Prediction of Subcellular Localization of Apoptosis Protein Using Chou’s Pseudo Amino Acid Composition

Apoptosis proteins play an essential role in regulating a balance between cell proliferation and death. The successful prediction of subcellular localization of apoptosis proteins directly from primary sequence is much benefited to understand programmed cell death and drug discovery. In this paper, by use of Chou’s pseudo amino acid composition (PseAAC), a total of 317 apoptosis proteins are predicted by support vector machine (SVM). The jackknife cross-validation is applied to test predictive capability of proposed method. The predictive results show that overall prediction accuracy is 91.1% which is higher than previous methods. Furthermore, another dataset containing 98 apoptosis proteins is examined by proposed method. The overall predicted successful rate is 92.9%.     

A Multilabel Model Based on Chou’s Pseudo–Amino Acid Composition for Identifying Membrane Proteins with Both Single and Multiple Functional Types

Predicting membrane protein type is a meaningful task because this kind of information is very useful to explain the function of membrane proteins. Due to the explosion of new protein sequences discovered, it is highly desired to develop efficient computation tools for quickly and accurately predicting the membrane type for a given protein sequence. Even though several membrane predictors have been developed, they can only deal with the membrane proteins which belong to the single membrane type. The fact is that there are membrane proteins belonging to two or more than two types. To solve this problem, a system for predicting membrane protein sequences with single or multiple types is proposed. Pseudo–amino acid composition, which has proven to be a very efficient tool in representing protein sequences, and a multilabel KNN algorithm are used to compose this prediction engine. The results of this initial study are encouraging.     

An Improved Method for the Fermentative Production of Coenzyme A from Pantothenic Acid,Cysteine, and 5′-AMP

The cultivation of Brevibacterium ammoniagenes IFO 12071 with pantothenic acid, cysteine, and 5′-adenylic acid gave coenzyme A in a high yield. The organism was stabilized by repeated single colony isolations. The culture conditions optimal for the production of coenzyme A were investigated, and the yield of coenzyme A in the culture broth reached more than 3 mg/ml.

The advantages and disadvantages of the present method were discussed by comparing them with our original dried cell method.     

Amino Acid Sequences and Distribution of High-Potential Iron–Sulfur Proteins That Donate Electrons to the Photosynthetic Reaction Center in Phototropic Proteobacteria

High-potential iron-sulfur protein (HiPIP) has recently been shown to function as a soluble mediator in photosynthetic electron transfer between the cytochrome bc1 complex and the reaction-center bacteriochlorophyll in some species of phototrophic proteobacteria, a role traditionally assigned to cytochrome c2. For those species that produce more than one high-potential electron carrier, it is unclear which protein functions in cyclic electron transfer and what characteristics determine reactivity. To establish how widespread the phenomenon of multiple electron donors might be, we have studied the electron transfer protein composition of a number of phototrophic proteobacterial species. Based upon the distribution of electron transfer proteins alone, we found that HiPIP is likely to be the electron carrier of choice in the purple sulfur bacteria in the families Chromatiaceae and Ectothiorhodospiraceae, but the majority of purple nonsulfur bacteria are likely to utilize cytochrome c2. We have identified several new species of phototrophic proteobacteria that may use HiPIP as electron donor and a few that may use cytochromes c other than c2. We have determined the amino acid sequences of 14 new HiPIPs and have compared their structures. There is a minimum of three sequence categories of HiPIP based upon major insertions and deletions which approximate the three families of phototrophic proteobacteria and each of them can be further subdivided prior to construction of a phylogenetic tree. The comparison of relationships based upon HiPIP and RNA revealed several discrepancies.     

Initial Amino Acid Intake Influences Phosphorus and Calcium Homeostasis in Preterm Infants – It Is Time to Change the Composition of the Early Parenteral Nutrition

Background

Early aggressive parenteral nutrition (PN), consisting of caloric and nitrogen intake soon after birth, is currently proposed for the premature baby. Some electrolyte disturbances, such as hypophosphatemia and hypercalcemia, considered unusual in early life, were recently described while using this PN approach. We hypothesize that, due to its impact on cell metabolism, the initial amino acid (AA) amount may specifically influence the metabolism of phosphorus, and consequently of calcium. We aim to evaluate the influence of AA intake on calcium-phosphorus metabolism, and to create a calculation tool to estimate phosphorus needs.

Methods

Prospective observational study. Phosphate and calcium plasma concentrations and calcium balance were evaluated daily during the first week of life in very preterm infants, and their relationship with nutrition was studied. For this purpose, infants were divided into three groups: high, medium and low AA intake (HAA, MAA, LAA). A calculation formula to assess phosphorus needs was elaborated, with a theoretical model based on AA and calcium intake, and the cumulative deficit of phosphate intake was estimated.

Results

154 infants were included. Hypophosphatemia (12.5%) and hypercalcemia (9.8%) were more frequent in the HAA than in the MAA (4.6% and 4.8%) and in the LAA group (0% and 1.9%); both p<0.001.

Discussion

Calcium-phosphorus homeostasis was influenced by the early AA intake. We propose to consider phosphorus and calcium imbalances as being part of a syndrome, related to incomplete provision of nutrients after the abrupt discontinuation of the placental nutrition at birth (PI-ReFeeding syndrome).We provide a simple tool to calculate the optimal phosphate intake. The early introduction of AA in the PN soon after birth might be completed by an early intake of phosphorus, since AA and phosphorus are (along with potassium) the main determinants of cellular growth.     

Projection of Young-Old and Old-Old with Functional Disability: Does Accounting for the Changing Educational Composition of the Elderly Population Make a Difference?

This study compares projections, up to year 2040, of young-old (aged 60-79) and old-old (aged 80+) with functional disability in Singapore with and without accounting for the changing educational composition of the Singaporean elderly. Two multi-state population models, with and without accounting for educational composition respectively, were developed, parameterized with age-gender-(education)-specific transition probabilities (between active, functional disability and death states) estimated from two waves (2009 and 2011) of a nationally representative survey of community-dwelling Singaporeans aged ≥60 years (N=4,990). Probabilistic sensitivity analysis with the bootstrap method was used to obtain the 95% confidence interval of the transition probabilities. Not accounting for educational composition overestimated the young-old with functional disability by 65 percent and underestimated the old-old by 20 percent in 2040. Accounting for educational composition, the proportion of old-old with functional disability increased from 40.8 percent in 2000 to 64.4 percent by 2040; not accounting for educational composition, the proportion in 2040 was 49.4 percent. Since the health profiles, and hence care needs, of the old-old differ from those of the young-old, health care service utilization and expenditure and the demand for formal and informal caregiving will be affected, impacting health and long-term care policy.     

iNSP-GCAAP: Identifying nonclassical secreted proteins using global composition of amino acid properties

Nonclassical secreted proteins (NSPs) refer to a group of proteins released into the extracellular environment under the facilitation of different biological transporting pathways apart from the Sec/Tat system. As experimental determination of NSPs is often costly and requires skilled handling techniques, computational approaches are necessary. In this study, we introduce iNSP-GCAAP, a computational prediction framework, to identify NSPs. We propose using global composition of a customized set of amino acid properties to encode sequence data and use the random forest (RF) algorithm for classification. We used the training dataset introduced by Zhang et al. (Bioinformatics, 36(3), 704–712, 2020) to develop our model and test it with the independent test set in the same study. The area under the receiver operating characteristic curve on that test set was 0.9256, which outperformed other state-of-the-art methods using the same datasets. Our framework is also deployed as a user-friendly web-based application to support the research community to predict NSPs.     

A machine learning based method for the prediction of secretory proteins using amino acid composition, their order and similarity-search

Most of the prediction methods for secretory proteins require the presence of a correct N-terminal end of the preprotein for correct classification. As large scale genome sequencing projects sometimes assign the 5'-end of genes incorrectly, many proteins are encoded without the correct N-terminus leading to incorrect prediction. In this study, a systematic attempt has been made to predict secretory proteins irrespective of presence or absence of N-terminal signal peptides (also known as classical and non-classical secreted proteins respectively), using machine-learning techniques; artificial neural network (ANN) and support vector machine (SVM). We trained and tested our methods on a dataset of 3321 secretory and 3654 non-secretory mammalian proteins using five-fold cross-validation technique. First, ANN-based modules have been developed for predicting secretory proteins using 33 physico-chemical properties, amino acid composition and dipeptide composition and achieved accuracies of 73.1%, 76.1% and 77.1%, respectively. Similarly, SVM-based modules using 33 physico-chemical properties, amino acid, and dipeptide composition have been able to achieve accuracies of 77.4%, 79.4% and 79.9%, respectively. In addition, BLAST and PSI-BLAST modules designed for predicting secretory proteins based on similarity search achieved 23.4% and 26.9% accuracy, respectively. Finally, we developed a hybrid-approach by integrating amino acid and dipeptide composition based SVM modules and PSI-BLAST module that increased the accuracy to 83.2%, which is significantly better than individual modules. We also achieved high sensitivity of 60.4% with low value of 5% false positive predictions using hybrid module. A web server SRTpred has been developed based on above study for predicting classical and non-classical secreted proteins from whole sequence of mammalian proteins, which is available from http://www.imtech.res.in/raghava/srtpred/.     

Protein subcellular localization prediction for Gram-negative bacteria using amino acid subalphabets and a combination of multiple support vector machines

Background  

Predicting the subcellular localization of proteins is important for determining the function of proteins. Previous works focused on predicting protein localization in Gram-negative bacteria obtained good results. However, these methods had relatively low accuracies for the localization of extracellular proteins. This paper studies ways to improve the accuracy for predicting extracellular localization in Gram-negative bacteria.     

利用伪氨基酸组分预测分枝杆菌膜蛋白类型

膜蛋白是重要的药物靶位点,对膜蛋白类型的研究有助于药物的成功设计,因此正确预测膜蛋白类型对于药物研发是十分必要的。本文采用由274条分枝杆菌膜蛋白序列组成的一致性小于40%的数据集,以经过优化的伪氨基酸组分为特征,利用支持向量机分类算法预测分枝杆菌膜蛋白类型,在Jackknife检验下,得到85.4%的总体准确率和72.2%的平均准确率。结果说明,该方法可用于分枝杆菌膜蛋白类型的识别,将有助于抗分枝杆菌药物的开发。     

革兰氏阴性菌血红素载体蛋白Hemophore的结构及作用机制

血红素作为宿主体内最丰富的铁离子来源,是致病菌营养竞争的主要目标,尤其对于血红素自身合成途径部分丧失的细菌。革兰氏阴性菌血红素转运系统由血红素载体蛋白(Hemophore)、外膜血红素受体、TonB-ExbB-ExbD复合物、ABC转运体等组成。Hemophore是存在于细菌细胞膜上或分泌到胞外环境中的一种蛋白。它能从宿主血红素结合蛋白中捕获血红素并将其传递给外膜受体。目前,在不同革兰氏阴性菌中已发现3种类型的Hemophore,分别是HasA、HxuA和HmuY型。本文将详细描述这3种Hemophore捕获血红素及与外膜受体相互作用的机制,以期为进一步研究其他细菌血红素载体蛋白的功能及作用机制奠定基础。     

SVM-based method for protein structural class prediction using secondary structural content and structural information of amino acids

The knowledge collated from the known protein structures has revealed that the proteins are usually folded into the four structural classes: all-α, all-β, α/β and α + β. A number of methods have been proposed to predict the protein's structural class from its primary structure; however, it has been observed that these methods fail or perform poorly in the cases of distantly related sequences. In this paper, we propose a new method for protein structural class prediction using low homology (twilight-zone) protein sequences dataset. Since protein structural class prediction is a typical classification problem, we have developed a Support Vector Machine (SVM)-based method for protein structural class prediction that uses features derived from the predicted secondary structure and predicted burial information of amino acid residues. The examination of different individual as well as feature combinations revealed that the combination of secondary structural content, secondary structural and solvent accessibility state frequencies of amino acids gave rise to the best leave-one-out cross-validation accuracy of ~81% which is comparable to the best accuracy reported in the literature so far.     

UPLC/MS based method for quantitative determination of fatty acid composition in Gram-negative and Gram-positive bacteria

Quantitative fatty acid composition of microorganisms at various growth space points is required for understanding membrane associated processes of cells, but the majority of the relevant publications still restrict to the relative compositions. In the current study, a simple and reliable method for quantitative measurement of fatty acid content in bacterial biomass without prior derivatization using ultra performance liquid chromatography-electrospray ionization mass spectrometry was developed. The method was applied for investigating the influence of specific growth rate and pH on the fatty acid profiles of two biotechnologically important microorganisms — Gram-negative bacteria Escherichia coli and Gram-positive bacteria Lactococcus lactis grown in controlled physiological states. It was found that the membranes of slowly growing cells are more rigid and that the fatty acid fraction of the cells of L. lactis diminishes considerably with increasing growth rate.     

Amino-terminal amino acid sequences of electron transfer proteins from Gram-negative bacteria as indicators of their cellular localization: the sulfate-reducing bacteria

Abstract Data are presented that all known periplasmic redox proteins from the sulfate reducing bacteria included in the genus, Desulfovibrio have aminoterminal (N-terminal) amino-acid sequences commonly found in other Gram-negative bacteria and are indicative of recognition sites for signal peptides. In contrast, none of the cytoplasmic redox proteins exhibited these unique N-terminal amino-acid sequences. It is proposed that the N-terminal amino-acid residues of a given protein can be used as an indicator of its cellular localization within the bacterial cell.     

A method for the identification of proteins secreted by lactic acid bacteria grown in complex media

Lactic acid bacteria (LAB) are known for their special nutritional requirements, being usually cultured in complex media to achieve optimal growth. In this paper, a protocol based on trichloroacetic acid precipitation of peptides and proteins is presented. The method has been tested on four probiotic LAB strains grown in De Man Rogosa Sharpe (MRS) broth, a complex medium that is often used for the culture of such bacteria. This protocol allowed the detection of 19 proteins after sodium dodecyl sulfate-polyacrylamide gel electrophoresis, 10 of them being successfully identified by tandem MS. Thereafter, the 10 were found to be secreted or surface associated by bioinformatic means. In conclusion, this work supplies a method for the identification of proteins secreted by LAB, allowing discrimination between the proteins present in the MRS and those produced by probiotic LAB.