The banded krait, Bungarus fasciatus is a medically important venomous snake in Asia. The wide distribution of this species in Southeast Asia and southern China indicates potential geographical variation of the venom which may impact the clinical management of snakebite envenomation. This study investigated the intraspecific venom variation of B. fasciatus from five geographical locales through a venom decomplexing proteomic approach, followed by toxinological and immunological studies. The venom proteomes composed of a total of 9 toxin families, comprising 22 to 31 proteoforms at varying abundances. The predominant proteins were phospholipase A2 (including beta-bungarotoxin), Kunitz-type serine protease inhibitor (KSPI) and three-finger toxins (3FTx), which are toxins that cause neurotoxicity and lethality. The venom lethality varied with geographical origins of the snake, with intravenous median lethal doses (LD50) ranging from 0.45-2.55 µg/g in mice. The Thai Bungarus fasciatus monovalent antivenom (BFMAV) demonstrated a dose-dependent increasing immunological binding activity toward all venoms; however, its in vivo neutralization efficacy varied vastly with normalized potency values ranging from 3 to 28 mg/g, presumably due to the compositional differences of dominant proteins in the different venoms. The findings support that antivenom use should be optimized in different geographical areas. The development of a pan-regional antivenom may be a more sustainable solution for the treatment of snakebite envenomation.
The life span of cancer patients can be prolonged with appropriate therapies if detected early. Mass screening for early detection of cancer, however, requires sensitive and specific biomarkers obtainable from body fluids such as blood or urine. To date, most biomarker discovery programs focus on the proteome rather than the endogenous peptidome. It has been long-established that tumor cells and stromal cells produce tumor resident proteases (TRPs) to remodel the surrounding tumor microenvironment in support of tumor progression. In fact, proteolytic products of TRPs have been shown to correlate with malignant behavior. Being of low molecular weight, these unique peptides can pass through the endothelial barrier of the vasculature into the bloodstream. As such, the cancer peptidome has increasingly become a focus for biomarker discovery. In this review, we discuss on the various aspects of the peptidome in cancer biomarker research.
Limitation on two dimensional (2D) gel electrophoresis technique causes some proteins to be under presented, especially the extreme acidic, basic, or membrane proteins. To overcome the limitation of 2D electrophoresis, an analysis method was developed for identification of differentially expressed proteins in normal and cancerous colonic tissues using self-pack hydroxyapatite (HA) column. Normal and cancerous colon tissues were homogenized and proteins were extracted using sodium phosphate buffer at pH 6.8. Protein concentration was determined and the proteins were loaded unto the HA column. HA column reduced the complexity of proteins mixture by fractionating the proteins according to their ionic strength. Further protein separation was accomplished by a simple and cost effective sodium dodecyl sulfate-polyacrylamide gel electrophoresis method. The protein bands were subjected to in-gel digestion and protein analysis was performed using electrospray ionization (ESI) ion trap mass spectrometer. There were 17 upregulated proteins and seven downregulated proteins detected with significant differential expression. Some of these proteins were low abundant proteins or proteins with extreme pH that were usually under presented in 2D gel analysis. We have identified brain mitochondrial carrier protein 1, T-cell surface glycoprotein CD1a, SOSS complex subunit B2, and Protein Jade 1 which were previously not detected in 2D gel analysis method.
Renal calculi disease or known as kidney stone disease is the most common urological disorder in both men and women, although it is more prevalent in men. The lifetime chance for an individual to develop renal calculi is approximately 10% whereas the risk of recurrence in a 10-year period is 74%. Therefore, a diagnostic tool for screening or detecting renal calculi is greatly needed. In this study, we analyze urinary protein profiles from patients with renal calculi for the first time (RC), healthy subjects (HS), and patients with recurrent renal calculi (RRC) to identify a biomarker for detecting the disease. Urinary proteins were isolated by salt precipitation and the proteins resolved by SDS-PAGE. Target proteins were analyzed with LC/MS/MS. Thirty-two proteins were identified from healthy subjects and patients. Uromodulin was the most abundant urinary protein in HS but was a very faint band if detected at all from those that formed renal calculi for the first time (p < 0.05). Yet the excreted levels of urinary uromodulin in RRC were similar to those of the HS suggesting that uromodulin is a reliable biomarker for only RC. In addition, a few immunoglobulins that were commonly found in the urine of both RC and RRC, which include Ig alpha heavy chain 1, Ig gamma-2 c region, Ig gamma-3 heavy chain disease protein, Ig heavy chain variable region, Ig heavy constant region gamma 4, and Ig heavy chain. Ig heavy chain Fab frag and antibody a5b7 chain B may serve as potential biomarkers for renal calculi disease.
The natural rubber latex extracted from the bark of Hevea brasiliensis plays various important roles in modern society. Post-translational modifications (PTMs) of the latex proteins are important for the stability and functionality of the proteins. In this study, latex proteins were acquired from the C-serum, lutoids, and rubber particle layers of latex without using prior enrichment steps; they were fragmented using collision-induced dissociation (CID), higher-energy collisional dissociation (HCD), and electron-transfer dissociation (ETD) activation methods. PEAKS 7 were used to search for unspecified PTMs, followed by analysis through PTM prediction tools to crosscheck both results. There were 73 peptides in 47 proteins from H. brasiliensis protein sequences derived from UniProtKB were identified and predicted to be post-translationally modified. The peptides with PTMs identified include phosphorylation, lysine acetylation, N-terminal acetylation, hydroxylation, and ubiquitination. Most of the PTMs discovered have yet to be reported in UniProt, which would provide great assistance in the research of the functional properties of H. brasiliensis latex proteins, as well as being useful biomarkers. The data are available via the MassIVE repository with identifier MSV000082419.
The natural rubber latex extracted from the bark of Hevea brasiliensis plays various important roles in today's modern society. Following ultracentrifugation, the latex can be separated into 3 layers: C-serum, lutoids, and rubber particles. Previous studies have shown that a large number of proteins are present in these 3 layers. However, a complete proteome for this important plant is still unavailable. Protein sequences have been recently translated from the completed draft genome database of H. brasiliensis, leading to the creation of annotated protein databases of the following H. brasiliensis biosynthetic pathways: photosynthesis, latex allergens, rubberwood formation, latex biosynthesis, and disease resistance. This research was conducted to identify the proteins contained within the latex by way of de novo sequencing from mass spectral data obtained from the 3 layers of the latex. Peptides from these proteins were fragmented using collision-induced dissociation, higher-energy collisional dissociation, and electron-transfer dissociation activation methods. A large percentage of proteins from the biosynthetic pathways (63% to 100%) were successfully identified. In addition, a total of 1839 unique proteins were identified from the whole translated draft genome database (AnnHBM).
Researchers frequently use two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) prior to mass spectrometric analysis in a proteomics approach. The i2D-PAGE method, which 'inverts' the dimension of protein separation of the conventional 2D-PAGE, is presented in this publication. Protein lysate of Channa striata, a freshwater snakehead fish, was separated based on its molecular weight in the first dimension and its isoelectric point in the second dimension. The first-dimension separation was conducted on a gel-free separation device, and the protein mixture was fractionated into 12 fractions in chronological order of increasing molecular weight. The second-dimension separation featured isoelectric focusing, which further separated the proteins within the same fraction according to their respective isoelectric point. Advantages of i2D-PAGE include better visualisation of the isolated protein, easy identification on protein isoforms, shorter running time, customisability and reproducibility. Erythropoietin standard was applied to i2D-PAGE to show its effectiveness for separating protein isoforms. Various staining methods such as Coomassie blue staining and silver staining are also applicable to i2D-PAGE. Overall, the i2D-PAGE separation method effectively separates protein lysate and is suitable for application in proteomics research.
Chalcones and their derivatives belong to the flavonoid family. They have been extensively studied for their anticancer properties and some have been approved for clinical use. In this study, the in vivo anti-tumor activity of flavokawain C (FKC), a naturally occurring chalcone found in Kava (Piper methysticum Forst) was evaluated in HCT 116 cells (colon carcinoma). We also attempted to identify potential biomarkers and/or molecular targets in serum with applicability in predicting treatment outcome. The anti-tumor effects and toxicity of FKC were assessed using the xenograft nude mice model. Cisplatin was used as positive control. The anti-proliferative and apoptotic activities were then evaluated in tumor tissues treated with FKC. Furthermore, two-dimensional electrophoresis (2-DE) followed by protein identification using MALDI-TOF/TOF-MS/MS was performed to compare the serum proteome profiles between healthy nude mice and nude mice bearing HCT 116 tumor treated with vehicle solution and FKC, respectively. Our results showed that FKC treatment significantly inhibited HCT 116 tumor growth. In vivo toxicity studies showed that administration of FKC did not cause damage to major organs and had no significant effect on body weight. FKC was found to induce apoptosis in tumor, and this was associated with increased expression of cleaved caspase-3 and decreased expression of Ki67 in tumor tissues. Our proteomic analysis identified five proteins that changed in abundance - Ig mu chain C region (secreted form), GRP78, hemopexin, kininogen-1 and apolipoprotein E. Overall, our findings demonstrated the potential of FKC as an anti-cancer agent for the treatment of colon carcinoma.
Proteomic analysis of plants relies on high yields of pure protein. In plants, protein extraction and purification present a great challenge due to accumulation of a large amount of interfering substances, including polysaccharides, polyphenols, and secondary metabolites. Therefore, it is necessary to modify the extraction protocols. A study was conducted to compare four protein extraction and precipitation methods for proteomic analysis. The results showed significant differences in protein content among the four methods. The chloroform-trichloroacetic acid-acetone method using 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) buffer provided the best results in terms of protein content, pellets, spot resolution, and intensity of unique spots detected. An overall of 83 qualitative or quantitative significant differential spots were found among the four methods. Based on the 2-DE gel map, the method is expected to benefit the development of high-level proteomic and biochemical studies of Andrographis paniculata, which may also be applied to other recalcitrant medicinal plant tissues.
A proteome is defined as a comprehensive protein set either of an organ or an organism at a given time and under specific physiological conditions. Accordingly, the study of the nervous system's proteomes is called neuroproteomics. In the neuroproteomics process, various pieces of the nervous system are "fragmented" to understand the dynamics of each given sub-proteome in a much better way. Functional proteomics addresses the organisation of proteins into complexes and the formation of organelles from these multiprotein complexes that control various physiological processes. Current functional studies of neuroproteomics mainly talk about the synapse structure and its organisation, the major building site of the neuronal communication channel. The proteomes of synaptic vesicle, presynaptic terminal, and postsynaptic density, have been examined by various proteomics techniques. The objectives of functional neuroproteomics are: to solve the proteome of single neurons or astrocytes grown in cell cultures or from the primary brain cells isolated from tissues under various conditions, to identify the set of proteins that characterize specific pathogenesis, or to determine the group of proteins making up postsynaptic or presynaptic densities. It is usual to solve a particular sub-proteome like the heat-shock response proteome or the proteome responding to inflammation. Post-translational protein modifications alter their functions and interactions. The techniques to detect synapse phosphoproteome are available. However, techniques for the analysis of ubiquitination and sumoylation are under development.
The hypoxia-inducible factors (HIFs) are key transcription factors in determining cellular responses involving alterations in protein levels in response to limited oxygen availability in animal cells. 2-Oxoglutarate-dependent oxygenases play key roles in regulating levels of HIF and its transcriptional activity. We describe MS-based proteomics studies in which we compared the results of subjecting human breast cancer MCF-7 cells to hypoxia or treating them with a cell-penetrating derivative (dimethyl N-oxalylglycine; DMOG) of the stable 2OG analogue N-oxalylglycine. The proteomic results are consistent with reported transcriptomic analyses and support the proposed key roles of 2OG-dependent HIF prolyl- and asparaginyl-hydroxylases in the hypoxic response. Differences between the data sets for hypoxia and DMOG might reflect context-dependent effects or HIF-independent effects of DMOG.
One of the best-established area within multi-omics is proteogenomics, whereby the underpinning technologies are next-generation sequencing (NGS) and mass spectrometry (MS). Proteogenomics has contributed significantly to genome (re)-annotation, whereby novel coding sequences (CDS) are identified and confirmed. By incorporating in-silico translated genome variants in protein database, single amino acid variants (SAAV) and splice proteoforms can be identified and quantified at peptide level. The application of proteogenomics in cancer research potentially enables the identification of patient-specific proteoforms, as well as the association of the efficacy or resistance of cancer therapy to different mutations. Here, we discuss how NGS/TGS data are analyzed and incorporated into the proteogenomic framework. These sequence data mainly originate from whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-Seq. We explain two major strategies for sequence analysis i.e., de novo assembly and reads mapping, followed by construction of customized protein databases using such data. Besides, we also elaborate on the procedures of spectrum to peptide sequence matching in proteogenomics, and the relationship between database size on the false discovery rate (FDR). Finally, we discuss the latest development in proteogenomics-assisted precision oncology and also challenges and opportunities in proteogenomics research.
Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. CRC liver metastases (CRLM) are often resistant to conventional treatments, with high rates of recurrence. Therefore, it is crucial to identify biomarkers for CRLM patients that predict cancer progression. This study utilised matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially map the CRLM tumour proteome. CRLM tissue microarrays (TMAs) of 84 patients were analysed using tryptic peptide MALDI-MSI to spatially monitor peptide abundances across CRLM tissues. Abundance of peptides was compared between tumour vs stroma, male vs female and across three groups of patients based on overall survival (0-3 years, 4-6 years, and 7+ years). Peptides were then characterised and matched using LC-MS/MS. A total of 471 potential peptides were identified by MALDI-MSI. Our results show that two unidentified m/z values (1589.876 and 1092.727) had significantly higher intensities in tumours compared to stroma. Ten m/z values were identified to have correlation with biological sex. Survival analysis identified three peptides (Histone H4, Haemoglobin subunit alpha, and Inosine-5'-monophosphate dehydrogenase 2) and two unidentified m/z values (1305.840 and 1661.060) that were significantly higher in patients with shorter survival (0-3 years relative to 4-6 years and 7+ years). This is the first study using MALDI-MSI, combined with LC-MS/MS, on a large cohort of CRLM patients to identify the spatial proteome in this malignancy. Further, we identify several protein candidates that may be suitable for drug targeting or for future prognostic biomarker development.
Remote protein homology detection and fold recognition refer to detection of structural homology in proteins where there are small or no similarities in the sequence. To detect protein structural classes from protein primary sequence information, homology-based methods have been developed, which can be divided to three types: discriminative classifiers, generative models for protein families and pairwise sequence comparisons. Support Vector Machines (SVM) and Neural Networks (NN) are two popular discriminative methods. Recent studies have shown that SVM has fast speed during training, more accurate and efficient compared to NN. We present a comprehensive method based on two-layer classifiers. The 1st layer is used to detect up to superfamily and family in SCOP hierarchy using optimized binary SVM classification rules. It used the kernel function known as the Bio-kernel, which incorporates the biological information in the classification process. The 2nd layer uses discriminative SVM algorithm with string kernel that will detect up to protein fold level in SCOP hierarchy. The results obtained were evaluated using mean ROC and mean MRFP and the significance of the result produced with pairwise t-test was tested. Experimental results show that our approaches significantly improve the performance of remote protein homology detection and fold recognition for all three different version SCOP datasets (1.53, 1.67 and 1.73). We achieved 4.19% improvements in term of mean ROC in SCOP 1.53, 4.75% in SCOP 1.67 and 4.03% in SCOP 1.73 datasets when compared to the result produced by well-known methods. The combination of first layer and second layer of BioSVM-2L performs well in remote homology detection and fold recognition even in three different versions of datasets.
Confirmation of oral squamous cell cancer (OSCC) currently relies on histological analysis, which does not provide clear indication of cancer development from precancerous lesions. In the present study, whole saliva proteins of patients with OSCC (n = 12) and healthy subjects (n = 12) were separated by 2DE to identify potential candidate biomarkers that are much needed to improve detection of the cancer. The OSCC patients' 2DE saliva protein profiles appeared unique and different from those obtained from the healthy subjects. The patients' saliva α1-antitrypsin (AAT) and haptoglobin (HAP) β chains were resolved into polypeptide spots with increased microheterogeneity, although these were not apparent in their sera. Their 2DE protein profiles also showed presence of hemopexin and α-1B glycoprotein, which were not detected in the profiles of the control saliva. When subjected to densitometry analysis, significant altered levels of AAT, complement C3, transferrin, transthyretin, and β chains of fibrinogen and HAP were detected. The increased levels of saliva AAT, HAP, complement C3, hemopexin, and transthyretin in the OSCC patients were validated by ELISA. The strong association of AAT and HAP with OSCC was further supported by immunohistochemical staining of cancer tissues. The differently expressed saliva proteins may be useful complementary biomarkers for the early detection and/or monitoring of OSCC, although this requires validation in clinically representative populations.
Diagnosis of prostate cancer (PCa) is currently much reliant on the invasive and time-consuming transrectal ultrasound-guided biopsy of the prostate gland, particularly in light of the inefficient use of prostate-specific antigen as its biomarker. In the present study, we have profiled the sera of patients with PCa and benign prostatic hyperplasia (BPH) using the gel- and lectin-based proteomics methods and demonstrated the significant differential expression of apolipoprotein AII, complement C3 beta chain fragment, inter-alpha-trypsin inhibitor heavy chain 4 fragment, transthyretin, alpha-1-antitrypsin, and high molecular weight kininogen (light chain) between the two groups of patients' samples. Our data are suggestive of the potential use of the serum proteins as complementary biomarkers to effectively discriminate PCa from BPH, although this requires further extensive validation on clinically representative populations.
Mushrooms are considered an important food for their traditionally famous nutritional and medicinal values, although much information about their potential at the molecular level is unfortunately unknown. Edible mushrooms include fungi that are either collected wild or cultivated. Many important species are difficult to cultivate but attempts have been made with varying degrees of success, with the results showing unsatisfactory economical cultivation methods. Recently, proteomic analysis has been developed as a powerful tool to study the protein content of fungi, particularly basidiomycetes. This mini-review article highlights the contribution of proteomics platforms to the study of edible mushrooms, focusing on the molecular mechanisms involved in developmental stages. This includes extracellular and cytoplasmic effector proteins that have potential or are involved in the synthesis of anticancer, antidiabetic, antioxidant, and antibiotic, in blood pressure control, in the supply of vitamins and minerals, and in other responses to environmental changes. The contribution of different proteomics techniques including classical and more advanced techniques is also highlighted.
Effective protein extraction is essential especially in producing a well-resolved proteome on 2D gels. A well-resolved placental cotyledon proteome, with good reproducibility, have allowed researchers to study the proteins underlying the physiology and pathophysiology of pregnancy. The aim of this study is to determine the best protein extraction protocol for the extraction of protein from placental cotyledons tissues for a two-dimensional gel electrophoresis (2D-GE). Based on widely used protein extraction strategies, 12 different extraction methodologies were carefully selected, which included one chemical extraction, two mechanical extraction coupled protein precipitations, and nine chemical extraction coupled protein precipitations. Extracted proteins were resolved in a one-dimensional gel electrophoresis and 2D-GE; then, it was compared with set criteria: extraction efficacy, protein resolution, reproducibility, and recovery efficiency. Our results revealed that a better profile was obtained by chemical extraction in comparison to mechanical extraction. We further compared chemical extraction coupled protein precipitation methodologies, where the DNase/lithium chloride-dense sucrose homogenization coupled dichloromethane-methanol precipitation (DNase/LiCl-DSH-D/MPE) method showed good protein extraction efficiency. This, however, was carried out with the best protein resolution and proteome reproducibility on 2D-gels. DNase/LiCl-DSH-D/MPE was efficient in the extraction of proteins from placental cotyledons tissues. In addition, this methodology could hypothetically allow the protein extraction of any tissue that contains highly abundant lipid and glycogen.
Wax apple is one of the underutilized fruits that is considered a good source of fibers, vitamins, minerals as well as antioxidants. In this study, a comparative analysis of the developments of wax fruit ripening at the proteomic and metabolomic level was reported. 2D electrophoresis coupled with MALDI-TOF/TOF was used to compare the proteome profile from three developmental stages named immature, young, and mature fruits. In general, the protein expression profile and the identified proteins function were discussed for their potential roles in fruit physiological development and ripening processes. The metabolomic investigation was also performed on the same samples using quadrupole LC-MS (LC-QTOF/MS). Roles of some of the differentially expressed proteins and metabolites are discussed in relation to wax apple ripening during the development. This is the first study investigating the changes in the proteins and metabolites in wax apple at different developmental stages. The information obtained from this research will be helpful in developing biomarkers for breeders and help the plant researchers to avoid wax apple cultivation problems such as fruit cracking.
Palm oil is an edible vegetable oil derived from lipid-rich fleshy mesocarp tissue of oil palm (Elaeis guineensis Jacq.) fruit and is of global economic and nutritional relevance. While the understanding of oil biosynthesis in plants is improving, the fundamentals of oil biosynthesis in oil palm still require further investigations. To gain insight into the systemic mechanisms that govern oil synthesis during oil palm fruit ripening, the proteomics approach combining gel-based electrophoresis and mass spectrometry was used to profile protein changes and classify the patterns of protein accumulation during these complex physiological processes. Protein profiles from different stages of fruit ripening at 10, 12, 14, 15, 16, 18 and 20 weeks after anthesis (WAA) were analysed by two-dimensional gel electrophoresis (2DE). The proteome data were then visualised using a multivariate statistical analysis of principal component analysis (PCA) to get an overview of the proteome changes during the development of oil palm mesocarp. A total of 68 differentially expressed protein spots were successfully identified by matrix-assisted laser desorption/ionisation-time of flight (MALDI-TOF/TOF) and functionally classified using ontology analysis. Proteins related to lipid production, energy, secondary metabolites and amino acid metabolism are the most significantly changed proteins during fruit development representing potential candidates for oil yield improvement endeavors. Data are available via ProteomeXchange with identifier PXD009579. This study provides important proteome information for protein regulation during oil palm fruit ripening and oil synthesis.