The combined use of photoaffinity labeling and surface plasmon resonance‐based technology identifies multiple salicylic acid‐binding proteins

Salicylic acid (SA) is a small phenolic molecule that not only is the active ingredient in the multi‐functional drug aspirin, but also serves as a plant hormone that affects diverse processes during growth, development, responses to abiotic stresses and disease resistance. Although a number of SA‐binding proteins (SABPs) have been identified, the underlying mechanisms of action of SA remain largely unknown. Efforts to identify additional SA targets, and thereby elucidate the complex SA signaling network in plants, have been hindered by the lack of effective approaches. Here, we report two sensitive approaches that utilize SA analogs in conjunction with either a photoaffinity labeling technique or surface plasmon resonance‐based technology to identify and evaluate candidate SABPs from Arabidopsis. Using these approaches, multiple proteins, including the E2 subunit of α‐ketoglutarate dehydrogenase and the glutathione S‐transferases GSTF2, GSTF8, GSTF10 and GSTF11, were identified as SABPs. Their association with SA was further substantiated by the ability of SA to inhibit their enzymatic activity. The photoaffinity labeling and surface plasmon resonance‐based approaches appear to be more sensitive than the traditional approach for identifying plant SABPs using size‐exclusion chromatography with radiolabeled SA, as these proteins exhibited little to no SA‐binding activity in such an assay. The development of these approaches therefore complements conventional techniques and helps dissect the SA signaling network in plants, and may also help elucidate the mechanisms through which SA acts as a multi‐functional drug in mammalian systems.     

Imbalanced multi-modal multi-label learning for subcellular localization prediction of human proteins with both single and multiple sites

It is well known that an important step toward understanding the functions of a protein is to determine its subcellular location. Although numerous prediction algorithms have been developed, most of them typically focused on the proteins with only one location. In recent years, researchers have begun to pay attention to the subcellular localization prediction of the proteins with multiple sites. However, almost all the existing approaches have failed to take into account the correlations among the locations caused by the proteins with multiple sites, which may be the important information for improving the prediction accuracy of the proteins with multiple sites. In this paper, a new algorithm which can effectively exploit the correlations among the locations is proposed by using gaussian process model. Besides, the algorithm also can realize optimal linear combination of various feature extraction technologies and could be robust to the imbalanced data set. Experimental results on a human protein data set show that the proposed algorithm is valid and can achieve better performance than the existing approaches.     

Generalizing Double and Triple Sampling for Repeated Surveys and Partial Verification

Population composition is often estimated by double sampling in which the value of a covariate is noted on each of a large number of randomly selected units and the value of the covariate and the exact class to which the unit belongs is noted for a smaller sample. The cross‐classified sample can be used to estimate the classification rates and these, in turn, can be used in conjunction with the estimated distribution of the covariate to obtain an improved estimate of the population composition over that obtained by direct observation of the identity of the individuals in a small sample. There are two approaches to this problem characterized by the way in which the classification rates are defined. The simplest approach uses estimates of the probability P(i | j) that the unit is actually in class i given that the covariate is in class j. The more complicated approach uses estimates of the probability Pi | j) that the covariate falls in class j given that the unit is actually in class i. The latter approach involves estimating more parameters than the former but avoids the necessity for the two samples to be drawn from the same population. We show the two approaches can be combined when there are multiple surveys. For example, one might conduct a disease survey for several years; in each year the accurate and/or error‐prone techniques may be applied to samples. The sensitivities and specificities of the error‐prone test are assumed constant across surveys. Generalizations allow for more than one error‐prone classifier and partial verification (estimation of misclassification rates by application of the accurate technique to fixed subsamples from each error‐prone category). The general approach is illustrated by considering a repeated survey for malaria.     

Multi‐ATOM: Ultrahigh‐throughput single‐cell quantitative phase imaging with subcellular resolution

A growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost‐effective and label‐free cellular assays, which provides useful insights into understanding the biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single‐cell precision to define cell identities in a large and heterogeneous population of cells—hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multiplexed asymmetric‐detection time‐stretch optical microscopy (multi‐ATOM) that captures and processes quantitative label‐free single‐cell images at ultrahigh throughput without compromising subcellular resolution. We show that multi‐ATOM, based upon ultrafast phase‐gradient encoding, outperforms state‐of‐the‐art QPI in permitting robust phase retrieval at a QPI throughput of >10 000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi‐ATOM for large‐scale, label‐free, multivariate, cell‐type classification (e.g. breast cancer subtypes, and leukemic cells vs peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi‐ATOM could empower new strategies in large‐scale biophysical single‐cell analysis with applications in biology and enriching disease diagnostics.      

Palmitoylation of stathmin family proteins domain A controls Golgi versus mitochondrial subcellular targeting

Background information. Precise localization of proteins to specialized subcellular domains is fundamental for proper neuronal development and function. The neural microtubule‐regulatory phosphoproteins of the stathmin family are such proteins whose specific functions are controlled by subcellular localization. Whereas stathmin is cytosolic, SCG10, SCLIP and RB3/RB3′/RB3″ are localized to the Golgi and vesicle‐like structures along neurites and at growth cones. We examined the molecular determinants involved in the regulation of this specific subcellular localization in hippocampal neurons in culture. Results. We show that their conserved N‐terminal domain A carrying two palmitoylation sites is dominant over the others for Golgi and vesicle‐like localization. Using palmitoylation‐deficient GFP (green fluorescent protein) fusion mutants, we demonstrate that domains A of stathmin proteins have the particular ability to control protein targeting to either Golgi or mitochondria, depending on their palmitoylation. This regulation involves the co‐operation of two subdomains within domain A, and seems also to be under the control of its SLD (stathmin‐like domain) extension. Conclusions. Our results unravel that, in specific biological conditions, palmitoylation of stathmin proteins might be able to control their targeting to express their functional activities at appropriate subcellular sites. They, more generally, open new perspectives regarding the role of palmitoylation as a signalling mechanism orienting proteins to their functional subcellular compartments.     

Differential proteomic analysis using isotope‐coded protein‐labeling strategies: Comparison,improvements and application to simulated microgravity effect on Cupriavidus metallidurans CH34

Among differential proteomic methods based on stable isotopic labeling, isotope‐coded protein labeling (ICPL) is a recent non‐isobaric technique devised to label primary amines found in proteins. ICPL overcomes some of the disadvantages found in other chemical‐labeling techniques, such as iTRAQ or ICAT. However, previous analyses revealed that more than 30% of the proteins identified in regular ICPL generally remain unquantified. In this study, we describe a modified version of ICPL, named Post‐digest ICPL, that makes it possible to label and thus to quantify all the peptides in a sample (bottom–up approach). Optimization and validation of this Post‐digest ICPL approach were performed using a standard protein mixture and complex protein samples. Using this strategy, the number of proteins that were identified and quantified was greatly increased in comparison with regular ICPL and cICAT approaches. The pros and cons of this improvement are discussed. This complementary approach to traditional ICPL was applied to the analysis of modification of protein abundances in the model bacterium Cupriavidus metallidurans CH34 after cultivation under simulated microgravity. In this context, two different systems – a 2‐D clinorotation and 3‐D random positioning device – were used and the results were compared and discussed.     

Clustering of multi‐domain protein sequences

The overall function of a multi‐domain protein is determined by the functional and structural interplay of its constituent domains. Traditional sequence alignment‐based methods commonly utilize domain‐level information and provide classification only at the level of domains. Such methods are not capable of taking into account the contributions of other domains in the proteins, and domain‐linker regions and classify multi‐domain proteins. An alignment‐free protein sequence comparison tool, CLAP (CLAssification of Proteins) was previously developed in our laboratory to especially handle multi‐domain protein sequences without a requirement of defining domain boundaries and sequential order of domains. Through this method we aim to achieve a biologically meaningful classification scheme for multi‐domain protein sequences. In this article, CLAP‐based classification has been explored on 5 datasets of multi‐domain proteins and we present detailed analysis for proteins containing (1) Tyrosine phosphatase and (2) SH3 domain. At the domain‐level CLAP‐based classification scheme resulted in a clustering similar to that obtained from an alignment‐based method. CLAP‐based clusters obtained for full‐length datasets were shown to comprise of proteins with similar functions and domain architectures. Our study demonstrates that multi‐domain proteins could be classified effectively by considering full‐length sequences without a requirement of identification of domains in the sequence.     

Process cost and facility considerations in the selection of primary cell culture clarification technology

The bioreactor volume delineating the selection of primary clarification technology is not always easily defined. Development of a commercial scale process for the manufacture of therapeutic proteins requires scale‐up from a few liters to thousands of liters. While the separation techniques used for protein purification are largely conserved across scales, the separation techniques for primary cell culture clarification vary with scale. Process models were developed to compare monoclonal antibody production costs using two cell culture clarification technologies. One process model was created for cell culture clarification by disc stack centrifugation with depth filtration. A second process model was created for clarification by multi‐stage depth filtration. Analyses were performed to examine the influence of bioreactor volume, product titer, depth filter capacity, and facility utilization on overall operating costs. At bioreactor volumes <1,000 L, clarification using multi‐stage depth filtration offers cost savings compared to clarification using centrifugation. For bioreactor volumes >5,000 L, clarification using centrifugation followed by depth filtration offers significant cost savings. For bioreactor volumes of ～2,000 L, clarification costs are similar between depth filtration and centrifugation. At this scale, factors including facility utilization, available capital, ease of process development, implementation timelines, and process performance characterization play an important role in clarification technology selection. In the case study presented, a multi‐product facility selected multi‐stage depth filtration for cell culture clarification at the 500 and 2,000 L scales of operation. Facility implementation timelines, process development activities, equipment commissioning and validation, scale‐up effects, and process robustness are examined. © 2013 The Authors. American Institute of Chemical Engineers Biotechnol. Prog., 29:1239–1245, 2013     

Proteomic maps of subcellular protein fractions of the Asian citrus psyllid Diaphorina citri,the vector of citrus huanglongbing

The Asian citrus psyllid Diaphorina citri Kuwayama (Hemiptera: Liviidae) is an insect vector that transmits the bacterial pathogen Candidatus Liberibacter asiaticus (CLas) associated with the destructive citrus disease, citrus huanglongbing (HLB). Currently, D. citri is the major target in HLB management, although insecticidal control and disruption of the D. citri–CLas interactions both face numerous challenges. The present study reports the subcellular proteomic profiles of D. citri, encompassing the three main subcellular protein fractions: cytosol, mitochondria and microsomes. After optimization, subcellular proteins of both high and low abundance are obtained by two‐dimensional gel electrophoresis (2‐DE). A total of 1170 spots are detected in the 2‐DE gels of the three subcellular fractions. One hundred and sixty‐four differentially expressed proteins are successfully identified using liquid chromatography‐dual mass spectroscopy. An efficient protocol for subcellular protein fractionation from D. citri is established and a clear protein separation is achieved with the chosen protein fractionation protocol. The identified cytosolic proteins are mainly metabolic enzymes, whereas a large portion of the identified proteins in the mitochondrial and microsomal fractions are involved in ATP biosynthesis and protein metabolism, respectively. Protein–protein interaction networks are predicted for some identified proteins known to be implicated in pathogen–vector interactions, such as actin, tubulin and ATP synthase, as well as insecticide resistance, such as the cytochrome P450 superfamily. The findings should provide useful information to help identify the mechanism responsible for the CLas–D. citri interactions and eventually contribute to D. citri control.     

Resolving subcellular plant metabolism

Plant cells are characterized by a high degree of compartmentalization and a diverse proteome and metabolome. Only a very limited number of studies has addressed combined subcellular proteomics and metabolomics which strongly limits biochemical and physiological interpretation of large‐scale ’omics data. Our study presents a methodological combination of nonaqueous fractionation, shotgun proteomics, enzyme activities and metabolomics to reveal subcellular diurnal dynamics of plant metabolism. Subcellular marker protein sets were identified and enzymatically validated to resolve metabolism in a four‐compartment model comprising chloroplasts, cytosol, vacuole and mitochondria. These marker sets are now available for future studies that aim to monitor subcellular metabolome and proteome dynamics. Comparing subcellular dynamics in wild type plants and HXK1‐deficient gin2‐1 mutants revealed a strong impact of HXK1 activity on metabolome dynamics in multiple compartments. Glucose accumulation in the cytosol of gin2‐1 was accompanied by diminished vacuolar glucose levels. Subcellular dynamics of pyruvate, succinate and fumarate amounts were significantly affected in gin2‐1 and coincided with differential mitochondrial proteome dynamics. Lowered mitochondrial glycine and serine amounts in gin2‐1 together with reduced abundance of photorespiratory proteins indicated an effect of the gin2‐1 mutation on photorespiratory capacity. Our findings highlight the necessity to resolve plant metabolism to a subcellular level to provide a causal relationship between metabolites, proteins and metabolic pathway regulation.     

Vegetation mapping of the Great Fish River basin,South Africa: Integrating spatial and multi‐spectral remote sensing techniques

Abstract. We present a remote sensing based vegetation mapping technique well suited to a heterogeneous, semi‐arid environment. 10 structural vegetation classes were identified and described on the ground. Using Landsat‐TM from two different seasons and a combination of three conventional classification techniques (including a multi‐temporal classification) we were unsuccessful in delineating all of the desired vegetation classes. We then employed a simple tex‐tural classification index, known as the Moving Standard Deviation Index (MSDI), that has been used to map degradation status. MSDI measures spatial variations in the landscape and is calculated by passing a 3 × 3 standard deviation filter across the Landsat‐TM red band. High MSDI values are associated with degraded or disturbed rangelands whilst low MSDI values are associated with undisturbed rangeland. A combination of two conventional multi‐spectral techniques and MSDI were used to produce a final vegetation classification at an accuracy of 84 %. MSDI successfully discriminated between two contrasting vegetation types of identical spectral properties and significantly strengthened the accuracy of the classification. We recommend the use of a tex‐tural index such as MSDI to supplement conventional vegetation classification techniques in heterogeneous, semi‐arid or arid environments.     

Development of Beet necrotic yellow vein virus‐based vectors for multiple‐gene expression and guide RNA delivery in plant genome editing

Many plant viruses with monopartite or bipartite genomes have been developed as efficient expression vectors of foreign recombinant proteins. Nonetheless, due to lack of multiple insertion sites in these plant viruses, it is still a big challenge to simultaneously express multiple foreign proteins in single cells. The genome of Beet necrotic yellow vein virus (BNYVV) offers an attractive system for expression of multiple foreign proteins owning to a multipartite genome composed of five positive‐stranded RNAs. Here, we have established a BNYVV full‐length infectious cDNA clone under the control of the Cauliflower mosaic virus 35S promoter. We further developed a set of BNYVV‐based vectors that permit efficient expression of four recombinant proteins, including some large proteins with lengths up to 880 amino acids in the model plant Nicotiana benthamiana and native host sugar beet plants. These vectors can be used to investigate the subcellular co‐localization of multiple proteins in leaf, root and stem tissues of systemically infected plants. Moreover, the BNYVV‐based vectors were used to deliver NbPDS guide RNAs for genome editing in transgenic plants expressing Cas9, which induced a photobleached phenotype in systemically infected leaves. Collectively, the BNYVV‐based vectors will facilitate genomic research and expression of multiple proteins, in sugar beet and related crop plants.     

Misannotations of the genes encoding sugar N‐formyltransferases

Tens of thousands of bacterial genome sequences are now known due to the development of rapid and inexpensive sequencing technologies. An important key in utilizing these vast amounts of data in a biologically meaningful way is to infer the function of the proteins encoded in the genomes via bioinformatics techniques. Whereas these approaches are absolutely critical to the annotation of gene function, there are still issues of misidentifications, which must be experimentally corrected. For example, many of the bacterial DNA sequences encoding sugar N‐formyltransferases have been annotated as l ‐methionyl‐tRNA transferases in the databases. These mistakes may be due in part to the fact that until recently the structures and functions of these enzymes were not well known. Herein we describe the misannotation of two genes, WP_088211966.1 and WP_096244125.1, from Shewanella spp. and Pseudomonas congelans, respectively. Although the proteins encoded by these genes were originally suggested to function as l ‐methionyl‐tRNA transferases, we demonstrate that they actually catalyze the conversion of dTDP‐4‐amino‐4,6‐dideoxy‐d ‐glucose to dTDP‐4‐formamido‐4,6‐dideoxy‐d ‐glucose utilizing N¹⁰‐formyltetrahydrofolate as the carbon source. For this analysis, the genes encoding these enzymes were cloned and the corresponding proteins purified. X‐ray structures of the two proteins were determined to high resolution and kinetic analyses were conducted. Both enzymes display classical Michaelis–Menten kinetics and adopt the characteristic three‐dimensional structural fold previously observed for other sugar N‐formyltransferases. The results presented herein will aid in the future annotation of these fascinating enzymes.     

A versatile vector for mycobacterial protein production with a functional minimized acetamidase regulon

Recombinant protein expression is a prerequisite for diverse investigations of proteins at the molecular level. For targets from Mycobacterium tuberculosis it is favorable to use M. smegmatis as an expression host, a species from the same genus. In the respective shuttle vectors, target gene expression is controlled by the complex tetra‐cistronic acetamidase regulon. As a result, the size of those vectors is large, rendering them of limited use, especially when the target proteins are expressed from multi‐cistronic operons. Therefore, in the current work we present a versatile new expression vector in which the acetamidase regulon has been minimized by deleting the two genes amiD and amiS. We assessed the functional properties of the resulting vector pMyCA and compared it with those of the existing vector pMyNT that contains the full‐length acetamidase regulon. We analyzed the growth features and protein expression patterns of M. smegmatis cultures transformed with both vectors. In addition, we created mCherry expression constructs to spectroscopically monitor the expression properties of both vectors. Our experiments showed that the minimized vector exhibited several advantages over the pMyNT vector. First, the overall yield of expressed protein is higher due to the higher yield of bacterial mass. Second, the heterologous expression was regulated more tightly, offering an expression tool for diverse target proteins. Third, it is suitable for large multi‐protein complexes that are expressed from multi‐cistronic operons. Additionally, our results propose a new understanding of the regulation mechanism of the acetamidase regulon with the potential to construct more optimized vectors in the future.     

Benchmarking sample preparation/digestion protocols reveals tube‐gel being a fast and repeatable method for quantitative proteomics

Sample preparation, typically by in‐solution or in‐gel approaches, has a strong influence on the accuracy and robustness of quantitative proteomics workflows. The major benefit of in‐gel procedures is their compatibility with detergents (such as SDS) for protein solubilization. However, SDS‐PAGE is a time‐consuming approach. Tube‐gel (TG) preparation circumvents this drawback as it involves directly trapping the sample in a polyacrylamide gel matrix without electrophoresis. We report here the first global label‐free quantitative comparison between TG, stacking gel (SG), and basic liquid digestion (LD). A series of UPS1 standard mixtures (at 0.5, 1, 2.5, 5, 10, and 25 fmol) were spiked in a complex yeast lysate background. TG preparation allowed more yeast proteins to be identified than did the SG and LD approaches, with mean numbers of 1979, 1788, and 1323 proteins identified, respectively. Furthermore, the TG method proved equivalent to SG and superior to LD in terms of the repeatability of the subsequent experiments, with mean CV for yeast protein label‐free quantifications of 7, 9, and 10%. Finally, known variant UPS1 proteins were successfully detected in the TG‐prepared sample within a complex background with high sensitivity. All the data from this study are accessible on ProteomeXchange (PXD003841).     

Comprehensive analysis of the Brassica juncea root proteome in response to cadmium exposure by complementary proteomic approaches

Indian mustard (Brassica juncea L.) is known to both accumulate and tolerate high levels of heavy metals from polluted soils. To gain a comprehensive understanding of the effect of cadmium (Cd) treatment on B. juncea roots, two quantitative proteomics approaches – fluorescence two‐dimensional difference gel electrophoresis (2‐D DIGE) and multiplexed isobaric tagging technology (iTRAQ) – were implemented. Several proteins involved in sulfur assimilation, redox homeostasis, and xenobiotic detoxification were found to be up‐regulated. Multiple proteins involved in protein synthesis and processing were down‐regulated. While the two proteomics approaches identified different sets of proteins, the proteins identified in both datasets are involved in similar biological processes. We show that 2‐D DIGE and iTRAQ results are complementary, that the data obtained independently using the two techniques validate one another, and that the quality of iTRAQ results depends on both the number of biological replicates and the number of sample injections. This study determined the involvement of enzymes such as peptide methionine sulfoxide reductase and 2‐nitropropane dioxygenase in alternatives redox‐regulation mechanisms, as well as O‐acetylserine sulfhydrylase, glutathione‐S‐transferase and glutathione‐conjugate membrane transporter, as essential players in the Cd hyperaccumation and tolerance of B. juncea.     

Predicting Viral Protein Subcellular Localization with Chou's Pseudo Amino Acid Composition and Imbalance-Weighted Multi-Label K-Nearest Neighbor Algorithm

Machine learning is a kind of reliable technology for automated subcellular localization of viral proteins within a host cell or virus-infected cell. One challenge is that the viral protein samples are not only with multiple location sites, but also class-imbalanced. The imbalanced dataset often decreases the prediction performance. In order to accomplish this challenge, this paper proposes a novel approach named imbalance-weighted multi-label K-nearest neighbor to predict viral protein subcellular location with multiple sites. The experimental results by jackknife test indicate that the presented algorithm achieves a better performance than the existing methods and has great potentials in protein science.     

Dual fluorescent protein reporters for studying cell behaviors in vivo

Fluorescent proteins (FPs) are useful tools for visualizing live cells and their behaviors. Protein domains that mediate subcellular localization have been fused to FPs to highlight cellular structures. FPs fused with histone H2B incorporate into chromatin allowing visualization of nuclear events. FPs fused to a glycosylphosphatidylinositol anchor signal sequence label the plasma membrane, highlighting cellular shape. Thus, a reporter gene containing both types of FP fusions would allow for effective monitoring of cell shape, movement, mitotic stage, apoptosis, and other cellular activities. Here, we report a binary color‐coding system using four differently colored FP reporters that generates 16 distinct color codes to label the nuclei and plasma membranes of live cells in culture and in transgenic mice. As an initial test of this system in vivo, the promoter of the human Ubiquitin C (UBC) gene was used to widely express one of the color‐code reporters. Widespread expression of the reporter was attained in embryos; however, both male and female transgenic mice were infertile. In contrast, the promoter of the mouse Oct4/Pou5f1 gene linked to two different color‐code reporters specifically labeled blastocysts, primordial germ cells, and postnatal germ cells, and these mice were fertile. Time‐lapse movies of fluorescently‐labeled primordial germs cells demonstrate the utility of the color‐code system to visualize cell behaviors. This set of new FP reporters should be a useful tool for labeling distinct cell populations and studying their behaviors in complex tissues in vivo. genesis 47:708–717, 2009. © 2009 Wiley‐Liss, Inc.