Reduced Amino Acid Research Articles

The Tryptophan-Induced tnaC Ribosome Stalling Sequence Exposes High Amino Acid Cross-Talk That Can Be Mitigated by Removal of NusB for Higher Orthogonality.

A growing number of engineered synthetic circuits have employed biological parts coupling transcription and translation in bacterial systems to control downstream gene expression. One such example, the leader sequence of the tryptophanase (tna) operon, is a transcription-translation system commonly employed as an l-tryptophan inducible circuit controlled by ribosome stalling. While induction of the tna operon has been well-characterized in response to l-tryptophan, cross-talk of this modular component with other metabolites in the cell, such as other naturally occurring amino acids, has been less explored. In this study, we investigated the impact of natural metabolites and E.coli host factors on induction of the tna leader sequence. To do so, we constructed and biochemically validated an experimental assay using the tna operon leader sequence to assess differential regulation of transcription elongation and translation in response to l-tryptophan. Operon induction was then assessed following addition of each of the 20 naturally occurring amino acids to discover that several additional amino acids (e.g., l-alanine, l-cysteine, l-glycine, l-methionine, and l-threonine) also induce expression of the tna leader sequence. Following characterization of dose-dependent induction by l-cysteine relative to l-tryptophan, the effect on induction by single gene knockouts of protein factors associated with transcription and/or translation were interrogated. Our results implicate the endogenous cellular protein, NusB, as an important factor associated with induction of the operon by the alternative amino acids. As such, removal of the nusB gene from strains intended for tryptophan-sensing utilizing the tna leader region reduces amino acid cross-talk, resulting in enhanced orthogonal control of this commonly used synthetic system.

Characterization of iron reducibility of soy protein amyloid fibrils and their applications in iron fortification

Iron deficiency is a common nutritional disorder worldwide. Iron fortification of food is an effective strategy to control iron deficiency anemia (IDA), however, traditional iron fortificants usually provoke undesirable organoleptic changes or have limited colloid stability. In this research, we investigated iron reducibility of soy protein amyloid fibrils made from soy protein isolates (SPI), soy β-conglycinin (7S) and soy glycinin (11S), and explored their applications in iron fortification. All three protein fibrils showed iron reducibility. The reducibility was utilized to generate fibril-iron nanoparticle composites. The iron reducibility was affected by fibril concentration, degree of fibrillation and reducing amino acid composition. We identified 11S had the most significant effect on reducing Fe (III) to more bioavailable Fe (II) state, whereas 7S showed the optimal result for generation of iron nanoparticle on fibrils in situ. The resulted fibril-iron nanoparticle hybrids showed high dispersibility in various liquid foods, without distinct color change.

Characterization and Prediction of Presynaptic and Postsynaptic Neurotoxins Based on Reduced Amino Acids and Biological Properties

Background: Presynaptic and postsynaptic neurotoxins are two important neurotoxins. Due to the important role of presynaptic and postsynaptic neurotoxins in pharmacology and neuroscience, identification of them becomes very important in biology. Method: In this study, the statistical test and F-score were used to calculate the difference between amino acids and biological properties. The support vector machine was used to predict the presynaptic and postsynaptic neurotoxins by using the reduced amino acid alphabet types. Results: By using the reduced amino acid alphabet as the input parameters of support vector machine, the overall accuracy of our classifier had increased to 91.07%, which was the highest overall accuracy in this study. When compared with the other published methods, better predictive results were obtained by our classifier. Conclusion: In summary, we analyzed the differences between two neurotoxins in amino acids and biological properties, and constructed a classifier that could predict these two neurotoxins by using the reduced amino acid alphabet.

DeepRTCP: Predicting ATP-Binding Cassette Transporters Based on 1-Dimensional Convolutional Network.

ATP-binding cassette (ABC) transporters can promote cells to absorb nutrients and excrete harmful substances. It plays a vital role in the transmembrane transport of macromolecules. Therefore, the identification of ABC transporters is of great significance for the biological research. This paper will introduce a novel method called DeepRTCP. DeepRTCP uses the deep convolutional neural network and a feature combined of reduced amino acid alphabet based tripeptide composition and PSSM to recognize ABC transporters. We constructed a dataset named ABC_2020. It contains the latest ABC transporters downloaded from Uniprot. We performed 10-fold cross-validation on DeepRTCP, and the average accuracy of DeepRTCP was 95.96%. Compared with the start-of-the-art method for predicting ABC transporters, DeepRTCP improved the accuracy by 9.29%. It is anticipated that DeepRTCP can be used as an effective ABC transporter classifier which provides a reliable guidance for the research of ABC transporters.

IHEC_RAAC: a online platform for identifying human enzyme classes via reduced amino acid cluster strategy

Enzymes have been proven to play considerable roles in disease diagnosis and biological functions. The feature extraction that truly reflects the intrinsic properties of protein is the most critical step for the automatic identification of enzymes. Although lots of feature extraction methods have been proposed, some challenges remain. In this study, we developed a predictor called IHEC_RAAC, which has the capability to identify whether a protein is a human enzyme and distinguish the function of the human enzyme. To improve the feature representation ability, protein sequences were encoded by a new feature-vector called 'reduced amino acid cluster'. We calculated 673 amino acid reduction alphabets to determine the optimal feature representative scheme. The tenfold cross-validation test showed that the accuracy of IHEC_RAAC to identify human enzymes was 74.66% and further discriminate the human enzyme classes with an accuracy of 54.78%, which was 2.06% and 8.68% higher than the state-of-the-art predictors, respectively. Additionally, the results from the independent dataset indicated that IHEC_RAAC can effectively predict human enzymes and human enzyme classes to further provide guidance for protein research. A user-friendly web server, IHEC_RAAC, is freely accessible at http://bioinfor.imu.edu.cn/ihecraac .

Placental trophoblast syncytialization potentiates macropinocytosis via mTOR signaling to adapt to reduced amino acid supply

During pregnancy, the appropriate allocation of nutrients between the mother and the fetus is dominated by maternal-fetal interactions, which is primarily governed by the placenta. The syncytiotrophoblast (STB) lining at the outer surface of the placental villi is directly bathed in maternal blood and controls feto-maternal exchange. The STB is the largest multinucleated cell type in the human body, and is formed through syncytialization of the mononucleated cytotrophoblast. However, the physiological advantage of forming such an extensively multinucleated cellular structure remains poorly understood. Here, we discover that the STB uniquely adapts to nutrient stress by inducing the macropinocytosis machinery through repression of mammalian target of rapamycin (mTOR) signaling. In primary human trophoblasts and in trophoblast cell lines, differentiation toward a syncytium triggers macropinocytosis, which is greatly enhanced during amino acid shortage, induced by inhibiting mTOR signaling. Moreover, inhibiting mTOR in pregnant mice markedly stimulates macropinocytosis in the syncytium. Blocking macropinocytosis worsens the phenotypes of fetal growth restriction caused by mTOR-inhibition. Consistently, placentas derived from fetal growth restriction patients display: 1) Repressed mTOR signaling, 2) increased syncytialization, and 3) enhanced macropinocytosis. Together, our findings suggest that the unique ability of STB to undergo macropinocytosis serves as an essential adaptation to the cellular nutrient status, and support fetal survival and growth under nutrient deprivation.

JPH203 as a potential L-Type Amino Acid Transporter 1 (LAT 1) inhibitor in the development of cancer theragnostic compounds

Background: Cancer has become a major cause of global health problems. Latest research currently focuses on an approach to cancer therapy that involves specific target molecules and theragnostic (therapy and diagnostic) agents. Among the specific target molecules in cancer therapy is LAT1, which is over expressed in cancer cells but under expressed in normal cells. Therefore, LAT1 inhibition can become an alternative to cancer therapy. A number of studies have shown that JPH203 specifically inhibits LAT1, thus reducing amino acid absorption into cancer cells and inhibiting cancer cell growth. Objective: The main objective of this literature study was to determine the potential of JPH203 as a LAT1 inhibitor to be developed into a novel theragnostic agent for cancer. Methods: Various studies were summarized to outline the development of JPH203 as a therapy targeting LAT1 and potential candidate of theragnostic compounds. Results: The results of the literature study showed that JPH203 as a selective LAT1 inhibitor was able to efficiently suppress the growth of cancer cells with a low IC50 value. Conclusion: The activity of LAT1 as an amino acid transporter of cancer cells could be selectively inhibited by JPH203, thereby allowing JPH203 to be reconsidered as a potential therapy in the development of theragnostic compounds against cancer. Keywords: JPH203, theragnostic, LAT1 inhibitor

Amino acids profile of loofah gourd Luffa cylindrica (M J Roem) seeds subjected to different heat processing methods

The major limiting factor to the utilisation of loofah gourd seeds (LGS) as food is its high content of anti-nutrient. Heat processing is one of the process of reducing the concentration of anti-nutrients in food resources which may adversely influence the amino acids contents of such resources. Raw seeds of loofah gourds (RLGS) were toasted (TLGS), boiled (BLGS) and cooked (CGLS) and analysed for the amino acids content. The amino acids score, the essential amino acids score and the predicted (P-PER) of the raw and heat treated RLGS were calculated using standard equations. Results revealed that heat treatment significantly reduced (P<0.05) the essential amino acids, total sulphur containing amino acids and total basic amino acids while significantly (P<0.05) increasing the total amino acids, and total non-essential amino acids. cysteine is the most reduced amino acids and toasting had the highest reduction effect on the amino acids. P-PER of LGS were significantly enhanced by heat processing. Glutamic acid and aspartic acid were the most abundant amino acids while cysteine and methionine were the major limiting amino acids in the raw and processed LGS. In conclusion, heat processing enhances the nutritional potentials of LGS and wet heat processing boiling and cooking are the most preferred processing methods for loofah gourd seed.

Deep-AntiFP: Prediction of antifungal peptides using distanct multi-informative features incorporating with deep neural networks

World widely, Fungal infections have become a serious issue for human beings. Fungal infections normally happen once invading fungus appear on a specific area of the body and become difficult for the human immune system to control. Current antifungal based therapies and drugs are deemed unsatisfactory due to their harmful side effects. Due to the rapid increase of this toxic disease in the human body, accurate identification of AFPs has become a challenging task for the researchers. Measuring the effectiveness of AFPs on the human body, a reliable intelligent model is highly indispensable for the accurate identification of Antifungal Peptides. In this study, high discriminative numerical descriptors are extracted from peptide sequences using composite physiochemical properties, quasi sequence order, and reduce amino acid alphabet. Furthermore, a multi-information fusion approach is also utilized for compensating the weakness of individual feature spaces. Finally, several classification learning methods are applied to choose a suitable operational engine for our model. After evaluating the empirical results, deep neural networks with hyper-parameter optimal values achieved an accuracy of 94.23%, 91.02%, and 89.08% using the training, alternate and independent dataset, respectively. It was found that our proposed “Deep-AntiFP” outperformed and reported the highest performance than the existing computational models. It is expected that the developed model may be played a useful role in research academia as well as proteomics and drug development. The source code and all datasets are publicly available at https://github.com/shahidawkum/Deep-AntiFP.

Whole-Genome Transcriptome Analyses of Native Symbionts Reveal Host Coral Genomic Novelties for Establishing Coral-Algae Symbioses.

Reef-building corals and photosynthetic, endosymbiotic algae of the family Symbiodiniaceae establish mutualistic relationships that are fundamental to coral biology, enabling coral reefs to support a vast diversity of marine species. Although numerous types of Symbiodiniaceae occur in coral reef environments, Acropora corals select specific types in early life stages. In order to study molecular mechanisms of coral–algal symbioses occurring in nature, we performed whole-genome transcriptomic analyses of Acropora tenuis larvae inoculated with Symbiodinium microadriaticum strains isolated from an Acropora recruit. In order to identify genes specifically involved in symbioses with native symbionts in early life stages, we also investigated transcriptomic responses of Acropora larvae exposed to closely related, nonsymbiotic, and occasionally symbiotic Symbiodinium strains. We found that the number of differentially expressed genes was largest when larvae acquired native symbionts. Repertoires of differentially expressed genes indicated that corals reduced amino acid, sugar, and lipid metabolism, such that metabolic enzymes performing these functions were derived primarily from S. microadriaticum rather than from A. tenuis. Upregulated gene expression of transporters for those metabolites occurred only when coral larvae acquired their natural symbionts, suggesting active utilization of native symbionts by host corals. We also discovered that in Acropora, genes for sugar and amino acid transporters, prosaposin-like, and Notch ligand-like, were upregulated only in response to native symbionts, and included tandemly duplicated genes. Gene duplications in coral genomes may have been essential to establish genomic novelties for coral–algae symbiosis.

Coordinate Regulation of Ribosome and tRNA Biogenesis Controls Hypoxic Injury and Translation

The translation machinery is composed of a myriad of proteins and RNAs whose levels must be coordinated to efficiently produce proteins without wasting energy or substrate. However, protein synthesis is clearly not always perfectly tuned to its environment, as disruption of translation machinery components can lengthen lifespan and stress survival. While much has been learned from bacteria and yeast about translational regulation, much less is known in metazoans. In a screen for mutations protecting C.elegans from hypoxic stress, we isolated multiple genes impacting protein synthesis: a ribosomal RNA helicase gene, tRNA biosynthesis genes, and a gene controlling amino acid availability. To define better the mechanisms by which these genes impact protein synthesis, we performed a second screen for suppressors of the conditional developmental arrest phenotype of the RNA helicase mutant and identified genes involved in ribosome biogenesis. Surprisingly, these suppressor mutations restored normal hypoxic sensitivity and protein synthesis to the tRNA biogenesis mutants, but not to the mutant reducing amino acid uptake. Proteomic analysis demonstrated that reduced tRNA biosynthetic activity produces a selective homeostatic reduction in ribosomal subunits, thereby offering a mechanism for the suppression results. Our study uncovers an unrecognized higher-order-translation regulatory mechanism in a metazoan whereby ribosome biogenesis genes communicate with genes controlling tRNA abundance matching the global rate of protein synthesis with available resources.

Exclusive enteral nutrition mediates gut microbial and metabolic changes that are associated with remission in children with Crohn\u2019s disease

A nutritional intervention, exclusive enteral nutrition (EEN) can induce remission in patients with pediatric Crohn’s disease (CD). We characterized changes in the fecal microbiota and metabolome to identify the mechanism of EEN. Feces of 43 children were collected prior, during and after EEN. Microbiota and metabolites were analyzed by 16S rRNA gene amplicon sequencing and NMR. Selected metabolites were evaluated in relevant model systems. Microbiota and metabolome of patients with CD and controls were different at all time points. Amino acids, primary bile salts, trimethylamine and cadaverine were elevated in patients with CD. Microbiota and metabolome differed between responders and non-responders prior to EEN. EEN decreased microbiota diversity and reduced amino acids, trimethylamine and cadaverine towards control levels. Patients with CD had reduced microbial metabolism of bile acids that partially normalized during EEN. Trimethylamine and cadaverine inhibited intestinal cell growth. TMA and cadaverine inhibited LPS-stimulated TNF-alpha and IL-6 secretion by primary human monocytes. A diet rich in free amino acids worsened inflammation in the DSS model of intestinal inflammation. Trimethylamine, cadaverine, bile salts and amino acids could play a role in the mechanism by which EEN induces remission. Prior to EEN, microbiota and metabolome are different between responders and non-responders.

Integrin-associated ILK and PINCH1 protein content are reduced in skeletal muscle of maintenance haemodialysis patients.

Patients with renal failure undergoing maintenance haemodialysis are associated with insulin resistance and protein metabolism dysfunction. Novel research suggests that disruption to the transmembrane protein linkage between the cytoskeleton and the extracellular matrix in skeletal muscle may contribute to reduced amino acid metabolism and insulin resistance in haemodialysis. ILK, PINCH1 and pFAKTyr397 were significantly decreased in haemodialysis compared to controls, whereas Rac1 and Akt2showed no different between groups. Rac1 deletion in the Rac1 knockout model did not alter the expression of integrin-associated proteins. Phenylalanine kinetics were reduced in the haemodialysis group at 30 and 60min post meal ingestion compared to controls; both groups showed similar levels of insulin sensitivity and β-cell function. Key proteins in the integrin-cytoskeleton linkage are reduced in haemodialysis patients, suggesting for the first time that integrin-associated proteins dysfunction may contribute to reduced phenylalanine flux without affecting insulin resistance in haemodialysis patients. Muscle atrophy, insulin resistance and reduced muscle phosphoinositide 3-kinase-Akt signalling are common characteristics of patients undergoing maintenance haemodialysis (MHD). Disruption to the transmembrane protein linkage between the cytoskeleton and the extracellular matrix in skeletal muscle may contribute to reduced amino acid metabolism and insulin resistance in MHD patients. Eight MHD patients (age: 56±5years: body mass index: 32±2kgm-2 ) and non-diseased controls (age: 50±2years: body mass index: 31±1kgm-2 ) received primed continuous l-[ring-2 H5 ]phenylalanine before consuming a mixed meal. Phenylalanine metabolism was determined using two-compartment modelling. Muscle biopsies were collected prior to the meal and at 300min postprandially. In a separate experiment, skeletal muscle tissue from muscle-specific Rac1 knockout (Rac1mKO) was harvested to investigate whether Rac1 depletion disrupted the cytoskeleton-integrin linkage, allowing for cross-model examination of proteins of interest. ILK, PINCH1 and pFAKTyr397 were significantly lower in MHD (P<0.01). Rac1 and Akt showed no difference between groups for the human trial. Rac1 deletion in the Rac1mKO model did not alter the expression of integrin-associated proteins. Phenylalanine rates of appearance and disappearance, as well as metabolic clearance rates, were lower in the MHD group at 30 and 60min post meal ingestion compared to controls (P<0.05). Both groups showed similar levels of insulin sensitivity and β-cell function. Key proteins in the integrin-cytoskeleton linkage are reduced in MHD patients, suggesting for the first time that integrin-associated proteins dysfunction may contribute to reduced phenylalanine flux without affecting insulin resistance in haemodialysis patients.

ISP-RAAC: Identify Secretory Proteins of Malaria Parasite Using Reduced Amino Acid Composition.

As the pathogen of malaria, malaria parasite secretes a variety of proteins for its growth and reproduction. The identification of the secretory proteins of malaria parasite has crucial reference significance for the development of anti-malaria vaccines as well as medicine. In this study, a computational classification method was developed to identify the secreted proteins of Plasmodium. Amino acid composition, dipeptide composition, and tripeptide composition as well as reduced amino acids alphabets were proposed to illuminate protein sequences. We further used SVM to train and predict respectively and optimized the features. 74 types of reduced amino acids alphabets were employed to predict secretory proteins. The results showed that the accuracy improved to 91.67% with 0.84 Mathew's correlation coefficient (MCC) by dipeptide composition, and the highest prediction accuracy reached 92.26% after feature selection, which demonstrated that our method is prominent and reliable in the field of malaria parasite secreted proteins prediction. A intuitive web server iSP-RAAC (http://bioinfor.imu.edu.cn/isppseraac) was established for the convenience of most experimental scientists.

ICTC-RAAC: An improved web predictor for identifying the types of ion channel-targeted conotoxins by using reduced amino acid cluster descriptors

Conotoxins are small peptide toxins which are rich in disulfide and have the unique diversity of sequences. It is significant to correctly identify the types of ion channel-targeted conotoxins because that they are considered as the optimal pharmacological candidate medicine in drug design owing to their ability specifically binding to ion channels and interfering with neural transmission. Comparing with other feature extracting methods, the reduced amino acid cluster (RAAC) better resolved in simplifying protein complexity and identifying functional conserved regions. Thus, in our study, 673 RAACs generated from 74 types of reduced amino acid alphabet were comprehensively assessed to establish a state-of-the-art predictor for predicting ion channel-targeted conotoxins. The results showed Type 20, Cluster 9 (T = 20, C = 9) in the tripeptide composition (N = 3) achieved the best accuracy, 89.3%, which was based on the algorithm of amino acids reduction of variance maximization. Further, the ANOVA with incremental feature selection (IFS) was used for feature selection to improve prediction performance. Finally, the cross-validation results showed that the best overall accuracy we calculated was 96.4% and 1.8% higher than the best accuracy of previous studies. Based on the predictor we proposed, a user-friendly webserver was established and can be friendly accessed at http://bioinfor.imu.edu.cn/ictcraac.

CnnAlpha: Protein disordered regions prediction by reduced amino acid alphabets and convolutional neural networks.

Intrinsically disordered regions (IDR) play an important role in key biological processes and are closely related to human diseases. IDRs have great potential to serve as targets for drug discovery, most notably in disordered binding regions. Accurate prediction of IDRs is challenging because their genome wide occurrence and a low ratio of disordered residues make them difficult targets for traditional classification techniques. Existing computational methods mostly rely on sequence profiles to improve accuracy which is time consuming and computationally expensive. This article describes an ab initio sequence-only prediction method-which tries to overcome the challenge of accurate prediction posed by IDRs-based on reduced amino acid alphabets and convolutional neural networks (CNNs). We experiment with six different 3-letter reduced alphabets. We argue that the dimensional reduction in the input alphabet facilitates the detection of complex patterns within the sequence by the convolutional step. Experimental results show that our proposed IDR predictor performs at the same level or outperforms other state-of-the-art methods in the same class, achieving accuracy levels of 0.76 and AUC of 0.85 on the publicly available Critical Assessment of protein Structure Prediction dataset (CASP10). Therefore, our method is suitable for proteome-wide disorder prediction yielding similar or better accuracy than existing approaches at a faster speed.

CHEMICAL COMPOSITION AND AMINO ACID PROFILE OF FRESH AND STEAMED COBIA (Rachycentron canadum L.)

Cobia ( Rachycentron canadum ) is economically important fish with good prospects because of fast growing and easily cultured. Cobia is usually processed by many methods including steaming. The purposes of this research were to determine the effect of steaming process on proximate and amino acids composition. The chemical composition of fresh and steamed cobia’s meat were determined by proximate analysis. Amino acid compositions of fresh and steamed cobia’s meat were measured using HPLC (high performance liquid chromatography). Steaming process reduced 11.31% of water, 1.06% of ash, 26.04% of fat, and 9.11% of protein. Fresh and steamed cobia’s meat contained 17 amino acids consisting of 9 essential amino acids and 8 nonessential amino acids. The highest essential amino acid in fresh cobia’s meat was arginine (2,262 mg/100 g) and the highest nonessential amino acid was glutamic acid (3,894 mg/100 g). Steaming process reduced amino acids generally. The highest essential amino acid in steamed cobia’s meat was leucine (1,379 mg/100 g) and the highest nonessential amino acid was glutamic acid (2,370 mg/100 g). Taurine content of fresh cobia’s meat was 120.84 mg/100 g and changed into 94.33 mg/100 g after steaming process.

Nutrients men-TOR β-Cells to Adulthood.

A major trigger of adult β-cell insulin secretion is glucose. In a recent issue of Cell Metabolism, Helman and colleagues show that in fetuses insulin secretion depends on the activation of mTOR by amino acids and that reducing amino acids promotes maturation of β-cells derived from pluripotent stem cells.

Prediction of High-Risk Types of Human Papillomaviruses Using Reduced Amino Acid Modes.

A human papillomavirus type plays an important role in the early diagnosis of cervical cancer. Most of the prediction methods use protein sequence and structure information, but the reduced amino acid modes have not been used until now. In this paper, we introduced the modes of reduced amino acids to predict high-risk HPV. We first reduced 20 amino acids into several nonoverlapping groups and calculated their structure and physicochemical modes for high-risk HPV prediction, which was tested and compared with the existing methods on 68 samples of known HPV types. The experiment result indicates that the proposed method achieved better performance with an accuracy of 96.49%, indicating that the reduced amino acid modes might be used to improve the prediction of high-risk HPV types.

RaacLogo: a new sequence logo generator by using reduced amino acid clusters.

Sequence logos give a fast and concise display in visualizing consensus sequence. Protein exhibits greater complexity and diversity than DNA, which usually affects the graphical representation of the logo. Reduced amino acids perform powerful ability for simplifying complexity of sequence alignment, which motivated us to establish RaacLogo. As a new sequence logo generator by using reduced amino acid alphabets, RaacLogo can easily generate many different simplified logos tailored to users by selecting various reduced amino acid alphabets that consisted of more than 40 clustering algorithms. This current web server provides 74 types of reduced amino acid alphabet, which were manually extracted to generate 673 reduced amino acid clusters (RAACs) for dealing with protein alignment. A two-dimensional selector was proposed for easily selecting desired RAACs with underlying biology knowledge. It is anticipated that the RaacLogo web server will play more high-potential roles for protein sequence alignment, topological estimation and protein design experiments. RaacLogo is freely available at http://bioinfor.imu.edu.cn/raaclogo.