Advances in proteomic technologies

Biomarker analysis from complex biofluids by an on-chip chemically modified light-controlled vertical nanopillar array device

Nanostructured devices have proven useful in a broad range of applications, from diagnosing diseases to discovering and screening new drug molecules. We developed vertical silicon nanopillar (SiNP) arrays for on-chip multiplex capture of selected biomolecules using a light-induced release of the array's selectively captured biomarkers. This platform allows the rapid, reusable and quantitative capture and release of a selection of biomarkers, followed by their downstream analysis. Here we outline a standardized protocol for producing the SiNP-based capture-and-release device, which involves the detailed fabrication steps for single-zone nanopillar arrays, their morphological characterization and the chemical modification procedures applied for the anchoring of selective bioreceptors together with the light-controlled on-demand release of the chemical agent. In addition, we provide a detailed approach for the fabrication of a multizone-SiNP array, allowing the simultaneous capture and release of multiple biomarkers of interest. Finally, we demonstrate the entire process of selective and quantitative capture and release of biomolecules from biosamples by means of a commercial low-volume microplate reader system, using green fluorescent protein as a biomarker example. The entire protocol can be conducted within 45 h and requires knowledge in nanoscience, surface chemistry, device micro- and nanofabrication procedures, microfluidics and protein quantification techniques. These SiNP array devices have already demonstrated applications for highly selective and quantitative analysis of a wide range of biological and chemical species, including proteins, nucleic acids, small molecules and ionic species.

4D label-free quantitative proteomic analysis identifies CRABP1 as a novel candidate gene for litter size in rabbits†

In commercial rabbit breeding, litter size is a crucial reproductive trait. This trait directly determines the reproductive ability of female rabbits and is crucial for evaluating the production efficiency. We here compared differentially expressed proteins of in the ovary tissue from New Zealand female rabbits with high (H) and low (L) litter sizes by using 4D label-free quantitative proteomic technology and identified 92 differential proteins. The biological functions of these proteins were revealed through gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Most distributions of GO and KEGG were related to reproduction, growth development, and metabolism. Furthermore, a novel candidate gene cellular retinoic acid binding protein-1 (CRABP1), which was highly expressed in the L group, was selected for further biological function verification. The Cell Counting Kit-8 (CCK-8) assay and flow cytometry analysis revealed that CRABP1 can promote granulosa cell (GC) apoptosis and inhibit GC proliferation. Furthermore, qRT-PCR and western blotting analysis revealed that CRABP1 regulates the genes (HSD17B1, Wnt-10b, FSHR, TAF4B, BMP15, and BMP6) and protein (Wnt-10b) associated with steroid hormone synthesis and follicle development. The PCR product direct sequencing method revealed single nucleotide polymorphisms in the core promoter region of CRABP1. Luciferase activity assays revealed that the transcriptional activity of the GG genotype was significantly higher than that of the TT or TG genotype. Different genotypes are accompanied by changes in transcription factors, which indicates that T-359G polymorphism can regulate CRABP1 expression. In general, we identified litter size-related genes and revealed the mechanism underlying the effect of CRABP1 on litter size. CRABP1 serves as a key factor in the reproductive capacity of rabbits and can act as a molecular biomarker for the breeding of New Zealand rabbits.

Applications of Omics Technology for Livestock Selection and Improvement

Conventional animal selection and breeding methods were based on the phenotypic performance of the animals. These methods have limitations, particularly for sex-limited traits and traits expressed later in the life cycle (e.g., carcass traits). Consequently, the genetic gain has been slow with high generation intervals. With the advent of high-throughput omics techniques and the availability of multi-omics technologies and sophisticated analytic packages, several promising tools and methods have been developed to estimate the actual genetic potential of the animals. It has now become possible to collect and access large and complex datasets comprising different genomics, transcriptomics, proteomics, metabolomics, and phonemics data as well as animal-level data (such as longevity, behavior, adaptation, etc.,), which provides new opportunities to better understand the mechanisms regulating animals' actual performance. The cost of omics technology and expertise of several fields like biology, bioinformatics, statistics, and computational biology make these technology impediments to its use in some cases. The population size and accurate phenotypic data recordings are other significant constraints for appropriate selection and breeding strategies. Nevertheless, omics technologies can estimate more accurate breeding values (BVs) and increase the genetic gain by assisting the section of genetically superior, disease-free animals at an early stage of life for enhancing animal productivity and profitability. This manuscript provides an overview of various omics technologies and their limitations for animal genetic selection and breeding decisions.

Green and Facile Assembly of Diverse Fused N-Heterocycles Using Gold-Catalyzed Cascade Reactions in Water

The present study describes an AuPPh₃Cl/AgSbF₆-catalyzed cascade reaction between amine nucleophiles and alkynoic acids in water. This process proceeds in high step economy with water as the sole coproduct, and leads to the generation of two rings, together with the formation of three new bonds in a single operation. This green cascade process exhibits valuable features such as low catalyst loading, good to excellent yields, high efficiency in bond formation, excellent selectivity, great tolerance of functional groups, and extraordinarily broad substrate scope. In addition, this is the first example of the generation of an indole/thiophene/pyrrole/pyridine/naphthalene/benzene-fused N-heterocycle library through gold catalysis in water from readily available materials. Notably, the discovery of antibacterial molecules from this library demonstrates its high quality and potential for the identification of active pharmaceutical ingredients.

Proteome profiling in the hippocampus, medial prefrontal cortex, and striatum of aging rat

Decrease in multiple functions occurs in the brain with aging, all of which can contribute to age-related cognitive and locomotor impairments. Brain atrophy specifically in hippocampus, medial prefrontal cortex (mPFC), and striatum, can contribute to this age-associated decline in function. Our recent metabolomics analysis showed age-related changes in these brain regions. To further understand the aging processes, analysis using a proteomics approach was carried out. This study was conducted to identify proteome profiles in the hippocampus, mPFC, and striatum of 14-, 18-, 23-, and 27-month-old rats. Proteomics analysis using ultrahigh performance liquid chromatography coupled with Q Exactive HF Orbitrap mass spectrometry identified 1074 proteins in the hippocampus, 871 proteins in the mPFC, and 241 proteins in the striatum. Of these proteins, 97 in the hippocampus, 25 in mPFC, and 5 in striatum were differentially expressed with age. The altered proteins were classified into three ontologies (cellular component, molecular function, and biological process) containing 44, 38, and 35 functional groups in the hippocampus, mPFC, and striatum, respectively. Most of these altered proteins participate in oxidative phosphorylation (e.g. cytochrome c oxidase and ATP synthase), glutathione metabolism (e.g. peroxiredoxins), or calcium signaling pathway (e.g. protein S100B and calmodulin). The most prominent changes were observed in the oldest animals. These results suggest that alterations in oxidative phosphorylation, glutathione metabolism, and calcium signaling pathway are involved in cognitive and locomotor impairments in aging.

Advances in Fasciola hepatica research using 'omics' technologies

The liver fluke Fasciola hepatica is an economically important pathogen of livestock worldwide, as well as being an important neglected zoonosis. Parasite control is reliant on the use of drugs, particularly triclabendazole, which is effective against multiple parasite stages. However, the spread of parasites resistant to triclabendazole has intensified the pursuit for novel control strategies. Emerging 'omics' technologies are helping advance our understanding of liver fluke biology, specifically the molecules that act at the host-parasite interface and are central to infection, virulence and long-term survival within the definitive host. This review discusses the technological sequencing advances that have facilitated the unbiased analysis of liver fluke biology, resulting in an extensive range of 'omics' datasets. In addition, we highlight the 'omics' studies of host responses to F. hepatica infection that, when combined with the parasite datasets, provide the opportunity for integrated analyses of host-parasite interactions. These extensive datasets will form the foundation for future in-depth analysis of F. hepatica biology and development, and the search for new drug or vaccine interventions.

Integrating Omic Technologies in Alzheimer's Disease

Scientific advances in biomedical disciplines have allowed us to identify the underlying causes of many diseases with increased comprehension-leading the way towards precision medicine. In this context, unique disease and medical traits pave the way for the development of adapted disease management, drugs and therapies tailored to each patient. Bearing in mind that reductionism, an approach that has dominated biomedical research for many years and has resulted in the identification of definite cellular phenotypes and human diseases which are linked with specific integral molecules, we strongly believe that Alzheimer's Disease, one of the most common neurodegenerative diseases, could not be applied to the model of one disease-one assay-one drug. Regarding the discrete complexities in the molecular pathogenesis combined with the limited knowledge of inherited and sporadic forms of Alzheimer's disease, the great heterogeneity in the clinical development, as well as the plethora of validated biomarkers that have been proposed for early diagnosis or prognosis of the disease, we presume that a radically different way of thinking is in demand for comprehensive explanations of the molecular pathogenesis of the disease. In this article we highlight the most recent advances made in the omics field of systems biology towards a more complete understanding of Alzheimer's disease mechanisms, emphasizing to the paramount emergence of the development of various high-throughput strategies applied to the omics sciences.

Proteomic contributions to our understanding of vaccine and immune responses

Vaccines are one of the greatest public health successes; yet, due to the empirical nature of vaccine design, we have an incomplete understanding of how the genes and proteins induced by vaccines contribute to the development of both protective innate and adaptive immune responses. While the advent of genomics has enabled new vaccine development and facilitated understanding of the immune response, proteomics identifies potentially new vaccine antigens with increasing speed and sensitivity. In addition, as proteomics is complementary to transcriptomic approaches, a combination of both approaches provides a more comprehensive view of the immune response after vaccination via systems vaccinology. This review details the advances that proteomic strategies have made in vaccine development and reviews how proteomics contributes to the development of a more complete understanding of human vaccines and immune responses.

The role of proteomics in understanding biological mechanisms of sepsis

Sepsis is a systemic inflammatory state caused by infection. Complications of this infection with multiple organ failure lead to more lethal conditions, such as severe sepsis and septic shock. Sepsis is one of the leading causes of US deaths. Novel biomarkers with high sensitivity and specificity may be helpful for early diagnosis of sepsis and for improvement of patient outcomes through the development of new therapies. Mass spectrometry-based proteomics offers powerful tools to identify such biomarkers and furthermore to give insight to fundamental mechanisms of this clinical condition. In this review, we summarize findings from proteomics studies of sepsis and how their applications have provided more understanding into the pathogenesis of septic infection. Literatures related to "proteomics", "sepsis", "systemic inflammatory response syndrome", "severe sepsis", "septic infection", and "multiple organ dysfunction syndrome" were searched using PubMed. Findings about neonatal and adult sepsis are discussed separately. Within the adult sepsis studies, results are grouped based on the models (e.g., human or animal). Across investigations in clinical populations and in rodent and mammalian animal models, biological pathways, such as inflammatory and acute phase response, coagulation, complement, mitochondrial energy metabolism, chaperones, and oxidative stress, are altered at the protein level. These proteomics studies have discovered many novel biomarker candidates of septic infection. Validation the clinical use of these biomarker candidates may significantly impact the diagnosis and prognosis of sepsis. In addition, the molecular mechanisms revealed by these studies may also guide the development of more effective treatments.

Label-free Quantification of Proteins Using Data-Independent Acquisition

In recent years the inherit problems of the traditional data-dependent acquisition mode in shotgun proteomics have been recognized. These include bias towards fragmentation of abundant peptides, stochastic effects and chimeric product ion spectra. One of the approaches to deal with these limitations is by a technique termed data-independent acquisition (DIA). This technique is comprised of several approaches, all of which relate to the parallel fragmentation of peptides in an unbiased manner, irrespective of their abundance. Presented here is one such approach termed MSE. This chapter discusses the performance from this unique acquisition mode for identification and quantification of proteins in complex biological samples.

Chip-based nanoelectrospray mass spectrometry for protein characterization

In the last several years, significant progress has been made in the development of microfluidic-based analytical technologies for proteomic and drug discovery applications. Chip-based nanoelectrospray coupled to a mass spectrometer detector is one of the recently developed analytical microscale technologies. This technology offers unique advantages for automated nanoelectrospray including reduced sample consumption, improved detection sensitivity and enhanced data quality for proteomic studies. This review presents an overview and introduction of recent developments in chip devices coupled to electrospray mass spectrometers including the development of the automated nanoelectrospray ionization chip device for protein characterization. Applications using automated chip-based nanoelectrospray ionization technology in proteomic and bioanalytical studies are also extensively reviewed in the fields of high-throughput protein identification, protein post-translational modification studies, top-down proteomics, biomarker screening by pattern recognition, noncovalent protein-ligand binding for drug discovery and lipid analysis. Additionally, future trends in chip-based nanoelectrospray technology are discussed.

In-depth proteomic analysis of mouse cochlear sensory epithelium by mass spectrometry

Proteomic analysis of sensory organs such as the cochlea is challenging due to its small size and difficulties with membrane protein isolation. Mass spectrometry in conjunction with separation methods can provide a more comprehensive proteome, because of the ability to enrich protein samples, detect hydrophobic proteins, and identify low abundant proteins by reducing the proteome dynamic range. GELFrEE as well as different separation and digestion techniques were combined with FASP and nanoLC-MS/MS to obtain an in-depth proteome analysis of cochlear sensory epithelium from 30-day-old mice. Digestion with LysC/trypsin followed by SCX fractionation and multiple nanoLC-MS/MS analyses identified 3773 proteins with a 1% FDR. Of these, 694 protein IDs were in the plasmalemma. Protein IDs obtained by combining outcomes from GELFrEE/LysC/trypsin with GELFrEE/trypsin/trypsin generated 2779 proteins, of which 606 additional proteins were identified using the GELFrEE/LysC/trypsin approach. Combining results from the different techniques resulted in a total of 4620 IDs, including a number of previously unreported proteins. GO analyses showed high expression of binding and catalytic proteins as well as proteins associated with metabolism. The results show that the application of multiple techniques is needed to provide an exhaustive proteome of the cochlear sensory epithelium that includes many membrane proteins. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000231.

Proteomics and transcriptomics of broccoli subjected to exogenously supplied and transgenic senescence-induced cytokinin for amelioration of postharvest yellowing

Previously, we investigated transgenic broccoli harboring senescence-associated-gene (SAG) promoter-triggered isopentenyltransferase (ipt), which encodes the key enzyme for cytokinin (CK) synthesis and mimics the action of exogenous supplied CK in delaying postharvest senescence of broccoli. Here, we used proteomics and transcriptomics to compare the mechanisms of ipt-transgenic and N(6)-benzylaminopurine (BA) CK treatment of broccoli during postharvest storage. The 2 treatments conferred common and distinct mechanisms. BA treatment decreased the quantity of proteins involved in energy and carbohydrate metabolism and amino acid metabolism, and ipt-transgenic treatment increased that of stress-related proteins and molecular chaperones and slightly affected levels of carbohydrate metabolism proteins. Both treatments regulated genes involved in CK signaling, sugar transport, energy and carbohydrate metabolism, amino acid metabolism and lipid metabolism, although ipt-transgenic treatment to a lesser extent. BA treatment induced genes encoding molecular chaperones, whereas ipt-transgenic treatment induced stress-related genes for cellular protection during storage. Both BA and ipt-transgenic treatments acted antagonistically on ethylene functions. We propose a long-term acclimation of metabolism and protection systems with ipt-transgenic treatment of broccoli and short-term modulation of metabolism and establishment of a protection system with both BA and ipt-transgenic treatments in delaying senescence of broccoli florets.

BIOLOGICAL SIGNIFICANCE

Transgenic broccoli harboring senescence-associated-gene (SAG) promoter-triggered isopentenyltransferase (ipt), which encodes the key enzyme for cytokinin (CK) synthesis and N(6)-benzylaminopurine (BA) CK treated broccoli both showed retardation of postharvest senescence during storage. The mechanisms underlying the two treatments were compared. The combination of proteomic and transcriptomic evidences revealed that the 2 treatments conferred common and distinct mechanisms in delaying senescence of broccoli florets. We propose a long-term acclimation of metabolism and protection systems with ipt-transgenic treatment of broccoli and short-term modulation of metabolism and establishment of a protection system with both BA and ipt-transgenic treatments in delaying senescence of broccoli florets. This article is part of a Special Issue entitled: Translational Plant Proteomics.

Smart surface for elution of protein-protein bound particles: nanonewton dielectrophoretic forces using atomic layer deposited oxides

By increasing the strength of the negative dielectrophoresis force, we demonstrated a significantly improved electrokinetic actuation and switching microsystem that can be used to elute specifically bound beads from the surface. In this work using atomic layer deposition we deposited a pinhole free nanometer-scale thin film oxide as a protective layer to prevent electrodes from corrosion, when applying high voltages (>20 V(pp)) at the electrodes. Then, by exciting the electrodes at high frequency, we capacitively coupled the electrodes to the buffer in order to avoid electric field degradation and, hence, reduction in dielectrophoresis force due to the presence of the insulating oxide layer. To illustrate the functionality of our system, we demonstrated 100% detachment of anti-IgG and IgG bound beads (which is on the same order of magnitude in strength as typical antibody-antigen interactions) from the surface, upon applying the improved negative dielectrophoresis force. The significantly enhanced switching performance presented in this work shows orders of magnitude of improvement in on-to-off ratio and switching response time, without any need for chemical eluting agents, as compared to the previous work. The promising results from this work vindicates that the functionality of this singleplexed platform can be extended to perform a multiplexed bead-based assay where in a single channel an array of proteins are patterned each targeting a different antigen or protein.

Microbial proteomics using mass spectrometry

Proteomic analyses involve a series of intricate, interdependent steps involving approaches and technical issues that must be fully coordinated to obtain the optimal amount of required information about the test subject. Fortunately, many of these steps are common to most test subjects, requiring only modifications to or, in some cases, substitution of some of the steps to ensure they are relevant to the desired objective of a study. This fortunate occurrence creates an essential core of proteomic approaches and techniques that are consistently available for most studies, regardless of test subject. In this chapter, an overview of some of these core approaches, techniques, and mass spectrometric instrumentation is given, while indicating how such steps are useful for and applied to bacterial investigations. To exemplify how such proteomic concepts and techniques are applicable to bacterial investigations, a practical, quantitative method useful for bacterial proteomic analysis is presented with a discussion of possibilities, pitfalls, and some emerging technology to provide a compilation of information from the diverse literature that is intermingled with experimental experience.

Propofol anaesthesia alters the cerebral proteome differently from sevoflurane anaesthesia

Previous studies suggest that propofol and sevoflurane anaesthesia in rats may have variable effects on the proteome. Brains from untreated rats and rats anaesthetised with intravenous propofol infusion or inhaled sevoflurane were collected at various time points post-anaesthesia and subjected to global protein expression profiling using two-dimensional gel electrophoresis. Significant changes in protein spot intensity (i.e. expression) between the propofol and sevoflurane groups demonstrated clear similarities and differences in proteomic regulation by these anaesthetics. The proteins regulated were broadly classified into groups involved in cytoskeletal/neuronal growth, cellular metabolism, signalling, and cell stress/death responses. Proteins concerned with cell death and stress responses were down-regulated by both agents, but the anaesthetics had variable effects on proteins in the other groups. Importantly, proteins such as Ulip2 and dihydropyrimidinase-like-2 were regulated in opposite directions by propofol and sevoflurane. Moreover, the time-course of regulation of proteins varied depending on the agent used. These data suggest different underlying mechanisms of proteomic regulation. We found that sevoflurane anaesthesia had more pronounced effects, on a wider range of proteins, and over an apparently longer duration than propofol. Thus, sevoflurane could be considered a more disruptive anaesthetic agent. Our findings show that protein expression is regulated differentially according to the anaesthetic agent and the method of delivery support and extend our previous observations of differential genomic regulation by anaesthetics in the brain. This study highlights the power of proteomic studies in assessing the effects of certain anaesthetics on the integrity of neuronal structure and function.

Models at the single cell level

Many cellular behaviors cannot be completely captured or appropriately described at the cell population level. Noise induced by stochastic chemical reactions, spatially polarized signaling networks, and heterogeneous cell-cell communication are among the many phenomena that require fine-grained analysis. Accordingly, the mathematical models used to describe such systems must be capable of single cell or subcellular resolution. Here, we review techniques for modeling single cells, including models of stochastic chemical kinetics, spatially heterogeneous intracellular signaling, and spatial stochastic systems. We also briefly discuss applications of each type of model.

Molecular level characterization of the inorganic-bioorganic interface by solid state NMR: alanine on a silica surface, a case study

The molecular interface between bioorganics and inorganics plays a key role in diverse scientific and technological research areas including nanoelectronics, biomimetics, biomineralization, and medical applications such as drug delivery systems and implant coatings. However, the physical/chemical basis of recognition of inorganic surfaces by biomolecules remains unclear. The molecular level elucidation of specific interfacial interactions and the structural and dynamical state of the surface bound molecules is of prime scientific importance. In this study, we demonstrate the ability of solid state NMR methods to accomplish these goals. L-[1-(13)C,(15)N]Alanine loaded onto SBA-15 mesoporous silica with a high surface area served as a model system. The interacting alanine moiety was identified as the -NH(3)(+) functional group by (15)N{(1)H}SLF NMR. (29)Si{(15)N} and (15)N{(29)Si}REDOR NMR revealed intermolecular interactions between the alanine -NH(3)(+) and three to four surface Si species, predominantly Q(3), with similar internuclear N...Si distances of 4.0-4.2 A. Distinct dynamic states of the adsorbed biomolecules were identified by (15)N{(13)C}REDOR NMR, indicating both bound and free alanine populations, depending on hydration level and temperature. In the bound populations, the -NH(3)(+) group is surface anchored while the free carboxylate end undergoes librations, implying the carboxylate has small or no contributions to surface binding. When surface water clusters grow bigger with increased hydration, the libration amplitude of the carboxyl end amplifies, until onset of dissolution occurs. Our measurements provide the first direct, comprehensive, molecular-level identification of the bioorganic-inorganic interface, showing binding functional groups, geometric constraints, stoichiometry, and dynamics, both for the adsorbed amino acid and the silica surface.

Proteomics: a strategy to understand the novel targets in protein misfolding and cancer therapy

Proteins carry out important functions as they fold themselves. Protein misfolding occurs during different biochemical processes and may lead to the development of diseases such as cancer, which is characterized by genetic instability. The cancer microenvironment exposes malignant cells to a variety of stressful conditions that may further promote protein misfolding. Tumor development and progression often arises from mutations that interfere with the appropriate function of tumor-suppressor proteins and oncogenes. These may be due to alteration of catalytic activity of the protein, loss of binding sites for effector proteins or alterations of the native folded protein conformation. Src family kinases, p53, mTOR and C-terminus of HSC70 interacting protein (CHIPs) are some examples associated with protein misfolding and tumorigenesis. Molecular chaperones, such as heat-shock protein (HSP)70 and HSP90, assist protein folding and recognize target misfolded proteins for degradation. It is likely that this misfolding in cancer is linked by common principles, and may, therefore, present an exciting possibility to identify common targets for therapeutic intervention. Here we aim to review a number of examples that show how alterations in the folding of tumor-suppressor proteins or oncogenes lead to tumorigenesis. The possibility of targeting the targets to repair or degrade protein misfolding in cancer therapy is discussed.

A proteomics approach for the analysis of hemolymph proteins involved in the immediate defense response of the soft tick, Ornithodoros savignyi, when challenged with Candida albicans

A proteomics approach was employed to identify proteins secreted into the hemolymph of Ornithodorus savignyi ticks 2 h after immune-challenge with the yeast, Candida albicans. Profiling of the proteins present in hemolymph of unchallenged ticks versus ticks challenged with heat-killed yeast revealed five proteins to be differentially expressed. The modulated protein spots were subjected to tandem mass spectrometry (MS/MS) analysis, but could not be positively identified. These proteins can be assigned to the immune response as they were not induced after aseptic injury. In an attempt to identify hemolymph proteins that recognize and bind to yeast cells, hemolymph obtained from both unchallenged and challenged ticks was incubated with C. albicans. Elution of the bound proteins followed by SDS-PAGE analysis indicated that three proteins (97, 88 and 26 kDa) present in both unchallenged and challenged hemolymph samples bind to yeast cells. The constant presence of these three proteins in tick hemolymph leads us to believe that they may be involved in non-self recognition and participate in yeast clearance from tick plasma. The analyzed yeast-binding proteins could also not be positively identified, suggesting that all the tick immune proteins investigated in this study are novel.

Approaches and applications of quantitative LC-MS for proteomics and activitomics

LC-MS is a powerful technique in biomolecular research. In addition to its uses as a tool for protein and peptide quantization, LC-MS can also be used to quantify the activity of signalling and metabolic pathways in a multiplex and comprehensive manner, i.e. as an 'activitomic' tool. Taking cancer research as an illustrative example of application, this review discusses the concepts of biochemical pathway analysis using LC-MS-based proteomic and activitomic techniques.

Evaluation of protein pattern changes in roots and leaves of Zea mays plants in response to nitrate availability by two-dimensional gel electrophoresis analysis

BACKGROUND

Nitrogen nutrition is one of the major factors that limit growth and production of crop plants. It affects many processes, such as development, architecture, flowering, senescence and photosynthesis. Although the improvement in technologies for protein study and the widening of gene sequences have made possible the study of the plant proteomes, only limited information on proteome changes occurring in response to nitrogen amount are available up to now. In this work, two-dimensional gel electrophoresis (2-DE) has been used to investigate the protein changes induced by NO3- concentration in both roots and leaves of maize (Zea mays L.) plants. Moreover, in order to better evaluate the proteomic results, some biochemical and physiological parameters were measured.

RESULTS

Through 2-DE analysis, 20 and 18 spots that significantly changed their amount at least two folds in response to nitrate addition to the growth medium of starved maize plants were found in roots and leaves, respectively. Most of these spots were identified by Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry (LC-ESI-MS/MS). In roots, many of these changes were referred to enzymes involved in nitrate assimilation and in metabolic pathways implicated in the balance of the energy and redox status of the cell, among which the pentose phosphate pathway. In leaves, most of the characterized proteins were related to regulation of photosynthesis. Moreover, the up-accumulation of lipoxygenase 10 indicated that the leaf response to a high availability of nitrate may also involve a modification in lipid metabolism.Finally, this proteomic approach suggested that the nutritional status of the plant may affect two different post-translational modifications of phosphoenolpyruvate carboxylase (PEPCase) consisting in monoubiquitination and phosphorylation in roots and leaves, respectively.

CONCLUSION

This work provides a first characterization of the proteome changes that occur in response to nitrate availability in leaves and roots of maize plants. According to previous studies, the work confirms the relationship between nitrogen and carbon metabolisms and it rises some intriguing questions, concerning the possible role of NO and lipoxygenase 10 in roots and leaves, respectively. Although further studies will be necessary, this proteomic analysis underlines the central role of post-translational events in modulating pivotal enzymes, such as PEPCase.

Identification of novel Stat6 regulated proteins in IL-4-treated mouse lymphocytes

Interleukin 4 (IL-4) has an indispensable role in the differentiation of naive T helper (Th) cells toward the Th2 phenotype and induction of B cells to produce the IgE class of Igs. By regulating these two cell types, IL-4 has a pre-eminent role in regulation of allergic inflammation. IL-4-mediated regulation of T and B cell functions is largely transmitted through signal transducer and activator of transcription 6 (Stat6). In this study, we have used metabolic labeling and 2-D electrophoresis to detect differences in the proteomes of IL-4 stimulated spleen mononuclear cells of Stat6-/- and wild type mice and MS/MS for protein identification. With this methodology, we identified 49 unique proteins from 21 protein spots to be differentially expressed. Interestingly, in Stat6-/- CD4(+) cells the expression of isoform 2 of core binding factor b (CBFb2) was enhanced. CBFb is a non-DNA binding cofactor for the Runx family of transcription factors, which have been implicated in regulation of Th cell differentiation. We also found cellular nucleic acid protein (CNBP) to be downregulated in Stat6-/- cells. None of the proteins identified in this study have previously been reported to be regulated via Stat6. The results highlight the importance of exploiting proteomics tools to complement the studies on Stat6 target genes identified through transcriptional profiling.

The interactome: predicting the protein-protein interactions in cells

The term Interactome describes the set of all molecular interactions in cells, especially in the context of protein-protein interactions. These interactions are crucial for most cellular processes, so the full representation of the interaction repertoire is needed to understand the cell molecular machinery at the system biology level. In this short review, we compare various methods for predicting protein-protein interactions using sequence and structure information. The ultimate goal of those approaches is to present the complete methodology for the automatic selection of interaction partners using their amino acid sequences and/or three dimensional structures, if known. Apart from a description of each method, details of the software or web interface needed for high throughput prediction on the whole genome scale are also provided. The proposed validation of the theoretical methods using experimental data would be a better assessment of their accuracy.

Methods for the purification of HQ-tagged proteins

The HQ (H = histidine, Q = glutamine) tag is a small fusion tag that can be isolated using immobilized metal affinity columns. HQ-tagged proteins can be expressed and purified from bacterial cells under native and denaturing conditions, mammalian cells, insect cells, wheat germ and rabbit reticulocyte. Furthermore, HQ-tagged proteins can be purified using magnetic or non-magnetic resins in multiple formats from small to large-scale and manual or automated. In this chapter, we have described various protocols for the purification of HQ-tagged proteins.

Recent advances in mercury speciation analysis with focus on spectrometric methods and enriched stable isotope applications

This paper discusses some recent advances in spectrometric methods and approaches for mercury speciation analysis of environmental samples with focus on isotope dilution techniques for determination of mercury species' concentrations in gaseous samples and reaction rates in soils and sediments. Such analytical data is important inter alia in fundamental research on mercury biogeochemistry and for risk assessments of mercury-contaminated soils and sediments and for designing effective remedial actions. The paper describes how the use of enriched stable isotope tracers in mercury speciation analysis can improve the traceability and accuracy of results, facilitate rational method developments, and be useful for studying biogeochemical processes, i.e. rate of reactions and fluxes, of mercury species. In particular the possibilities to study and correct for unwanted species transformation reactions during sample treatment and to study "natural" transformations of species in environmental samples, or micro- and mesocosm ecosystems, during incubations are highlighted. Important considerations to generate relevant data in isotope tracer experiments as well as reliability and quality assurance of mercury speciation analysis in general are also discussed.

Discover true association rates in multi-protein complex proteomics data sets

Experimental processes to collect and process proteomics data are increasingly complex, while the computational methods to assess the quality and significance of these data remain unsophisticated. These challenges have led to many biological oversights and computational misconceptions. We developed a complete empirical Bayes model to analyze multi-protein complex (MPC) proteomics data derived from peptide mass spectrometry detections of purified protein complex pull-down experiments. Our model considers not only bait-prey associations, but also prey-prey associations missed in previous work. Using our model and a yeast MPC proteomics data set, we estimated that there should be an average of 28 true associations per MPC, almost ten times as high as was previously estimated. For data sets generated to mimic a real proteome, our model achieved on average 80% sensitivity in detecting true associations, as compared with the 3% sensitivity in previous work, while maintaining a comparable false discovery rate of 0.3%.

A statistical framework to discover true associations from multiprotein complex pull-down proteomics data sets

Experimental processes to collect and process proteomics data are increasingly complex, and the computational methods to assess the quality and significance of these data remain unsophisticated. These challenges have led to many biological oversights and computational misconceptions. We developed an empirical Bayes model to analyze multiprotein complex (MPC) proteomics data derived from peptide mass spectrometry detections of purified protein complex pull-down experiments. Using our model and two yeast proteomics data sets, we estimated that there should be an average of about 20 true associations per MPC, almost 10 times as high as was previously estimated. For data sets generated to mimic a real proteome, our model achieved on average 80% sensitivity in detecting true associations, as compared with the 3% sensitivity in previous work, while maintaining a comparable false discovery rate of 0.3%. Cross-examination of our results with protein complexes confirmed by various experimental techniques demonstrates that many true associations that cannot be identified by previous approach are identified by our method.

Proteomic evaluation of neonatal exposure to 2,2 ,4,4 ,5-pentabromodiphenyl ether

Exposure to the brominated flame retardant 2,2 ,4,4 ,5-pentabromodiphenyl ether (PBDE-99) during the brain growth spurt disrupts normal brain development in mice and results in disturbed spontaneous behavior in adulthood. The neurodevelopmental toxicity of PBDE-99 has been reported to affect the cholinergic and catecholaminergic systems. In this study we use a proteomics approach to study the early effect of PBDE-99 in two distinct regions of the neonatal mouse brain, the striatum and the hippocampus. A single oral dose of PBDE-99 (12 mg/kg body weight) or vehicle was administered to male NMRI mice on neonatal day 10, and the striatum and the hippocampus were isolated. Using two-dimensional fluorescence difference gel electrophoresis (2D-DIGE), we found 40 and 56 protein spots with significantly (p < 0.01) altered levels in the striatum and the hippocampus, respectively. We used matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF-MS) to determine the protein identity of 11 spots from the striatum and 10 from the hippocampus. We found that the levels of proteins involved in neurodegeneration and neuroplasticity (e.g., Gap-43/neuromodulin, stathmin) were typically altered in the striatum, and proteins involved in metabolism and energy production [e.g., alpha-enolase; gamma-enolase; ATP synthase, H+ transporting, mitochondrial F1 complex, beta subunit (Atp5b); and alpha-synuclein] were typically altered in the hippocampus. Interestingly, many of the identified proteins have been linked to protein kinase C signaling. In conclusion, we identify responses to early exposure to PBDE-99 that could contribute to persistent neurotoxic effects. This study also shows the usefulness of proteomics to identify potential biomarkers of developmental neurotoxicity of organohalogen compounds.

Identification of neutrophil gelatinase-associated lipocalin (NGAL) as a discriminatory marker of the hepatocyte-secreted protein response to IL-1beta: a proteomic analysis

The liver is the major source of proteins used throughout the body for various functions. Upon injury or infection, an acute phase response (APR) is initiated in the liver that is primarily mediated by inflammatory cytokines such as interleukin-1beta (IL-1beta) and interleukin-6. Among others, the APR is characterized by an altered protein synthetic profile. We used two-dimensional gel electrophoresis to study the dynamics of changes in protein synthesis in hepatocytes exposed to these inflammatory cytokines. Protein profiles were quantified using image analysis and further analyzed using multivariate statistical methods. Our results indicate that IL-1beta and IL-6 each induces secreted protein responses with distinct dynamics and dose-dependence. Parallel stimulation by IL-1beta and IL-6 results in a protein pattern indistinguishable from the IL-1beta pattern, indicating a dominant effect of IL-1beta over IL-6 at the doses tested. Multidimensional scaling (MDS) of correlation distances between protein secretion levels revealed two protein pairs that are robustly co-secreted across the various cytokine stimulation conditions, suggesting shared regulatory pathways. Finally, we also used multivariate alternating conditional expectation (MACE) to identify transformation functions that discriminated the cytokine-stimulated and untreated hepatocyte-secreted protein profiles. Our analysis indicates that the expression of neutrophil gelatinase-associated lipocalin (NGAL) was sufficient to discriminate between IL-1beta and IL-6 stimulation. The combination of proteomics and multivariate analysis is expected to provide new information on the cellular regulatory networks involved in generating specific cellular responses.

Molecular MR imaging in oncology

The implementation and integration of systems biology approaches with the emerging nanosciences and microchip technology will revolutionize profoundly molecular imaging and fuel the drive toward a more predictive and individualized health care. In combination with informatics platforms, key gene and protein targets will be identified, and serve as more effective targets for diagnostic and therapeutic interventions. Drug development also will be expedited by the judicious selection of more appropriate molecular biomarkers that will serve as objective end points of treatment efficacy, in addition to facilitating the development of new target-specific therapeutics. Finally, with the more widespread proliferation of high-field magnets and advancements in imaging hardware; acquisition methods; and novel,"smart" MR agents, the ability to achieve higher resolution analyses of tumor biology, cell track-ing, and gene expression will be realized more fully. Although radiologists will continue to serve as diagnostic consultants and assist in management decisions, the contributions from new developments in the biologic and molecular sciences will significantly alter the scope of our profession. Radiologists will be required to participate more actively in the individualized care of the patient and cultivate a deeper understanding of the underlying molecular basis of disease and molecular pharmacology for facilitating selection of the most appropriate combination of imaging studies that address biologically relevant questions. These radical changes in our profession will necessitate the re-education and emergence of a small cadre of professionals that is educated broadly in multiple scientific disciplines, and demonstrate expertise in clinical care and the basic sciences. The optimistic view is that this already is happening.

Bacterial proteomics and its role in antibacterial drug discovery

Gene-expression profiling technologies in general, and proteomic technologies in particular have proven extremely useful to study the physiological response of bacterial cells to various environmental stress conditions. Complex protein toolkits coordinated by sophisticated regulatory networks have evolved to accommodate bacterial survival under ever-present stress conditions such as varying temperatures, nutrient availability, or antibiotics produced by other microorganisms that compete for habitat. In the last decades, application of man-made antibacterial agents resulted in additional bacterial exposure to antibiotic stress. Whereas the targeted use of antibiotics has remarkably reduced human suffering from infectious diseases, the ever-increasing emergence of bacteria that are resistant to antibiotics has led to an urgent need for novel antibiotic strategies. The intent of this review is to present an overview of the major achievements of proteomic approaches to study adaptation networks that are crucial for bacterial survival with a special emphasis on the stress induced by antibiotic treatment. A further focus will be the review of the, so far few, published efforts to exploit the knowledge derived from bacterial proteomic studies directly for the antibacterial drug-discovery process.

Evaluation of an in vitro model of hepatic inflammatory response by gene expression profiling

The body's response to biochemical stress involves coordinated changes in the expression of several sets of genes that regulate its return to homeostasis. Although several cell culture systems have been utilized for studying such complex physiological events in vitro, their assessment has been limited to biochemical assays on individual genes and proteins, limiting interpretation of the results in a systems context. Advances in genomics provide an opportunity to provide a more comprehensive assessment. In this study, we have used DNA microarrays to profile gene expression dynamics during interleukin 6-stimulated inflammation in hepatocytes maintained in a stable, collagen double-gel in vitro model system. The observed expression profile was also compared with that obtained from rat liver tissue after burn injury to determine the extent and nature of responses captured by the in vitro system. Our results indicate that several aspects of the in vivo hepatic inflammatory response can be captured by the in vitro system at the molecular systems level. Statistical analysis of the mRNA profiles was also used to characterize the temporal response in each model system and demonstrate similar behavior. A small panel of molecules involved in the hepatic acute-phase response was also profiled, using quantitative kinetic polymerase chain reaction, to confirm these observations. These results indicate the utility of the stable hepatocyte culture system for expression profiling of inflammatory states and for providing insights into the interplay of changes in gene expression during complex physiological states.

Intact-protein based sample preparation strategies for proteome analysis in combination with mass spectrometry

The complexity of tissue and cell proteomes and the vast dynamic range of protein abundance present a formidable challenge for analysis that no one analytical technique can overcome. As a result, there is a need to integrate technologies to achieve the high-resolution and high-sensitivity analysis of complex biological samples. The combined technologies of separation science and biological mass spectrometry (Bio-MS) are the current workhorse in proteomics, and are continuing to evolve to meet the needs for high sensitivity and high throughput. They are relied upon for protein quantification, identification, and analysis of post-translational modifications (PTMs). The standard technique of two dimensional poly-acrylamide gel electrophoresis (2D PAGE) offers relatively limited resolution and sensitivity for the simultaneous analysis of all cellular proteins, with only the most highly abundant proteins detectable in whole cell or tissue-derived samples. Hence, many alternative strategies are being explored. Numerous sample preparation procedures are currently available to reduce sample complexity and to increase the detectability of low-abundance proteins. Maintaining proteins intact during sample preparation has important advantages compared with strategies that digest proteins at an early step. These strategies include the ability to quantitate and recover proteins, and the assessment of PTMs. A review of current intact protein-based strategies for protein sample preparation prior to mass spectrometry (MS) is presented in the context of biomedically driven applications.

Metal recognition of septapeptides via polypod molecular architecture

The understanding of the nature of recognition of inorganic materials by proteins is one of the core elements of and has profound implications in biological materials science and engineering. Using combinatorial display methods, a considerable number of short polypeptides have recently been selected with affinity to engineering materials. During these selections, more than several polypeptides are identified with binding specificity to a chosen inorganic material. Understanding the nature of surface recognition of materials by polypeptides is essential for rational design and biomimetic engineering of these inorganic-binding polypeptides for use as linkers, catalyzers, and growth modifiers in nanotechnology and nanobiotechnology. Although there may not be direct homology among the amino acids constituting the polypeptides, their function may come from conserved molecular architecture. Here we study crystallographic surface recognition of platinum metal-binding septapeptides by conformational analysis. We find that the septapeptides conform into certain molecular architectures containing multiple protrusions (polypods) that spatially match with the crystallographic metal surfaces. While the physical recognition may originate from how well the molecular polypods spatially match a given crystallographic surface, the degree of binding may be due to the reactive groups that form the polypods, e.g., charged or polar groups (e.g., hydroxyl and amine). These results are highly consistent with the experimental binding characteristics of the Pt binders with various degrees of affinities.

Use of high throughput genomic tools for the study of endothelial cell biology

The endothelium is an active, dynamic and heterogeneous organ. It lines the vessels in every organ system and regulates diverse and important biological functions. Over the past several years researchers have gained enormous insights into endothelial cell function in physiological processes such as coagulation and vascular reactivity, and pathophysiological disease states such as inflammation and atherosclerosis. Despite our expanding knowledge of endothelial cell biology, the molecular mechanisms underlying these functions remain largely unknown. The newly developed high throughput genomic tools and accompanying analytical methods provide powerful approaches for identifying new endothelial cell genes and characterizing their role in health and disease. Here, we review some of the recent genomics and proteomic advances that are providing new methodologies for endothelial cell and vascular biology research.

Towards quantitative biology: integration of biological information to elucidate disease pathways and to guide drug discovery

Developing a new drug is a tedious and expensive undertaking. The recently developed high-throughput experimental technologies, summarised by the terms genomics, transcriptomics, proteomics and metabolomics provide for the first time ever the means to comprehensively monitor the molecular level of disease processes. The "-omics" technologies facilitate the systematic characterisation of a drug target's physiology, thereby helping to reduce the typically high attrition rates in discovery projects, and improving the overall efficiency of pharmaceutical research processes. Currently, the bottleneck for taking full advantage of the new experimental technologies are the rapidly growing volumes of automatically produced biological data. A lack of scalable database systems and computational tools for target discovery has been recognised as a major hurdle. In this review, an overview will be given on recent progress in computational biology that has an impact on drug discovery applications. The focus will be on novel in silico methods to reconstruct regulatory networks, signalling cascades, and metabolic pathways, with an emphasis on comparative genomics and microarray-based approaches. Promising methods, such as the mathematical simulation of pathway dynamics are discussed in the context of applications in discovery projects. The review concludes by exemplifying concrete data-driven studies in pharmaceutical research that demonstrate the value of integrated computational systems for drug target identification and validation, screening assay development, as well as drug candidate efficacy and toxicity evaluations.

High-throughput measurement of protein stability in microtiter plates

The direct determination of protein stability at high throughput has applications in proteomics, directed evolution, and formulation. Each application places different requirements on the accuracy of stability or transition midpoint determination. The measurement of protein stability by chemical denaturation has been previously performed at medium throughput and high accuracy using autotitrating fluorometers, after removal of proteins from the 96-well plate format in which they were expressed and purified. Herein we present a higher-throughput method for measuring and indexing the stability of proteins maintained within the 96-well format using a fluorescence microplate reader. Protein unfolding transitions were monitored by tryptophan fluorescence at 340 nm and assessed using bovine and equine cytochrome c (cyt c), as well as bovine serum albumin (BSA) stabilized with various amounts of palmitic acid. Two different approaches for generating unfolding curves in microtiter plates have been evaluated for their accuracy and applicability. Unfolding curves generated by the serial addition of denaturant into single wells allowed high-throughput stability screens capable of identifying protein variants with unfolding midpoint differences of 0.15 M denaturant concentration or larger. Such a method would be suitable for screening large numbers of proteins, as typically generated for directed evolution. Unfolding curves generated using one well per denaturant concentration allowed for medium-throughput stability screening and generated more accurate and precise stability values (C(1/2) +/- 0.05 M, m(G), and DeltaG(H2O)) for cyt c that are similar to values reported in literature. This method is suitable for screening the smaller numbers of proteins generated in proteomic research programmes. By using BSA stabilized with various palmitate concentrations and simple numerical indexing, it was shown that both experimental methods can successfully rank the order of protein stability.

Tackling the plant proteome: practical approaches, hurdles and experimental tools

The study of complex biological questions through comparative proteomics is becoming increasingly attractive to plant biologists as the rapidly expanding plant genomic and expressed sequence tag databases provide improved opportunities for protein identification. This review focuses on practical issues associated with comparative proteomic analysis, including the challenges of effective protein extraction and separation from plant tissues, the pros and cons of two-dimensional gel-based analysis and the problems of identifying proteins from species that are not recognized models for functional genomic studies. Specific points are illustrated using data from an ongoing study of the tomato and pepper fruit proteomes.

Potential for False Positive Identifications from Large Databases through Tandem Mass Spectrometry

The biomedical research community at large is increasingly employing shotgun proteomics for large-scale identification of proteins from enzymatic digests. Typically, the approach used to identify proteins and peptides from tandem mass spectral data is based on the matching of experimentally generated tandem mass spectra to the theoretical best match from a protein database. Here, we present the potential difficulties of using such an approach without statistical consideration of the false positive rate, especially when large databases, as are encountered in eukaryotes are considered. This is illustrated by searching a dataset generated from a multidimensional separation of a eukaryotic tryptic digest against an in silico generated random protein database, which generated a significant number of positive matches, even when previously suggested score filtering criteria are used.

Proteomic profiling of bone marrow mesenchymal stem cells upon transforming growth factor beta1 stimulation

Bone marrow mesenchymal stem cells (MSCs) can differentiate into different types of cells and have tremendous potential for cell therapy and tissue engineering. Transforming growth factor beta1 (TGF-beta) plays an important role in cell differentiation and vascular remodeling. We showed that TGF-beta induced cell morphology change and an increase in actin fibers in MSCs. To determine the global effects of TGF-beta on MSCs, we employed a proteomic strategy to analyze the effect of TGF-beta on the human MSC proteome. By using two-dimensional gel electrophoresis and electrospray ionization coupled to quadrupole/time-of-flight tandem mass spectrometers, we have generated a proteome reference map of MSCs, and we identified approximately 30 proteins with an increase or decrease in expression or phosphorylation in response to TGF-beta. The proteins regulated by TGF-beta included cytoskeletal proteins, matrix synthesis proteins, membrane proteins, metabolic enzymes, etc. TGF-beta increased the expression of smooth muscle alpha-actin and decreased the expression of gelsolin. Overexpression of gelsolin inhibited TGF-beta-induced assembly of smooth muscle alpha-actin; on the other hand, knocking down gelsolin expression enhanced the assembly of alpha-actin and actin filaments without significantly affecting alpha-actin expression. These results suggest that TGF-beta coordinates the increase of alpha-actin and the decrease of gelsolin to promote MSC differentiation. This study demonstrates that proteomic tools are valuable in studying stem cell differentiation and elucidating the underlying molecular mechanisms.

Sharing neuroimaging studies of human cognition

After more than a decade of collecting large neuroimaging datasets, neuroscientists are now working to archive these studies in publicly accessible databases. In particular, the fMRI Data Center (fMRIDC), a high-performance computing center managed by computer and brain scientists, seeks to catalogue and openly disseminate the data from published fMRI studies to the community. This repository enables experimental validation and allows researchers to combine and examine patterns of brain activity beyond that of any single study. As with some biological databases, early scientific, technical and sociological concerns hindered initial acceptance of the fMRIDC. However, with the continued growth of this and other neuroscience archives, researchers are recognizing the potential of such resources for identifying new knowledge about cognitive and neural activity. Thus, the field of neuroimaging is following the lead of biology and chemistry, mining its accumulating body of knowledge and moving toward a 'discovery science' of brain function.

Guided cell patterning on gold–silicon dioxide substrates by surface molecular engineering

We report an effective approach to patterning cells on gold-silicon dioxide substrates with high precision, selectivity, stability, and reproducibility. This technique is based on photolithography and surface molecular engineering and requires no cell positioning or delivery devices, thus significantly reducing the potential damage to cells. The cell patterning was achieved by activating the gold regions of the substrate with functionalized thiols that covalently bind proteins onto the gold regions to guide subsequent cell adhesion while passivating the silicon dioxide background with polyethylene glycol to resist cell adhesion. Fourier transform infrared reflectance spectroscopy verified the successful immobilization of proteins on gold surfaces. Protein patterns were visualized by tagging proteins with Rhodamine fluorescent probes. Time-of-flight secondary ion mass spectrometry was used to characterize the chemistry of both the cell-adhesive and cell-resistant regions of surfaces after each key chemical reaction occurring during the molecular surface engineering. The ability of the engineered surfaces to guide cell adhesion was illustrated by differential interference contrast (DIC) reflectance microscopy. The cell patterning technique introduced in this study is compatible with micro- and photo-electronics, and may have many medical, environmental, and defense applications.