Comprehensive comparison of iTRAQ and label-free LC-based quantitative proteomics approaches using two Chlamydomonas reinhardtii strains of interest for biofuels engineering

Simultaneous ammonia and nitrate removal in an airlift reactor using poly(butylene succinate) as carbon source and biofilm carrier

In this study, an airlift inner-loop sequencing batch reactor using poly(butylene succinate) as the biofilm carrier and carbon source was operated under an alternant aerobic/anoxic strategy for nitrogen removal in recirculating aquaculture system. The average TAN and nitrate removal rates of 47.35±15.62gNH4-Nm(-3)d(-1) and 0.64±0.14kgNO3-Nm(-3)d(-1) were achieved with no obvious nitrite accumulation (0.70±0.76mg/L) and the dissolved organic carbon in effluents was maintained at 148.38±39.06mg/L. Besides, the activities of dissimilatory nitrate reduction to ammonium and sulfate reduction activities were successfully inhibited. The proteome KEGG analysis illustrated that ammonia might be removed through heterotrophic nitrification, while the activities of nitrate and nitrite reductases were enhanced through aeration treatment. The microbial community analysis revealed that denitrifiers of Azoarcus and Simplicispira occupied the dominate abundance which accounted for the high nitrate removal performance. Overall, this study broadened our understanding of simultaneous nitrification and denitrification using biodegradable material as biofilm carrier.

Label-free quantitative proteomic analysis of pre-flowering PMeV-infected Carica papaya L

Papaya meleira virus (PMeV) infects papaya (Carica papaya L.) and leads to Papaya Sticky Disease (PSD) or "Meleira", characterized by a spontaneous exudation of latex from fruits and leaves only in the post-flowering developmental stage. The latex oxidizes in contact with air and accumulates as a sticky substance on the plant organs, impairing papaya fruit's marketing and exportation. To understand pre-flowering C. papaya resistance to PMeV, an LC-MS/MS-based label-free proteomics approach was used to assess the differential proteome of PMeV-infected pre-flowering C. papaya vs. uninfected (control) plants. In this study, 1333 proteins were identified, of which 111 proteins showed a significant abundance change (57 increased and 54 decreased) and supports the hypothesis of increased photosynthesis and reduction of 26S-proteassoma activity and cell-wall remodeling. All of these results suggest that increased photosynthetic activity has a positive effect on the induction of plant immunity, whereas the reduction of caspase-like activity and the observed changes in the cell-wall associated proteins impairs the full activation of defense response based on hypersensitive response and viral movement obstruction in pre-flowering C. papaya plants.

BIOLOGICAL SIGNIFICANCE

The papaya (Carica papaya L.) fruit's production is severely limited by the occurrence of Papaya meleira virus (PMeV) infection, which causes Papaya Sticky Disease (PSD). Despite the efforts to understand key features involved with the plant×virus interaction, PSD management is still largely based on the observation of the first disease symptoms in the field, followed by the elimination of the diseased plants. However, C. papaya develops PSD only after flowering, i.e. about six-months after planting, and the virus inoculum sources are kept in field. The development of PMeV resistant genotypes is impaired by the limited knowledge about C. papaya resistance against viruses. The occurrence of a resistance/tolerance mechanism to PSD symptoms development prior to C. papaya flowering is considered in this study. Thus, field-grown and PMeV-infected C. papaya leaf samples were analyzed using proteomics, which revealed the modulation of photosynthesis-, 26S proteasome- and cell-wall remodeling-associated proteins. The data implicate a role for those systems in C. papaya resistance to viruses and support the idea of a partial resistance induction in the plants at pre-flowering stage. The specific proteins presented in the manuscript represent a starting point to the selection of key genes to be used in C. papaya improvement to PMeV infection resistance. The presented data also contribute to the understanding of virus-induced disease symptoms development in plants, of interest to the plant-virus interaction field.

A Pathway Proteomic Profile of Ischemic Stroke Survivors Reveals Innate Immune Dysfunction in Association with Mild Symptoms of Depression - A Pilot Study

Depression after stroke is a common occurrence, raising questions as to whether depression could be a long-term biological and immunological sequela of stroke. Early explanations for post-stroke depression (PSD) focused on the neuropsychological/psychosocial effects of stroke on mobility and quality of life. However, recent investigations have revealed imbalances of inflammatory cytokine levels in association with PSD, though to date, there is only one published proteomic pathway analysis testing this hypothesis. Thus, we examined the serum proteome of stroke patients (n = 44, mean age = 63.62 years) and correlated these with the Montgomery–Åsberg Depression Rating Scale (MADRS) scores at 3 months post-stroke. Overall, the patients presented with mild depression symptoms on the MADRS, M = 6.40 (SD = 7.42). A discovery approach utilizing label-free relative quantification was employed utilizing an LC-ESI–MS/MS coupled to a LTQ-Orbitrap Elite (Thermo-Scientific). Identified peptides were analyzed using the gene set enrichment approach on several different genomic databases that all indicated significant downregulation of the complement and coagulation systems with increasing MADRS scores. Complement and coagulation systems are traditionally thought to play a key role in the innate immune system and are established precursors to the adaptive immune system through pro-inflammatory cytokine signaling. Both systems are known to be globally affected after ischemic or hemorrhagic stroke. Thus, our results suggest that lowered complement expression in the periphery in conjunction with depressive symptoms post-stroke may be a biomarker for incomplete recovery of brain metabolic needs, homeostasis, and inflammation following ischemic stroke damage. Further proteomic investigations are now required to construct the temporal profile, leading from acute lesion damage to manifestation of depressive symptoms. Overall, the findings provide support for the involvement of inflammatory and immune mechanisms in PSD symptoms and further demonstrate the value and feasibility of the proteomic approach in stroke research.

The proteome and phosphoproteome of maize pollen uncovers fertility candidate proteins

Maize is unique since it is both monoecious and diclinous (separate male and female flowers on the same plant). We investigated the proteome and phosphoproteome of maize pollen containing modified proteins and here we provide a comprehensive pollen proteome and phosphoproteome which contain 100,990 peptides from 6750 proteins and 5292 phosphorylated sites corresponding to 2257 maize phosphoproteins, respectively. Interestingly, among the total 27 overrepresented phosphosite motifs we identified here, 11 were novel motifs, which suggested different modification mechanisms in plants compared to those of animals. Enrichment analysis of pollen phosphoproteins showed that pathways including DNA synthesis/chromatin structure, regulation of RNA transcription, protein modification, cell organization, signal transduction, cell cycle, vesicle transport, transport of ions and metabolisms, which were involved in pollen development, the following germination and pollen tube growth, were regulated by phosphorylation. In this study, we also found 430 kinases and 105 phosphatases in the maize pollen phosphoproteome, among which calcium dependent protein kinases (CDPKs), leucine rich repeat kinase, SNF1 related protein kinases and MAPK family proteins were heavily enriched and further analyzed. From our research, we also uncovered hundreds of male sterility-associated proteins and phosphoproteins that might influence maize productivity and serve as targets for hybrid maize seed production. At last, a putative complex signaling pathway involving CDPKs, MAPKs, ubiquitin ligases and multiple fertility proteins was constructed. Overall, our data provides new insight for further investigation of protein phosphorylation status in mature maize pollen and construction of maize male sterile mutants in the future.

Dissecting characteristics and dynamics of differentially expressed proteins during multistage carcinogenesis of human colorectal cancer

AIM: To discover novel biomarkers for early diagnosis, prognosis or treatment of human colorectal cancer.

METHODS: iTRAQ 2D LC-MS/MS analysis was used to identify differentially expressed proteins (DEPs) in the human colonic epithelial carcinogenic process using laser capture microdissection-purified colonic epithelial cells from normal colon, adenoma, carcinoma in situ and invasive carcinoma tissues.

RESULTS: A total of 326 DEPs were identified, and four DEPs (DMBT1, S100A9, Galectin-10, and S100A8) with progressive alteration in the carcinogenic process were further validated by immunohistochemistry. The DEPs were involved in multiple biological processes including cell cycle, cell adhesion, translation, mRNA processing, and protein synthesis. Some of the DEPs involved in cellular process such as “translation” and “mRNA splicing” were progressively up-regulated, while some DEPs involved in other processes such as “metabolism” and “cell response to stress” was progressively down-regulated. Other proteins with up- or down-regulation at certain stages of carcinogenesis may play various roles at different stages of the colorectal carcinogenic process.

CONCLUSION: These findings give insights into our understanding of the mechanisms of colorectal carcinogenesis and provide clues for further investigation of carcinogenesis and identification of biomarkers.

Synthetic and systems biology for microbial production of commodity chemicals

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

Nitrogen starvation-induced accumulation of triacylglycerol in the green algae: evidence for a role for ROC40, a transcription factor involved in circadian rhythm

Microalgal triacylglycerol (TAG), a promising source of biofuel, is induced upon nitrogen starvation (-N), but the proteins and genes involved in this process are poorly known. We performed isobaric tagging for relative and absolute quantification (iTRAQ)-based quantitative proteomics to identify Chlorella proteins with modulated expression under short-term -N. Out of 1736 soluble proteins and 2187 membrane-associated proteins identified, 288 and 56, respectively, were differentially expressed under -N. Gene expression analysis on select genes confirmed the same direction of mRNA modulation for most proteins. The MYB-related transcription factor ROC40 was the most induced protein, with a 9.6-fold increase upon -N. In a previously generated Chlamydomonas mutant, gravimetric measurements of crude total lipids revealed that roc40 was impaired in its ability to increase the accumulation of TAG upon -N, and this phenotype was complemented when wild-type Roc40 was expressed. Results from radiotracer experiments were consistent with the roc40 mutant being comparable to the wild type in recycling membrane lipids to TAG but being impaired in additional de novo synthesis of TAG during -N stress. In this study we provide evidence to support the hypothesis that transcription factor ROC40 has a role in -N-induced lipid accumulation, and uncover multiple previously unknown proteins modulated by short-term -N in green algae.

Plant Structure and Specificity - Challenges and Sample Preparation Considerations for Proteomics

Plants are considered as a simple structured organism when compared to humans and other vertebrates. The number of organs and tissue types is very limited. Instead the origin of the complexity comes from the high number and variety of plant species that exist, with >300,000 compared to 5000 in mammals. Proteomics, defined as the large-scale study of the proteins present in a tissue, cell or cellular compartment at a defined time point, was introduced in 1994. However, the first publications reported in the plant proteomics field only appeared at the beginning of the twenty-first century. Since these early years, the increase of proteomic studies in plants has only followed a linear trend. The main reason for this stems from the challenges specific to studying plants, those of protein extraction from cells with variously strengthened cellulosic cell walls, and a high abundance of interfering compounds, such as phenolic compounds and pigments located in plastids throughout the plant. Indeed, the heterogeneity between different organs and tissue types, between species and different developmental stages, requires the use of optimized plant protein extraction methods as described in this section. The second bottleneck of plant proteomics, which will not be discussed or reviewed here, is the lack of genomic information. Without sequence databases of the >300,000 species, proteomic studies of plants, especially of those that are not considered economically relevant, are impossible to accomplish.

Reproducibility of Differential Proteomic Technologies in CPTAC Fractionated Xenografts

The NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) employed a pair of reference xenograft proteomes for initial platform validation and ongoing quality control of its data collection for The Cancer Genome Atlas (TCGA) tumors. These two xenografts, representing basal and luminal-B human breast cancer, were fractionated and analyzed on six mass spectrometers in a total of 46 replicates divided between iTRAQ and label-free technologies, spanning a total of 1095 LC-MS/MS experiments. These data represent a unique opportunity to evaluate the stability of proteomic differentiation by mass spectrometry over many months of time for individual instruments or across instruments running dissimilar workflows. We evaluated iTRAQ reporter ions, label-free spectral counts, and label-free extracted ion chromatograms as strategies for data interpretation (source code is available from http://homepages.uc.edu/~wang2x7/Research.htm ). From these assessments, we found that differential genes from a single replicate were confirmed by other replicates on the same instrument from 61 to 93% of the time. When comparing across different instruments and quantitative technologies, using multiple replicates, differential genes were reproduced by other data sets from 67 to 99% of the time. Projecting gene differences to biological pathways and networks increased the degree of similarity. These overlaps send an encouraging message about the maturity of technologies for proteomic differentiation.

Quantitative Proteomics Analysis of the Hepatitis C Virus Replicon High-Permissive and Low-Permissive Cell Lines

Chronic hepatitis C virus (HCV) infection is one of the leading causes of severe hepatitis. The molecular mechanisms underlying HCV replication and pathogenesis remain unclear. The development of the subgenome replicon model system significantly enhanced study of HCV. However, the permissiveness of the HCV subgenome replicon greatly differs among different hepatoma cell lines. Proteomic analysis of different permissive cell lines might provide new clues in understanding HCV replication. In this study, to detect potential candidates that might account for the differences in HCV replication. Label-free and iTRAQ labeling were used to analyze the differentially expressed protein profiles between Huh7.5.1 wt and HepG2 cells. A total of 4919 proteins were quantified in which 114 proteins were commonly identified as differentially expressed by both quantitative methods. A total of 37 differential proteins were validated by qRT-PCR. The differential expression of Glutathione S-transferase P (GSTP1), Ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1), carboxylesterase 1 (CES1), vimentin, Proteasome activator complex subunit1 (PSME1), and Cathepsin B (CTSB) were verified by western blot. And over-expression of CTSB or knock-down of vimentin induced significant changes to HCV RNA levels. Additionally, we demonstrated that CTSB was able to inhibit HCV replication and viral protein translation. These results highlight the potential role of CTSB and vimentin in virus replication.

Proteomic approaches in research of cyanobacterial photosynthesis

Oxygenic photosynthesis in cyanobacteria, algae, and plants is carried out by a fabulous pigment-protein machinery that is amazingly complicated in structure and function. Many different approaches have been undertaken to characterize the most important aspects of photosynthesis, and proteomics has become the essential component in this research. Here we describe various methods which have been used in proteomic research of cyanobacteria, and demonstrate how proteomics is implemented into on-going studies of photosynthesis in cyanobacterial cells.

Using proteomic analysis to investigate uniconazole-induced phytohormone variation and starch accumulation in duckweed (Landoltia punctata)

BACKGROUND

Duckweed (Landoltia punctata) has the potential to remediate wastewater and accumulate enormous amounts of starch for bioethanol production. Using systematical screening, we determined that the highest biomass and starch percentage of duckweed was obtained after uniconazole application. Uniconazole contributes to starch accumulation of duckweed, but the molecular mechanism is still unclear.

RESULTS

To elucidate the mechanisms of high starch accumulation, in the study, the responses of L. punctata to uniconazole were investigated using a quantitative proteomic approach combined with physiological and biochemical analysis. A total of 3327 proteins were identified. Among these identified proteins, a large number of enzymes involved in endogenous hormone synthetic and starch metabolic pathways were affected. Notably, most of the enzymes involved in abscisic acid (ABA) biosynthesis showed up-regulated expression, which was consistent with the content variation. The increased endogenous ABA may up-regulate expression of ADP-glucose pyrophosphorylase to promote starch biosynthesis. Importantly, the expression levels of several key enzymes in the starch biosynthetic pathway were up-regulated, which supported the enzymatic assay results and may explain why there is increased starch accumulation.

CONCLUSIONS

These generated data linked uniconazole with changes in expression of enzymes involved in hormone biosynthesis and starch metabolic pathways and elucidated the effect of hormones on starch accumulation. Thus, this study not only provided insights into the molecular mechanisms of uniconazole-induced hormone variation and starch accumulation but also highlighted the potential for duckweed to be feedstock for biofuel as well as for sewage treatment.

Comparative Analysis of Label-Free and 8-Plex iTRAQ Approach for Quantitative Tissue Proteomic Analysis

High resolution proteomics approaches have been successfully utilized for the comprehensive characterization of the cell proteome. However, in the case of quantitative proteomics an open question still remains, which quantification strategy is best suited for identification of biologically relevant changes, especially in clinical specimens. In this study, a thorough comparison of a label-free approach (intensity-based) and 8-plex iTRAQ was conducted as applied to the analysis of tumor tissue samples from non-muscle invasive and muscle-invasive bladder cancer. For the latter, two acquisition strategies were tested including analysis of unfractionated and fractioned iTRAQ-labeled peptides. To reduce variability, aliquots of the same protein extract were used as starting material, whereas to obtain representative results per method further sample processing and MS analysis were conducted according to routinely applied protocols. Considering only multiple-peptide identifications, LC-MS/MS analysis resulted in the identification of 910, 1092 and 332 proteins by label-free, fractionated and unfractionated iTRAQ, respectively. The label-free strategy provided higher protein sequence coverage compared to both iTRAQ experiments. Even though pre-fraction of the iTRAQ labeled peptides allowed for a higher number of identifications, this was not accompanied by a respective increase in the number of differentially expressed changes detected. Validity of the proteomics output related to protein identification and differential expression was determined by comparison to existing data in the field (Protein Atlas and published data on the disease). All methods predicted changes which to a large extent agreed with published data, with label-free providing a higher number of significant changes than iTRAQ. Conclusively, both label-free and iTRAQ (when combined to peptide fractionation) provide high proteome coverage and apparently valid predictions in terms of differential expression, nevertheless label-free provides higher sequence coverage and ultimately detects a higher number of differentially expressed proteins. The risk for receiving false associations still exists, particularly when analyzing highly heterogeneous biological samples, raising the need for the analysis of higher sample numbers and/or application of adjustment for multiple testing.

Identification of regulatory network hubs that control lipid metabolism in Chlamydomonas reinhardtii

Microalgae-based biofuels are promising sources of alternative energy, but improvements throughout the production process are required to establish them as economically feasible. One of the most influential improvements would be a significant increase in lipid yields, which could be achieved by altering the regulation of lipid biosynthesis and accumulation. Chlamydomonas reinhardtii accumulates oil (triacylglycerols, TAG) in response to nitrogen (N) deprivation. Although a few important regulatory genes have been identified that are involved in controlling this process, a global understanding of the larger regulatory network has not been developed. In order to uncover this network in this species, a combined omics (transcriptomic, proteomic and metabolomic) analysis was applied to cells grown in a time course experiment after a shift from N-replete to N-depleted conditions. Changes in transcript and protein levels of 414 predicted transcription factors (TFs) and transcriptional regulators (TRs) were monitored relative to other genes. The TF and TR genes were thus classified by two separate measures: up-regulated versus down-regulated and early response versus late response relative to two phases of polar lipid synthesis (before and after TAG biosynthesis initiation). Lipidomic and primary metabolite profiling generated compound accumulation levels that were integrated with the transcript dataset and TF profiling to produce a transcriptional regulatory network. Evaluation of this proposed regulatory network led to the identification of several regulatory hubs that control many aspects of cellular metabolism, from N assimilation and metabolism, to central metabolism, photosynthesis and lipid metabolism.

Integrative proteomics to understand the transmission mechanism of Barley yellow dwarf virus-GPV by its insect vector Rhopalosiphum padi

Barley yellow dwarf virus-GPV (BYDV-GPV) is transmitted by Rhopalosiphum padi and Schizaphis graminum in a persistent nonpropagative manner. To improve our understanding of its transmission mechanism by aphid vectors, we used two approaches, isobaric tags for relative and absolute quantitation (iTRAQ) and yeast two-hybrid (YTH) system, to identify proteins in R. padi that may interact with or direct the spread of BYDV-GPV along the circulative transmission pathway. Thirty-three differential aphid proteins in viruliferous and nonviruliferous insects were identified using iTRAQ coupled to 2DLC-MS/MS. With the yeast two-hybrid system, 25 prey proteins were identified as interacting with the readthrough protein (RTP) and eight with the coat protein (CP), which are encoded by BYDV-GPV. Among the aphid proteins identified, most were involved in primary energy metabolism, synaptic vesicle cycle, the proteasome pathway and the cell cytoskeleton organization pathway. In a systematic comparison of the two methods, we found that the information generated by the two methods was complementary. Taken together, our findings provide useful information on the interactions between BYDV-GPV and its vector R. padi to further our understanding of the mechanisms regulating circulative transmission in aphid vectors.

Serum proteomes distinguish children developing type 1 diabetes in a cohort with HLA-conferred susceptibility

We determined longitudinal serum proteomics profiles from children with HLA-conferred diabetes susceptibility to identify changes that could be detected before seroconversion and positivity for disease-associated autoantibodies. Comparisons were made between children who seroconverted and progressed to type 1 diabetes (progressors) and those who remained autoantibody negative, matched by age, sex, sample periodicity, and risk group. The samples represented the prediabetic period and ranged from the age of 3 months to 12 years. After immunoaffinity depletion of the most abundant serum proteins, isobaric tags for relative and absolute quantification were used for sample labeling. Quantitative proteomic profiles were then measured for 13 case-control pairs by high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Additionally, a label-free LC-MS/MS approach was used to analyze depleted sera from six case-control pairs. Importantly, differences in abundance of a set of proteins were consistently detected before the appearance of autoantibodies in the progressors. Based on top-scoring pairs analysis, classification of such progressors was observed with a high success rate. Overall, the data provide a reference of temporal changes in the serum proteome in healthy children and children progressing to type 1 diabetes, including new protein candidates, the levels of which change before clinical diagnosis.

Evaluation of iTRAQ and SWATH-MS for the Quantification of Proteins Associated with Insulin Resistance in Human Duodenal Biopsy Samples

Insulin resistance (IR) is associated with increased production of triglyceride-rich lipoproteins of intestinal origin. In order to assess whether insulin resistance affects the proteins involved in lipid metabolism, we used two mass spectrometry based quantitative proteomics techniques to compare the intestinal proteome of 14 IR patients to that of 15 insulin sensitive (IS) control patients matched for age and waist circumference. A total of 3886 proteins were identified by the iTRAQ (Isobaric Tags for Relative and Absolute Quantitation) mass spectrometry approach and 2290 by the SWATH-MS strategy (Serial Window Acquisition of Theoretical Spectra). Using these two methods, 208 common proteins were identified with a confidence corresponding to FDR < 1%, and quantified with p-value < 0.05. The quantification of those 208 proteins has a Pearson correlation coefficient (r²) of 0.728 across the two techniques. Gene Ontology analyses of the differentially expressed proteins revealed that annotations related to lipid metabolic process and oxidation reduction process are overly represented in the set of under-expressed proteins in IR subjects. Furthermore, both methods quantified proteins of relevance to IR. These data also showed that SWATH-MS is a promising and compelling alternative to iTRAQ for protein quantitation of complex mixtures.

Quantifying reversible oxidation of protein thiols in photosynthetic organisms

Photosynthetic organisms use dynamic post-translational modifications to survive and adapt, which include reversible oxidative modifications of protein thiols that regulate protein structure, function, and activity. Efforts to quantify thiol modifications on a global scale have relied upon peptide derivatization, typically using isobaric tags such as TMT, ICAT, or iTRAQ that are more expensive, less accurate, and provide less proteome coverage than label-free approaches--suggesting the need for improved experimental designs for studies requiring maximal coverage and precision. Herein, we present the coverage and precision of resin-assisted thiol enrichment coupled to label-free quantitation for the characterization of reversible oxidative modifications on protein thiols. Using C. reinhardtii and Arabidopsis as model systems for algae and plants, we quantified 3662 and 1641 unique cysteinyl peptides, respectively, with median coefficient of variation (CV) of 13% and 16%. Further, our method is extendable for the detection of protein abundance changes and stoichiometries of cysteine oxidation. Finally, we demonstrate proof-of-principle for our method, and reveal that exogenous hydrogen peroxide treatment regulates the C. reinhardtii redox proteome by increasing or decreasing the level of oxidation of 501 or 67 peptides, respectively. As protein activity and function is controlled by oxidative modifications on protein thiols, resin-assisted thiol enrichment coupled to label-free quantitation can reveal how intracellular and environmental stimuli affect plant survival and fitness through oxidative stress.

Label-free quantitative phosphorylation analysis of human transgelin2 in Jurkat T cells reveals distinct phosphorylation patterns under PKA and PKC activation conditions

Background

Transgelin2, one of cytoskeletal actin binding proteins has recently been suggested to be involved in the formation of immune synapses. Although detailed function of transgelin2 is largely unknown, interactions between transgelin2 and actin appear to be important in regulating cellular functions of transgelin2. Because protein phosphorylation can change ability to interact with other proteins, comprehensive phosphorylation analysis of transgelin2 will be helpful in understanding its functional mechanisms.

Results

Here, a specific protein label-free quantitative phosphorylation analysis method combining immuno-precipitation, IMAC phosphopeptide enrichment technique and label-free relative quantification analysis was used to monitor the phosphorylation changes of transgelin2 overexpressed in Jurkat T cells under protein kinase C (PKC) and protein kinase A (PKA) activation conditions, two representative intracellular signalling pathways of immune cell activation and homeostasis. A total of six serine/threonine phosphorylation sites were identified including threonine-84, a novel phosphorylation site. Notably, distinct phosphorylation patterns of transgelin2 under the two kinase activation conditions were observed. Most phosphorylation sites showing specific kinase-dependent phosphorylation changes were discretely located in two previously characterized actin-binding regions: actin-binding site (ABS) and calponin repeat domain (CNR). PKC activation increased phosphorylation of threonine-180 and serine-185 in the CNR, and PKA activation increased phosphorylation of serine-163 in the ABS.

Conclusions

Multiple actin-binding regions of transgelin2 participate to accomplish its full actin-binding capability, and the actin-binding affinity of each actin-binding region appears to be modulated by specific kinase-dependent phosphorylation changes. Accordingly, different actin-binding properties or cellular functions of transgelin2 may result from distinct intracellular signalling events under immune response activation or homeostasis conditions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12953-015-0070-9) contains supplementary material, which is available to authorized users.

The regulation of photosynthetic structure and function during nitrogen deprivation in Chlamydomonas reinhardtii

The accumulation of carbon storage compounds by many unicellular algae after nutrient deprivation occurs despite declines in their photosynthetic apparatus. To understand the regulation and roles of photosynthesis during this potentially bioenergetically valuable process, we analyzed photosynthetic structure and function after nitrogen deprivation in the model alga Chlamydomonas reinhardtii. Transcriptomic, proteomic, metabolite, and lipid profiling and microscopic time course data were combined with multiple measures of photosynthetic function. Levels of transcripts and proteins of photosystems I and II and most antenna genes fell with differing trajectories; thylakoid membrane lipid levels decreased, while their proportions remained similar and thylakoid membrane organization appeared to be preserved. Cellular chlorophyll (Chl) content decreased more than 2-fold within 24 h, and we conclude from transcript protein and (13)C labeling rates that Chl synthesis was down-regulated both pre- and posttranslationally and that Chl levels fell because of a rapid cessation in synthesis and dilution by cellular growth rather than because of degradation. Photosynthetically driven oxygen production and the efficiency of photosystem II as well as P700(+) reduction and electrochromic shift kinetics all decreased over the time course, without evidence of substantial energy overflow. The results also indicate that linear electron flow fell approximately 15% more than cyclic flow over the first 24 h. Comparing Calvin-Benson cycle transcript and enzyme levels with changes in photosynthetic (13)CO2 incorporation rates also pointed to a coordinated multilevel down-regulation of photosynthetic fluxes during starch synthesis before the induction of high triacylglycerol accumulation rates.

The response of Chlamydomonas reinhardtii to nitrogen deprivation: a systems biology analysis

Drastic alteration in macronutrients causes large changes in gene expression in the photosynthetic unicellular alga Chlamydomonas reinhardtii. Preliminary data suggested that cells follow a biphasic response to this change hinging on the initiation of lipid accumulation, and we hypothesized that drastic repatterning of metabolism also followed this biphasic modality. To test this hypothesis, transcriptomic, proteomic, and metabolite changes that occur under nitrogen (N) deprivation were analyzed. Eight sampling times were selected covering the progressive slowing of growth and induction of oil synthesis between 4 and 6 h after N deprivation. Results of the combined, systems-level investigation indicated that C. reinhardtii cells sense and respond on a large scale within 30 min to a switch to N-deprived conditions turning on a largely gluconeogenic metabolic state, which then transitions to a glycolytic stage between 4 and 6 h after N depletion. This nitrogen-sensing system is transduced to carbon- and nitrogen-responsive pathways, leading to down-regulation of carbon assimilation and chlorophyll biosynthesis, and an increase in nitrogen metabolism and lipid biosynthesis. For example, the expression of nearly all the enzymes for assimilating nitrogen from ammonium, nitrate, nitrite, urea, formamide/acetamide, purines, pyrimidines, polyamines, amino acids and proteins increased significantly. Although arginine biosynthesis enzymes were also rapidly up-regulated, arginine pool size changes and isotopic labeling results indicated no increased flux through this pathway.

Bioflocculant production from untreated corn stover using Cellulosimicrobium cellulans L804 isolate and its application to harvesting microalgae

BACKGROUND

Microalgae are widely studied for biofuel production. Nevertheless, harvesting step of biomass is still a critical challenge. Bioflocculants have been applied in numerous applications including the low-cost harvest of microalgae. A major bottleneck for commercial application of bioflocculant is its high production cost. Lignocellulosic substrates are abundantly available. Hence, the hydrolyzates of rice stover and corn stover have been used as carbon source to produce the bioflocculant in previous studies. However, the hydrolyzates of biomass required the neutralization of pH before the downstream fermentation processes, and the toxic by-products produced during hydrolysis process inhibited the microbial activities in the subsequent fermentation processes and contaminated the bioflocculant product. Therefore, strains that can secrete plant cell-wall-degrading enzymes and simultaneously produce bioflocculants through directly degrading the lignocellulosic biomasses are of academic and practical interests.

RESULTS

A lignocellulose-degrading strain Cellulosimicrobium cellulans L804 was isolated in this study, which can produce the bioflocculant MBF-L804 using untreated biomasses, such as corn stover, corn cob, potato residues, and peanut shell. The effects of culture conditions including initial pH, carbon source, and nitrogen source on MBF-L804 production were analyzed. The results showed that over 80 % flocculating activity was achieved when the corn stover, corn cob, potato residues, and peanut shell were used as carbon sources and 4.75 g/L of MBF-L804 was achieved under the optimized condition: 20 g/L dry corn stover as carbon source, 3 g/L yeast extract as nitrogen source, pH 8.2. The bioflocculant MBF-L804 contained 68.6 % polysaccharides and 28.0 % proteins. The Gel permeation chromatography analysis indicated that the approximate molecular weight (MW) of MBF-L804 was 229 kDa. The feasibility of harvesting microalgae Chlamydomonas reinhardtii and Chlorella minutissima using MBF-L804 was evaluated. The highest flocculating efficiencies for C. reinhardtii and C. minutissima were 99.04 and 93.83 %, respectively.

CONCLUSIONS

This study shows for the first time that C. cellulans L804 can directly convert corn stover, corn cob, potato residues and peanut shell into the bioflocculants, which can be used to effectively harvest microalgae.

Studies on quantitative phosphopeptide analysis by matrix-assisted laser desorption/ionization mass spectrometry without label, chromatography or calibration curves

RATIONALE

Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry combined with isotope labeling methods are effective for protein and peptide quantification, but limited in their multiplexing capacity, cost-effectiveness and dynamic range. This study investigates MALDI-MS-based quantification of peptide phosphorylation without labeling, and aims to overcome the shot-to-shot variability of MALDI using a mathematical transformation and extended data acquisition times.

METHODS

A linear relationship between the reciprocal of phosphopeptide mole fraction and the reciprocal of phosphorylated-to-unphosphorylated signal ratio is derived, and evaluated experimentally using three separate phosphopeptide systems containing phosphorylated serine, threonine and tyrosine residues: mixtures of phosphopeptide and its des-phospho-analog with known stoichiometry measured by vacuum MALDI-linear ion trap mass spectrometry and fit to the linear model. The model is validated for quantifying in vitro phosphorylation assays with inhibition studies on Cdk2/cyclinA.

RESULTS

Dynamic range of picomoles to femtomoles, good accuracy (deviations of 1.5-3.0% from expected values) and reproducibility (relative standard deviation (RSD) = 4.3-6.3%) are achieved. Inhibition of cyclin-dependent kinase phosphorylation by the classical inhibitors olomoucine and r-roscovitine was evaluated and IC50 values found to be in agreement with reported literature values. These results, achieved with single-point calibration, without isotope or chromatography, compare favorably to those arrived at using isotope dilution (p > 0.5 for accuracy).

CONCLUSIONS

The mathematical relationship derived here can be applied to a method that we term Double Reciprocal Isotope-free Phosphopeptide Quantification (DRIP-Q), as a strategy for quantification of in vitro phosphorylation assays, the first MALDI-based, isotope- and calibration curve-free method of its type. These results also pave the way for further systematic studies investigating the effect of peptide composition and experimental conditions on quantitative, label-free MALDI.

Isobaric labeling-based relative quantification in shotgun proteomics

Mass spectrometry plays a key role in relative quantitative comparisons of proteins in order to understand their functional role in biological systems upon perturbation. In this review, we review studies that examine different aspects of isobaric labeling-based relative quantification for shotgun proteomic analysis. In particular, we focus on different types of isobaric reagents and their reaction chemistry (e.g., amine-, carbonyl-, and sulfhydryl-reactive). Various factors, such as ratio compression, reporter ion dynamic range, and others, cause an underestimation of changes in relative abundance of proteins across samples, undermining the ability of the isobaric labeling approach to be truly quantitative. These factors that affect quantification and the suggested combinations of experimental design and optimal data acquisition methods to increase the precision and accuracy of the measurements will be discussed. Finally, the extended application of isobaric labeling-based approach in hyperplexing strategy, targeted quantification, and phosphopeptide analysis are also examined.

Colonization state influences the hemocyte proteome in a beneficial squid-Vibrio symbiosis

The squid Euprymna scolopes and the luminescent bacterium Vibrio fischeri form a highly specific beneficial light organ symbiosis. Not only does the host have to select V. fischeri from the environment, but it must also prevent subsequent colonization by non-symbiotic microorganisms. Host macrophage-like hemocytes are believed to play a role in mediating the symbiosis with V. fischeri. Previous studies have shown that the colonization state of the light organ influences the host's hemocyte response to the symbiont. To further understand the molecular mechanisms behind this process, we used two quantitative mass-spectrometry-based proteomic techniques, isobaric tags for relative and absolute quantification (iTRAQ) and label-free spectral counting, to compare and quantify the adult hemocyte proteomes from colonized (sym) and uncolonized (antibiotic-treated/cured) squid. Overall, iTRAQ allowed for the quantification of 1,024 proteins with two or more peptides. Thirty-seven unique proteins were determined to be significantly different between sym and cured hemocytes (p value < 0.05), with 20 more abundant proteins and 17 less abundant in sym hemocytes. The label-free approach resulted in 1,241 proteins that were identified in all replicates. Of 185 unique proteins present at significantly different amounts in sym hemocytes (as determined by spectral counting), 92 were more abundant and 93 were less abundant. Comparisons between iTRAQ and spectral counting revealed that 30 of the 37 proteins quantified via iTRAQ exhibited trends similar to those identified by the label-free method. Both proteomic techniques mutually identified 16 proteins that were significantly different between the two groups of hemocytes (p value < 0.05). The presence of V. fischeri in the host light organ influenced the abundance of proteins associated with the cytoskeleton, adhesion, lysosomes, proteolysis, and the innate immune response. These data provide evidence that colonization by V. fischeri alters the hemocyte proteome and reveals proteins that may be important for maintaining host-symbiont specificity.

Phosphoproteomics in photosynthetic organisms

As primarily sessile organisms, photosynthetic species survive in dynamic environments by using elegant signaling pathways to manifest molecular responses to extracellular cues. These pathways exploit phosphorylation of specific amino acids (e.g. serine, threonine, tyrosine), which impact protein structure, function, and localization. Despite substantial progress in implementation of phosphoproteomics to understand photosynthetic organisms, researchers still struggle to translate a biological question into an experimental strategy and vice versa. This review evaluates the current status of phosphoproteomics in photosynthetic organisms and concludes with recommendations based on current knowledge.

Oleosome-associated protein of the oleaginous diatom Fistulifera solaris contains an endoplasmic reticulum-targeting signal sequence

Microalgae tend to accumulate lipids as an energy storage material in the specific organelle, oleosomes. Current studies have demonstrated that lipids derived from microalgal oleosomes are a promising source of biofuels, while the oleosome formation mechanism has not been fully elucidated. Oleosome-associated proteins have been identified from several microalgae to elucidate the fundamental mechanisms of oleosome formation, although understanding their functions is still in infancy. Recently, we discovered a diatom-oleosome-associated-protein 1 (DOAP1) from the oleaginous diatom, Fistulifera solaris JPCC DA0580. The DOAP1 sequence implied that this protein might be transported into the endoplasmic reticulum (ER) due to the signal sequence. To ensure this, we fused the signal sequence to green fluorescence protein. The fusion protein distributed around the chloroplast as like a meshwork membrane structure, indicating the ER localization. This result suggests that DOAP1 could firstly localize at the ER, then move to the oleosomes. This study also demonstrated that the DOAP1 signal sequence allowed recombinant proteins to be specifically expressed in the ER of the oleaginous diatom. It would be a useful technique for engineering the lipid synthesis pathways existing in the ER, and finally controlling the biofuel quality.

The global phosphoproteome of Chlamydomonas reinhardtii reveals complex organellar phosphorylation in the flagella and thylakoid membrane

Chlamydomonas reinhardtii is the most intensively-studied and well-developed model for investigation of a wide-range of microalgal processes ranging from basic development through understanding triacylglycerol production. Although proteomic technologies permit interrogation of these processes at the protein level and efforts to date indicate phosphorylation-based regulation of proteins in C. reinhardtii is essential for its underlying biology, characterization of the C. reinhardtii phosphoproteome has been limited. Herein, we report the richest exploration of the C. reinhardtii proteome to date. Complementary enrichment strategies were used to detect 4588 phosphoproteins distributed among every cellular component in C. reinhardtii. Additionally, we report 18,160 unique phosphopeptides at <1% false discovery rate, which comprise 15,862 unique phosphosites - 98% of which are novel. Given that an estimated 30% of proteins in a eukaryotic cell are subject to phosphorylation, we report the majority of the phosphoproteome (23%) of C. reinhardtii. Proteins in key biological pathways were phosphorylated, including photosynthesis, pigment production, carbon assimilation, glycolysis, and protein and carbohydrate metabolism, and it is noteworthy that hyperphosphorylation was observed in flagellar proteins. This rich data set is available via ProteomeXchange (ID: PXD000783) and will significantly enhance understanding of a range of regulatory mechanisms controlling a variety of cellular process and will serve as a critical resource for the microalgal community.

Integrated quantitative analysis of nitrogen stress response in Chlamydomonas reinhardtii using metabolite and protein profiling

Nitrogen starvation induces a global stress response in microalgae that results in the accumulation of lipids as a potential source of biofuel. Using GC-MS-based metabolite and iTRAQ-labeled protein profiling, we examined and correlated the metabolic and proteomic response of Chlamydomonas reinhardtii under nitrogen stress. Key amino acids and metabolites involved in nitrogen sparing pathways, methyl group transfer reactions, and energy production were decreased in abundance, whereas certain fatty acids, citric acid, methionine, citramalic acid, triethanolamine, nicotianamine, trehalose, and sorbitol were increased in abundance. Proteins involved in nitrogen assimilation, amino acid metabolism, oxidative phosphorylation, glycolysis, TCA cycle, starch, and lipid metabolism were elevated compared with nonstressed cultures. In contrast, the enzymes of the glyoxylate cycle, one carbon metabolism, pentose phosphate pathway, the Calvin cycle, photosynthetic and light harvesting complex, and ribosomes were reduced. A noteworthy observation was that citrate accumulated during nitrogen stress coordinate with alterations in the enzymes that produce or utilize this metabolite, demonstrating the value of comparing protein and metabolite profiles to understand complex patterns of metabolic flow. Thus, the current study provides unique insight into the global metabolic adjustments leading to lipid storage during N starvation for application toward advanced biofuel production technologies.

Comparative quantitative proteomics analysis of the ABA response of roots of drought-sensitive and drought-tolerant wheat varieties identifies proteomic signatures of drought adaptability

Wheat is one of the most highly cultivated cereals in the world. Like other cultivated crops, wheat production is significantly affected by abiotic stresses such as drought. Multiple wheat varieties suitable for different geographical regions of the world have been developed that are adapted to different environmental conditions; however, the molecular basis of such adaptations remains unknown in most cases. We have compared the quantitative proteomics profile of the roots of two different wheat varieties, Nesser (drought-tolerant) and Opata (drought-sensitive), in the absence and presence of abscisic acid (ABA, as a proxy for drought). A labeling LC-based quantitative proteomics approach using iTRAQ was applied to elucidate the changes in protein abundance levels. Quantitative differences in protein levels were analyzed for the evaluation of inherent differences between the two varieties as well as the overall and variety-specific effect of ABA on the root proteome. This study reveals the most elaborate ABA-responsive root proteome identified to date in wheat. A large number of proteins exhibited inherently different expression levels between Nesser and Opata. Additionally, significantly higher numbers of proteins were ABA-responsive in Nesser roots compared with Opata roots. Furthermore, several proteins showed variety-specific regulation by ABA, suggesting their role in drought adaptation.

HCD-only fragmentation method balances peptide identification and quantitation of TMT-labeled samples in hybrid linear ion trap/orbitrap mass spectrometers

Protein quantitation based on the generation of reporter ions from chemical labels is a widely used quantitative proteomics approach that enables measuring changes in protein abundance in response to biological perturbations. Isobaric labeling strategies at the MS2 level allow simultaneous measurements of different samples but it requires a fine-tuning of the collision energy used in HCD fragmentation to simultaneously obtain confident peptide identifications and highly sensitive and accurate quantitation. Although the recent development of dual CID/HCD fragmentation methods to circumvent these limitations, the fact is that many laboratories still use HCD-only methods for routine TMT protein quantitation experiments. Here, we have explored the effect of the collision energy on peptide identification and quantitation using HCD-only fragmentation methods on a linear ion trap/orbitrap mass spectrometer bearing an axial field HCD fragmentation cell. Our results using the HCD-only method show that a balance between the increase in the number of peptide identifications and the decrease in the precision of peptide quantitation is attained at a normalized collision energy of 40%. The HCD-only method at 40% does not only yield better results than those obtained using a higher collision energies, but it also outperforms the results obtained using the available CID/HCD dual method.

BIOLOGICAL SIGNIFICANCE

In this work we have explored the effect of the collision energy on peptide identification and quantitation using HCD-only fragmentation methods on an Orbitrap Velos Pro mass spectrometer. Our results show that when using a HCD-only method, a balance between the number of peptide identifications and the precision of peptide quantitation is attained at a normalized collision energy (NCE) of 40%. This contrast with the parameters routinely used in many laboratories, which are set at NCE 45%. The single HCD method at 40% does not only yield better results than those obtained using a collision energy of 45% but it also outperforms the results obtained using the available CID/HCD dual method. Therefore, we suggest that the single HCD method using the optimal NCE of 40% can therefore become the method of choice in routinely TMT protein quantitation experiments.

Proteomics analysis of oil body-associated proteins in the oleaginous diatom

For biodiesel production from microalgae, it is desirable to understand the entire triacylglycerol (TAG) metabolism. TAG accumulation occurs in oil bodies, and although oil body-associated proteins could play important roles in TAG metabolism, only a few microalgal species have been studied by a comprehensive analysis. Diatoms are microalgae that are promising producers of biodiesel, on which such proteomics analysis has not been conducted to date. Herein, we identified oil body-associated proteins in the oleaginous diatom Fistulifera sp. strain JPCC DA0580. The oil body fraction was separated by cell disruption with beads beating and subsequent ultracentrifugation. Contaminating factors could be removed by comparing proteins from the oil body and the soluble fractions. This novel strategy successfully revealed 15 proteins as oil body-associated protein candidates. Among them, two proteins, which were parts of proteins predicted to have transmembrane domains, were indeed confirmed to specifically localize to the oil bodies in this strain by observation of GFP fusion proteins. One (predicted to be a potassium channel) was also detected from the ER, suggesting that oil bodies might originate from the ER. By utilizing this novel subtraction method, we succeeded in identifying the oil body-associated proteins in the diatom for the first time.

Green fluorescent protein expression triggers proteome changes in breast cancer cells

Green fluorescent protein (GFP) is the most commonly used reporter of expression in cell biology despite evidence that it affects the cell physiology. The molecular mechanism of GFP-associated modifications has been largely unexplored. In this paper we investigated the proteome modifications following stable expression of GFP in breast cancer cells (MDA-MB-231). A combination of three different proteome analysis methods (2-DE, iTRAQ, label-free) was used to maximise proteome coverage. We found that GFP expression induces changes in expression of proteins that are associated with protein folding, cytoskeletal organisation and cellular immune response. In view of these findings, the use of GFP as a cell reporter should be carefully monitored.

Quantitative Proteomics via High Resolution MS Quantification: Capabilities and Limitations

Recent improvements in the mass accuracy and resolution of mass spectrometers have led to renewed interest in label-free quantification using data from the primary mass spectrum (MS1) acquired from data-dependent proteomics experiments. The capacity for higher specificity quantification of peptides from samples enriched for proteins of biological interest offers distinct advantages for hypothesis generating experiments relative to immunoassay detection methods or prespecified peptide ions measured by multiple reaction monitoring (MRM) approaches. Here we describe an evaluation of different methods to post-process peptide level quantification information to support protein level inference. We characterize the methods by examining their ability to recover a known dilution of a standard protein in background matrices of varying complexity. Additionally, the MS1 quantification results are compared to a standard, targeted, MRM approach on the same samples under equivalent instrument conditions. We show the existence of multiple peptides with MS1 quantification sensitivity similar to the best MRM peptides for each of the background matrices studied. Based on these results we provide recommendations on preferred approaches to leveraging quantitative measurements of multiple peptides to improve protein level inference.

iTRAQ-Based and Label-Free Proteomics Approaches for Studies of Human Adenovirus Infections

Both isobaric tags for relative and absolute quantitation (iTRAQ) and label-free methods are widely used for quantitative proteomics. Here, we provide a detailed evaluation of these proteomics approaches based on large datasets from biological samples. iTRAQ-label-based and label-free quantitations were compared using protein lysate samples from noninfected human lung epithelial A549 cells and from cells infected for 24 h with human adenovirus type 3 or type 5. Either iTRAQ-label-based or label-free methods were used, and the resulting samples were analyzed by liquid chromatography (LC) and tandem mass spectrometry (MS/MS). To reduce a possible bias from quantitation software, we applied several software packages for each procedure. ProteinPilot and Scaffold Q+ software were used for iTRAQ-labeled samples, while Progenesis LC-MS and ProgenesisF-T2PQ/T3PQ were employed for label-free analyses. R² correlation coefficients correlated well between two software packages applied to the same datasets with values between 0.48 and 0.78 for iTRAQ-label-based quantitations and 0.5 and 0.86 for label-free quantitations. Analyses of label-free samples showed higher levels of protein up- or downregulation in comparison to iTRAQ-labeled samples. The concentration differences were further evaluated by Western blotting for four downregulated proteins. These data suggested that the label-free method was more accurate than the iTRAQ method.

Defining, comparing, and improving iTRAQ quantification in mass spectrometry proteomics data

The purpose of this study was to generate a basis for the decision of what protein quantities are reliable and find a way for accurate and precise protein quantification. To investigate this we have used thousands of peptide measurements to estimate variance and bias for quantification by iTRAQ (isobaric tags for relative and absolute quantification) mass spectrometry in complex human samples. A549 cell lysate was mixed in the proportions 2:2:1:1:2:2:1:1, fractionated by high resolution isoelectric focusing and liquid chromatography and analyzed by three mass spectrometry platforms; LTQ Orbitrap Velos, 4800 MALDI-TOF/TOF and 6530 Q-TOF. We have investigated how variance and bias in the iTRAQ reporter ions data are affected by common experimental variables such as sample amount, sample fractionation, fragmentation energy, and instrument platform. Based on this, we have suggested a concept for experimental design and a methodology for protein quantification. By using duplicate samples in each run, each experiment is validated based on its internal experimental variation. The duplicates are used for calculating peptide weights, unique to the experiment, which is used in the protein quantification. By weighting the peptides depending on reporter ion intensity, we can decrease the relative error in quantification at the protein level and assign a total weight to each protein that reflects the protein quantitation confidence. We also demonstrate the usability of this methodology in a cancer cell line experiment as well as in a clinical data set of lung cancer tissue samples. In conclusion, we have in this study developed a methodology for improved protein quantification in shotgun proteomics and introduced a way to assess quantification for proteins with few peptides. The experimental design and developed algorithms decreased the relative protein quantification error in the analysis of complex biological samples.

An adaptive alignment algorithm for quality-controlled label-free LC-MS

Label-free quantification using precursor-based intensities is a versatile workflow for large-scale proteomics studies. The method however requires extensive computational analysis and is therefore in need of robust quality control during the data mining stage. We present a new label-free data analysis workflow integrated into a multiuser software platform. A novel adaptive alignment algorithm has been developed to minimize the possible systematic bias introduced into the analysis. Parameters are estimated on the fly from the data at hand, producing a user-friendly analysis suite. Quality metrics are output in every step of the analysis as well as actively incorporated into the parameter estimation. We furthermore show the improvement of this system by comprehensive comparison to classical label-free analysis methodology as well as current state-of-the-art software.

Identification of protein biomarkers in human serum using iTRAQ and shotgun mass spectrometry

Blood serum is one of the easiest accessible sources of biomarkers and its proteome presents a significant parcel of immune system proteins. These proteins can provide not only biological explanation but also diagnostic and drug response answers independently of the type of disease or condition in question. Shotgun mass spectrometry has profoundly contributed to proteome analysis and is presently considered as an indispensible tool in the field of biomarker discovery. In addition, the multiplexing potential of isotopic labeling techniques such as iTRAQ can increase statistical relevance and accuracy of proteomic data through the simultaneous analysis of different biological samples. Here, we describe a complete protocol using iTRAQ in a shotgun proteomics workflow along with data analysis steps, customized for the challenges associated with the serum proteome.

Temperature modulation of fatty acid profiles for biofuel production in nitrogen deprived Chlamydomonas reinhardtii

This study investigated the changes in the fatty acid content and composition in the nitrogen-starved Chlamydomonas reinhardtii starchless mutant, BAF-J5, grown at different temperatures. The optimal temperature for vegetative growth under nitrogen sufficient conditions was found to be 32 °C. Shifting temperature from 25 to 32 °C, in conjunction with nitrogen starvation, resulted in BAF-J5 storing the maximum quantity of fatty acid (76% of dry cell weight). Shifting to temperatures lower than 25 °C, reduced the total amount of stored fatty acid content and increased the level of desaturation in the fatty acids. The optimal fatty acid composition for biodiesel was at 32 °C. This study demonstrates how a critical environmental factor, such as temperature, can modulate the amount and composition of fatty acids under nitrogen deprivation and reduce the requirement for costly refining of biofuels.