Exploiting Amino Acid Composition for Predicting Protein-Protein Interactions

Background

Computational prediction of protein interactions typically use protein domains as classifier features because they capture conserved information of interaction surfaces. However, approaches relying on domains as features cannot be applied to proteins without any domain information. In this paper, we explore the contribution of pure amino acid composition (AAC) for protein interaction prediction. This simple feature, which is based on normalized counts of single or pairs of amino acids, is applicable to proteins from any sequenced organism and can be used to compensate for the lack of domain information.

Results

AAC performed at par with protein interaction prediction based on domains on three yeast protein interaction datasets. Similar behavior was obtained using different classifiers, indicating that our results are a function of features and not of classifiers. In addition to yeast datasets, AAC performed comparably on worm and fly datasets. Prediction of interactions for the entire yeast proteome identified a large number of novel interactions, the majority of which co-localized or participated in the same processes. Our high confidence interaction network included both well-studied and uncharacterized proteins. Proteins with known function were involved in actin assembly and cell budding. Uncharacterized proteins interacted with proteins involved in reproduction and cell budding, thus providing putative biological roles for the uncharacterized proteins.

Conclusion

AAC is a simple, yet powerful feature for predicting protein interactions, and can be used alone or in conjunction with protein domains to predict new and validate existing interactions. More importantly, AAC alone performs at par with existing, but more complex, features indicating the presence of sequence-level information that is predictive of interaction, but which is not necessarily restricted to domains.     

Constitutive and Chloroplast Targeted Expression of Acetyl-CoA Carboxylase in Oleaginous Microalgae Elevates Fatty Acid Biosynthesis

Photosynthetic microalgae are of burgeoning interest in the generation of commercial bioproducts. Microalgae accumulate high lipid content under adverse conditions, which in turn compromise their growth and hinder their commercial potential. Hence, it is necessary to engineer microalgae to mitigate elevated lipid accumulation and biomass. In this study, we identified acetyl-CoA carboxylase (ACCase) in oleaginous microalga Phaeodactylum tricornutum (PtACC2) and expressed constitutively in the chloroplast to demonstrate the potential of chloroplast engineering. Molecular characterization of transplastomic microalgae revealed that PtACC2 was integrated, transcribed and expressed successfully, and localized in the chloroplast. Enzymatic activity of ACCase was elevated by 3.3-fold, and the relative neutral lipid content increased substantially by 1.77-fold, and lipid content reached up to 40.8% of dry weight. Accordingly, the number and size of oil bodies markedly increased. Fatty acid profiling showed that the content of monounsaturated fatty acids increased, while polyunsaturated fatty acids decreased. This method provides a valuable genetic engineering toolbox for microalgal bioreactors with industrial significance.     

海洋微藻脂肪酸去饱和酶

海洋微藻中富含多不饱和脂肪酸(polyunsaturated fatty acid,PUFA),在部分微藻中ω3 PUFA的量可达其总脂肪酸的30%～50%。而且微藻油具有鱼油所不可比拟的健康优势,也是唯一得到美国食品与药物管理局(FDA)认可的儿童DHA(二十二碳六烯酸)补充剂来源。由于用培养微藻来提取、纯化PUFA受到现有生产工艺的限制,使微藻油在国际食品(尤其是高质量食品)及保健品市场上供不应求。微藻脂肪酸去饱和酶(fatty aciddesaturase,FAD)是微藻PUFA合成的关键酶类,所以对微藻FAD的深入研究无疑将促进PUFA资源的合理开发和利用。     

Analysis of Fatty Acid Content and Composition in Microalgae

A method to determine the content and composition of total fatty acids present in microalgae is described. Fatty acids are a major constituent of microalgal biomass. These fatty acids can be present in different acyl-lipid classes. Especially the fatty acids present in triacylglycerol (TAG) are of commercial interest, because they can be used for production of transportation fuels, bulk chemicals, nutraceuticals (ω-3 fatty acids), and food commodities. To develop commercial applications, reliable analytical methods for quantification of fatty acid content and composition are needed. Microalgae are single cells surrounded by a rigid cell wall. A fatty acid analysis method should provide sufficient cell disruption to liberate all acyl lipids and the extraction procedure used should be able to extract all acyl lipid classes.With the method presented here all fatty acids present in microalgae can be accurately and reproducibly identified and quantified using small amounts of sample (5 mg) independent of their chain length, degree of unsaturation, or the lipid class they are part of.This method does not provide information about the relative abundance of different lipid classes, but can be extended to separate lipid classes from each other.The method is based on a sequence of mechanical cell disruption, solvent based lipid extraction, transesterification of fatty acids to fatty acid methyl esters (FAMEs), and quantification and identification of FAMEs using gas chromatography (GC-FID). A TAG internal standard (tripentadecanoin) is added prior to the analytical procedure to correct for losses during extraction and incomplete transesterification.     

Parallel Force Assay for Protein-Protein Interactions

Quantitative proteome research is greatly promoted by high-resolution parallel format assays. A characterization of protein complexes based on binding forces offers an unparalleled dynamic range and allows for the effective discrimination of non-specific interactions. Here we present a DNA-based Molecular Force Assay to quantify protein-protein interactions, namely the bond between different variants of GFP and GFP-binding nanobodies. We present different strategies to adjust the maximum sensitivity window of the assay by influencing the binding strength of the DNA reference duplexes. The binding of the nanobody Enhancer to the different GFP constructs is compared at high sensitivity of the assay. Whereas the binding strength to wild type and enhanced GFP are equal within experimental error, stronger binding to superfolder GFP is observed. This difference in binding strength is attributed to alterations in the amino acids that form contacts according to the crystal structure of the initial wild type GFP-Enhancer complex. Moreover, we outline the potential for large-scale parallelization of the assay.     

Manipulating membrane Fatty Acid compositions of whole plants with tween-Fatty Acid esters

This paper describes a method for manipulating plant membrane fatty acid compositions without altering growth temperature or other conditions. Tween-fatty acid esters carrying specific fatty acids were synthesized and applied to various organs of plants growing axenically in glass jars. Treated plants incorporated large amounts of exogenous fatty acids into all acylated membrane lipids detected. Fatty acids were taken up by both roots and leaves. Fatty acids applied to roots were found in leaves, while fatty acids applied to leaves appeared in both leaves higher on the plant and in roots, indicating translocation (probably in the phloem). Foliar application was most effective; up to 20% of membrane fatty acids of leaves above the treated leaf and up to 40% of root membrane fatty acids were exogenously derived. Plants which took up exogenous fatty acids changed their patterns of fatty acid synthesis such that ratios of saturated to unsaturated fatty acids remained essentially unaltered. Fatty acid uptake was most extensively studied in soybean (Glycine max [L.] Merr.), but was also observed in other species, including maize (Zea mays L.), mung beans (Vigna radiata L.), peas (Pisum sativum L.), petunia (Petunia hybrida L.) and tomato (Lycopersicon esculentum Mill.). Potential applications of this system include studying internal transport of fatty acids, regulation of fatty acid and membrane synthesis, and influences of membrane fatty acid composition on plant physiology.     

Evolution of Specificity in Protein-Protein Interactions

Hub proteins are proteins that maintain promiscuous molecular recognition. Because they are reported to play essential roles in cellular control, there has been a special interest in the study of their structural and functional properties, yet the mechanisms by which they evolve to maintain functional interactions are poorly understood. By combining biophysical simulations of coarse-grained proteins and analysis of proteins-complex crystallographic structures, we seek to elucidate those mechanisms. We focus on two types of hub proteins: Multi hubs, which interact with their partners through different interfaces, and Singlish hubs, which do so through a single interface. We show that loss of structural stability is required for the evolution of protein-protein-interaction (PPI) networks, and it is more profound in Singlish hub systems. In addition, different ratios of hydrophobic to electrostatic interfacial amino acids are shown to support distinct network topologies (i.e., Singlish and Multi systems), and therefore underlie a fundamental design principle of PPI in a crowded environment. We argue that the physical nature of hydrophobic and electrostatic interactions, in particular, their favoring of either same-type interactions (hydrophobic-hydrophobic), or opposite-type interactions (negatively-positively charged) plays a key role in maintaining the network topology while allowing the protein amino acid sequence to evolve.     

Evolution of Specificity in Protein-Protein Interactions

Hub proteins are proteins that maintain promiscuous molecular recognition. Because they are reported to play essential roles in cellular control, there has been a special interest in the study of their structural and functional properties, yet the mechanisms by which they evolve to maintain functional interactions are poorly understood. By combining biophysical simulations of coarse-grained proteins and analysis of proteins-complex crystallographic structures, we seek to elucidate those mechanisms. We focus on two types of hub proteins: Multi hubs, which interact with their partners through different interfaces, and Singlish hubs, which do so through a single interface. We show that loss of structural stability is required for the evolution of protein-protein-interaction (PPI) networks, and it is more profound in Singlish hub systems. In addition, different ratios of hydrophobic to electrostatic interfacial amino acids are shown to support distinct network topologies (i.e., Singlish and Multi systems), and therefore underlie a fundamental design principle of PPI in a crowded environment. We argue that the physical nature of hydrophobic and electrostatic interactions, in particular, their favoring of either same-type interactions (hydrophobic-hydrophobic), or opposite-type interactions (negatively-positively charged) plays a key role in maintaining the network topology while allowing the protein amino acid sequence to evolve.     

Mapping of a Locus for Unsaturated Fatty Acid Biosynthesis in Escherichia coli

A mutation affecting unsaturated fatty acid biosynthesis in Escherichia coli has been mapped. This mutation, which is in the fabB locus, lies between the aroC and purF loci.     

Current Large-Scale US Biofuel Potential from Microalgae Cultivated in Photobioreactors

Current assessments of the commercial viability and productivity potential of microalgae biofuels have been forced to extrapolate small-scale research data. The resulting analyses are not representative of microalgae cultivation and processing at industrial scale. To more accurately assess the current near-term realizable, large-scale microalgae productivity potential in the USA, this paper presents a model of microalgae growth derived from industrial-scale outdoor photobioreactor growth data. This model is combined with thermal models of the photobioreactor system and 15?years of hourly historical weather data from 864 locations in the USA to more accurately assess the current productivity potential of microalgae. The resulting lipid productivity potential of Nannochloropsis is presented in the form of a map that incorporates various land availability models to illustrate the near-term feasible cultivation locations and corresponding productivity potentials for the USA. The discussion focuses on a comparison of model results with productivity potentials currently reported in literature, an assessment demonstrating the scale of Department of Energy 2030 alternative fuel goals, and a critical comparison of productivity potential in several key regions of the USA.     

Predicting Pharmacodynamic Drug-Drug Interactions through Signaling Propagation Interference on Protein-Protein Interaction Networks

As pharmacodynamic drug-drug interactions (PD DDIs) could lead to severe adverse effects in patients, it is important to identify potential PD DDIs in drug development. The signaling starting from drug targets is propagated through protein-protein interaction (PPI) networks. PD DDIs could occur by close interference on the same targets or within the same pathways as well as distant interference through cross-talking pathways. However, most of the previous approaches have considered only close interference by measuring distances between drug targets or comparing target neighbors. We have applied a random walk with restart algorithm to simulate signaling propagation from drug targets in order to capture the possibility of their distant interference. Cross validation with DrugBank and Kyoto Encyclopedia of Genes and Genomes DRUG shows that the proposed method outperforms the previous methods significantly. We also provide a web service with which PD DDIs for drug pairs can be analyzed at http://biosoft.kaist.ac.kr/targetrw.     

Mapping of the fabA Locus for Unsaturated Fatty Acid Biosynthesis in Escherichia coli

fabA mutants of Escherichia coli require an appropriate unsaturated fatty acid for growth. The fabA locus has now been mapped at minute 21.5 of the linkage map of E. coli. The locus is cotransduced with pyrD and aroA but not with pyrC, purB, or pdxC. The clockwise order of markers in the region is pdxC, aroA, cmlB, pyrD, fabA, pyrC.     

How Structure Defines Affinity in Protein-Protein Interactions

Protein-protein interactions (PPI) in nature are conveyed by a multitude of binding modes involving various surfaces, secondary structure elements and intermolecular interactions. This diversity results in PPI binding affinities that span more than nine orders of magnitude. Several early studies attempted to correlate PPI binding affinities to various structure-derived features with limited success. The growing number of high-resolution structures, the appearance of more precise methods for measuring binding affinities and the development of new computational algorithms enable more thorough investigations in this direction. Here, we use a large dataset of PPI structures with the documented binding affinities to calculate a number of structure-based features that could potentially define binding energetics. We explore how well each calculated biophysical feature alone correlates with binding affinity and determine the features that could be used to distinguish between high-, medium- and low- affinity PPIs. Furthermore, we test how various combinations of features could be applied to predict binding affinity and observe a slow improvement in correlation as more features are incorporated into the equation. In addition, we observe a considerable improvement in predictions if we exclude from our analysis low-resolution and NMR structures, revealing the importance of capturing exact intermolecular interactions in our calculations. Our analysis should facilitate prediction of new interactions on the genome scale, better characterization of signaling networks and design of novel binding partners for various target proteins.     

A High-Throughput Fatty Acid Profiling Screen Reveals Novel Variations in Fatty Acid Biosynthesis in Chlamydomonas reinhardtii and Related Algae

Analysis of fatty acid methyl esters (FAMEs) by gas chromatography (GC) is a common technique for the quantitative and qualitative analysis of acyl lipids. Methods for FAME preparation are typically time-consuming and labor-intensive and require multiple transfers of reagents and products between reaction tubes and autosampler vials. In order to increase throughput and lower the time and materials costs required for FAME preparation prior to GC analysis, we have developed a method in which 10-to-20-mg samples of microbial biomass are transferred to standard GC autosampler vials, transesterified using an emulsion of methanolic trimethylsulfonium hydroxide and hexane, and analyzed directly by GC without further sample handling. This method gives results that are essentially identical to those obtained by the more labor- and material-intensive FAME preparation methods, such as transmethylation with methanolic HCl. We applied this method to the screening of laboratory and environmental isolates of the green alga Chlamydomonas for variations in fatty acid composition. This screening method facilitated two novel discoveries. First, we identified a common laboratory strain of C. reinhardtii, CC-620, completely lacking all ω-3 fatty acids normally found in this organism and showed that this strain contains an inactivating mutation in the CrFAD7 gene, encoding the sole ω-3 desaturase activity in this organism. Second, we showed that some species of Chlamydomonas make Δ6-unsaturated polyunsaturated fatty acids (PUFA) rather than the Δ5 species normally made by the previously characterized laboratory strains of Chlamydomonas, suggesting that there is species-specific variation in the regiospecificity and substrate selectivity of front-end desaturases in this algal genus.     

Evidence for Two Genes Specifically Involved in Unsaturated Fatty Acid Biosynthesis in Escherichia coli

Unsaturated fatty acid auxotrophs of Eschericha coli have been divided into two distinct cistrons by extract complementation and genetic complementation based on abortive transduction. Lesions in one cistron result in the loss of the beta-hydroxydecanoyl thioester dehydrase which produces the first biosynthetic intermediate in unsaturated fatty acid formation. Evidence is presented which indicates that lesions in the second cistron result in the lack of a second enzyme specifically involved in the biosynthesis of unsaturated fatty acids.     

Light-dependent Induction of Polyunsaturated Fatty Acid Biosynthesis in Greening Cucumber Cotyledons

Greening cucumber (Cucumis sativus L.) cotyledons exhibited dramatic increases in the ability to desaturate exogenously added [1-¹⁴C]oleic acid and [1-¹⁴C]linoleic acid within 2 to 3 hours of illumination. These increases were effectively inhibited by 10 micrograms per milliliter cycloheximide. Oleate desaturation remained at a high level in constant light for 5 to 6 days after induction and then declined by about 50%; when returned to the dark, the tissue showed a sharp decrease in conversion of [¹⁴C]oleate to [¹⁴C]linoleate. Linoleate desaturation reached a maximum about 15 hours after induction and declined immediately thereafter while the tissue still was in the light; after induction had peaked return of the tissue to the dark showed a dramatic fall of linoleate desaturation. The changes in desaturation were correlated with the conversion of the principal fatty acid in the etiolated cotyledons, linoleate, to α-linolenate, and with the assembly of the chlorophyll-containing photosynthetic membranes. The incorporation of [1-¹⁴C]acetate into lipids showed no significant light stimulation. The role of light in the regulation of certain aspects of plant metabolism during development is discussed.