conserved protein family. TMCC1 concentrates at the ER-endosome MCSs that are spatially and temporally linked to endosome fission. When TMCC1 is depleted, endosome morphology is normal, buds still form, but ER-associated bud fission and subsequent cargo sorting to the Golgi are impaired. We find that the endosome-localized actin regulator Coronin 1C is required for ER-associated fission of actin-dependent cargo-sorting domains. Coronin 1C is recruited to endosome buds independently of TMCC1, while TMCC1/ER recruitment requires Coronin 1C. This link between TMCC1 and Coronin 1C suggests that the timing of TMCC1-dependent ER recruitment is tightly regulated to occur after cargo has been properly sequestered into the bud.

All Cats are Gray in the Dark: Enrichment/Depletion Approaches for Biomarker Discovery on Felis catus Plasma

In veterinary medicine, assay performance is often affected by the lack of species-specific diagnostic tools. Reliable biomarkers might be identified by investigating biological fluids of the species of interest, but protein sequence databases are often incomplete and human-specific devices for reducing sample complexity might fail when applied to animal plasma. Here, seven commercial methods based on different capturing agents (anti-human antibodies, affinity ligands, mixture of antibodies and ligands, and combinatorial peptide ligand libraries) are applied to cat plasma and evaluated in terms of yield, identified proteins/ peptides, and relative abundance by high-resolution shotgun proteomics and label-free quantitation. As a result, anti-human antibody-based methods are unsatisfactory. Most fail in reducing albumin and immunoglobulins, and some lead to a substantial removal of other highly abundant proteins, probably because of nonspecific interactions. A protein A/dye ligand-based method is efficient in reducing immunoglobulins, fibrinogen, and apolipoprotein A1 and A2, but not albumin, and protein identifications do not increase. Only peptide ligand libraries flatten the dynamic range, and increased protein identification (59.0%). Albumin and immunoglobulins are successfully depleted (60.7% and 35.9%, respectively). Although further studies will be required for reinforcing our observations, this work can provide a useful guide for cat plasma pretreatment in biomarker discovery studies.

The Starch Utilization System Assembles around Stationary Starch-Binding Proteins

Bacteroides thetaiotaomicron (Bt) is a prominent member of the human gut microbiota with an extensive capacity for glycan harvest. This bacterium expresses a five-protein complex in the outer membrane, called the starch utilization system (Sus), which binds, degrades, and imports starch into the cell. Sus is a model system for the many glycan-targeting polysaccharide utilization loci found in Bt and other members of the Bacteroidetes phylum. Our previous work has shown that SusG, a lipidated amylase in the outer membrane, explores the entire cell surface but diffuses more slowly as it interacts with starch. Here, we use a combination of single-molecule tracking, super-resolution imaging, reverse genetics, and proteomics to show that SusE and SusF, two proteins that bind starch, are immobile on the cell surface even when other members of the system are knocked out and under multiple different growth conditions. This observation suggests a new paradigm for protein complex formation: binding proteins form immobile complexes that transiently associate with a mobile enzyme partner.

A human proteomic dataset from untreated and depleted/enriched serum samples

We present a proteomic dataset generated from a human serum sample and the enriched/depleted fractions obtained by seven commercial products. This report is related to the research article entitled "Comparative evaluation of seven commercial products for human serum enrichment/depletion by shotgun proteomics" [1]. All samples were analyzed by LC-MS/MS, label free quantitation using the spectral counting approach, and Gene Ontology (GO) annotation. Protein relative abundances and functions were reported.

SDS-PAGE fractionation to increase metaproteomic insight into the taxonomic and functional composition of microbial communities for biogas plant samples

Metaproteomics represent an important tool for the taxonomic and functional investigation of microbial communities in humans, environment, and technical applications. Due to the high complexity of the microbial communities, protein, and peptide fractionation is applied to improve the characterization of taxonomic and functional composition of microbial communities. In order to target scientific questions regarding taxonomic and functional composition adequately, a tradeoff between the number of fractions analyzed and the required depth of information has to be found. Two samples of a biogas plant were analyzed by either single LC-MS/MS measurement (1D) or LC-MS/MS measurements of fractions obtained after SDS-PAGE (2D) separation. Fractionation with SDS-PAGE increased the number of identified spectra by 273%, the number of peptides by 95%, and the number of metaproteins by 59%. Rarefaction plots of species and metaproteins against identified spectra showed that 2D separation was sufficient to identify most microbial families but not all metaproteins. More reliable quantitative comparison could be achieved with 2D. 1D separation enabled high-throughput analysis of samples, however, depth in functional descriptions and reliability of quantification were lost. Nevertheless, the proteotyping of multiple samples was still possible. 2D separations provided more reliable quantitative data combined with a deeper insight into the taxonomic and functional composition of the microbial communities. Regarding taxonomic and functional composition, metaproteomics based on 2D is just the tip of an iceberg.

Differential Proteomic Analysis between Small Cell Lung Carcinoma (SCLC) and Pulmonary Carcinoid Tumors Reveals Molecular Signatures for Malignancy in Lung Cancer

PURPOSE

The molecular underpinnings that may prognosticate survival and increase our understanding of tumor development and progression are still poorly understood. This study aimed to define the molecular signatures for malignancy in small cell lung carcinoma (SCLC), which is known for its highly aggressive clinical features and poor prognosis.

EXPERIMENTAL DESIGN

Using clinical specimens, the authors perform a comparative proteomic analysis of high-grade SCLCs and low-grade pulmonary carcinoid tumors (PCTs), both of which are types of neuroendocrine tumors. A label-free LC-MS-based quantitative proteomic analysis is applied to tumor cells laser-microdissected from their formalin-fixed paraffin-embedded (FFPE) tissues obtained from six patients each.

RESULTS

Overall, 1991 proteins are identified from tumor cells in the FFPE tissues. Through the protein-protein interaction network analysis of 201 proteins significantly, the authors find that SCLC is functionally characterized by activation of molecular pathways for spliceosome, RNA transport, and DNA replication and cell cycle. Particularly, 11 proteins involved in tumor proliferation (MCM2, 4, 6, 7, and MSH2), metastasis (RCC2, CORO1C, CHD4, and IPO9), and cancer metabolism (PHGDH and TYMP) are identified as SCLC-specific proteins. Furthermore, their prognostic significances are demonstrated by online Kaplan-Meier survival analysis.

CONCLUSIONS AND CLINICAL RELEVANCE

These clinical tissue proteomic approach for SCLC reveals the proteins associated with aggressiveness and poor prognosis. The identified SCLC-specific proteins represent potential therapeutic targets. Moreover, MCMs and PHGDH can be poor prognostic factors for lung cancer.

Supraphysiological Levels of Oxygen Exposure During the Neonatal Period Impairs Signaling Pathways Required for Learning and Memory

Preterm infants often require prolonged oxygen supplementation and are at high risk of neurodevelopmental impairment. We recently reported that adult mice exposed to neonatal hyperoxia (postnatal day [P] 2 to 14) had spatial navigation memory deficits associated with hippocampal shrinkage. The mechanisms by which early oxidative stress impair neurodevelopment are not known. Our objective was to identify early hyperoxia-induced alterations in hippocampal receptors and signaling pathways necessary for memory formation. We evaluated C57BL/6 mouse pups at P14, exposed to either 85% oxygen or air from P2 to 14. We performed targeted analysis of hippocampal ligand-gated ion channels and proteins necessary for memory formation, and global bioinformatic analysis of differentially expressed hippocampal genes and proteins. Hyperoxia decreased hippocampal mGLU7, TrkB, AKT, ERK2, mTORC1, RPS6, and EIF4E and increased α3, α5, and ɤ2 subunits of GABA_A receptor and PTEN proteins, although changes in gene expression were not always concordant. Bioinformatic analysis indicated dysfunction in mitochondria and global protein synthesis and translational processes. In conclusion, supraphysiological oxygen exposure reduced proteins necessary for hippocampus-dependent memory formation and may adversely impact hippocampal mitochondrial function and global protein synthesis. These early hippocampal changes may account for memory deficits seen in preterm survivors following prolonged oxygen supplementation.

Relative and Absolute Quantitation in Mass Spectrometry-Based Proteomics

Mass spectrometry-based quantitative proteomics is a powerful tool for gaining insights into function and dynamics of biological systems. However, peptides with different sequences have different ionization efficiencies, and their intensities in a mass spectrum are not correlated with their abundances. Therefore, various label-free or stable isotope label-based quantitation methods have emerged to assist mass spectrometry to perform comparative proteomic experiments, thus enabling nonbiased identification of thousands of proteins differentially expressed in healthy versus diseased cells. Here, we discuss the most widely used label-free and metabolic-, enzymatic-, and chemical labeling-based proteomic strategies for relative and absolute quantitation. We summarize the specific strengths and weaknesses of each technique in terms of quantification accuracy, proteome coverage, multiplexing capability, and robustness. Applications of each strategy for solving specific biological complexities are also presented.

Proteomic Analysis of Exosomes and Its Application in HIV-1 Infection

Exosomes are 30-100 nm extracellular vesicles secreted from late endosomes by various types of cells. Numerous studies have suggested that exosomes play significant roles in human immunodeficiency virus 1 (HIV-1) biogenesis. Proteomics coupled with exosome fractionation has been successfully used to identify various exosomal proteins and helped to uncover the interactions between exosomes and HIV-1. To inform the current progress in the intersection of exosome, proteomics, and HIV-1, this review is focused on: i) analyzing different exosome isolation, purification methods, and their implications in HIV-1 studies; ii) evaluating the roles of various proteomic techniques in defining exosomal contents; iii) discussing the research and clinical applications of proteomics and exosome in HIV-1 biology.

Comparative Proteomic Study of the Antiproliferative Activity of Frog Host-Defence Peptide Caerin 1.9 and Its Additive Effect with Caerin 1.1 on TC-1 Cells Transformed with HPV16 E6 and E7

Caerin is a family of peptides isolated from the glandular secretion of Australian tree frogs, the genus Litoria, and has been previously shown to have anticancer activity against several cancer cells. In this work, we used two host-defence peptides, caerin 1.1 and caerin 1.9, to investigate their ability to inhibit a murine derived TC-1 cell transformed with human papillomavirus 16 E6 and E7 growth in vitro. Caerin 1.9 inhibits TC-1 cell proliferation, although inhibition is more pronounced when applied in conjunction with caerin 1.1. To gain further insights into the antiproliferative mechanisms of caerin 1.9 and its additive effect with caerin 1.1, we used a proteomics strategy to quantitatively examine (i) the changes in the protein profiles of TC-1 cells and (ii) the excretory-secretory products of TC-1 cells following caerin peptides treatment. Caerin 1.9 treatment significantly altered the abundance of several immune-related proteins and related pathways, such as the Tec kinase and ILK signalling pathways, as well as the levels of proinflammatory cytokines and chemokines. In conclusion, caerin peptides inhibit TC-1 cell proliferation, associated with modification in signalling pathways that would change the tumour microenvironment which is normally immune suppressive.

A novel liver metastasis-correlated protein of pancreatic neuroendocrine neoplasm (PanNEN) discovered by proteomic analysis

The aim of this study was to identify novel liver metastasis-correlated proteins of PanNEN by proteomics to compare pancreatic tumor (PT) with paired metastatic liver tumor (LT). Of 118 surgical cases with PanNEN, 7 cases with formalin-fixed paraffin-embedded (FFPE) tissues of both PT and paired LT were evaluated by proteomics. Tumor cells were selectively collected from FFPE tissues by laser capture microdissection. A total of 3,722 proteins were detected from extracted peptides by mass spectrometry-based shotgun analysis. Selection of the candidate proteins expressed differently between PT and LT were performed by semi-quantitative comparison in silico and confirmation with immunohistochemistry. We focused on ANXA6, CNPY2, RAB11B and TUBB3, all of which had higher expressions in LT. In all surgical cases with FFPE samples, liver recurrence-free survival (RFS) was evaluated in correlation to the expression of the candidate proteins in PT by immunohistochemistry. Liver RFS was significantly poorer in CNPY2 positive patients than in negative patients (10-year liver RFS; 39.8% vs. 92.3%, p = 0.012). Also, liver RFS tended to be poorer in ANXA6 positive patients than in those who were negative (10-year liver RFS; 51.4% vs. 95.0%, p = 0.099). In the multivariate analysis, the independent predictors of liver RFS were CNPY2 positivity (HR: 6.19, 95 % CI: 1.47-42.79, p = 0.011) and tumor size ≥ 42 mm (HR: 4.63, 95 % CI: 1.03-23.23, p = 0.045). In conclusion, CNPY2 is a novel liver metastasis-correlated protein of PanNEN.

Toxin-resolved antivenomics-guided assessment of the immunorecognition landscape of antivenoms

Snakebite envenoming represents a major issue in rural areas of tropical and subtropical regions across sub-Saharan Africa, South to Southeast Asia, Latin America and Oceania. Antivenoms constitute the only scientifically validated therapy for snakebite envenomings, provided they are safe, effective, affordable, accessible and administered appropriately. However, the lack of financial incentives in a technology that has remained relatively unchanged for more than a century, has contributed to some manufacturers leaving the market and others downscaling production or increasing the prices, leading to a decline in the availability and accessibility for these life-saving antidotes to millions of rural poor most at risk from snakebites in low income countries. The shortage of antivenoms can be significantly alleviated by optimizing the use of current antivenoms (through the assessment of their specific and paraspecific efficacy against the different medically relevant homologous and heterologous snake venoms) and by generating novel polyspecific antivenoms exhibiting broad clinical spectrum and wide geographic distribution range. Research on venoms has been continuously enhanced by advances in technology. Particularly, the last decade has witnessed the development of omics strategies for unravelling the toxin composition of venoms ("venomics") and to assess the immunorecognition profile of antivenoms ("antivenomics"). Here, we review recent developments and reflect on near future innovations that promise to revolutionize the mutually enlightening relationship between evolutionary and translational venomics.