Prashanth Suravajhala

A classification scoring schema to validate protein interactors

Hypothetical protein [HP] annotation poses a great challenge especially when the protein is putatively linked or mapped to another protein. With protein interaction networks (PIN) prevailing, many visualizers still remain unsupported to the HP annotation. Through this work, we propose a six-point classification system to validate protein interactions based on diverse features. The HP data-set was used as a training data-set to find putative functional interaction partners to the remaining proteins that are waiting to be interacting. A Total Reliability Score (TRS) was calculated based on the six-point classification which was evaluated using machine learning algorithm on a single node. We found that multilayer perceptron of neural network yielded 81.08% of accuracy in modelling TRS whereas feature selection algorithms confirmed that all classification features are implementable. Furthermore statistical results using variance and co-variance analyses confirmed the usefulness of these classification metrics. It has been evaluated that of all the classification features, subcellular location (sorting signals) makes higher impact in predicting the function of HPs.

Comparative leaf proteomics of drought-tolerant and -susceptible peanut in response to water stress

UNLABELLED Water stress (WS) predisposes peanut plants to fungal infection resulting in pre-harvest aflatoxin contamination. Major changes during water stress including oxidative stress, lead to destruction of photosynthetic apparatus and other macromolecules within cells. Two peanut cultivars with diverse drought tolerance characteristics were subjected to WS, and their leaf proteome was compared using two-dimensional electrophoresis complemented with MALDI-TOF/TOF mass spectrometry. Ninety-six protein spots were differentially abundant to water stress in both cultivars that corresponded to 60 non-redundant proteins. Protein interaction prediction analysis suggests that 42 unique proteins showed interactions in tolerant cultivar while 20 showed interactions in the susceptible cultivar, activating other proteins in directed system response networks. Four proteins: glutamine ammonia ligase, chitin class II, actin isoform B, and beta tubulin, involved in metabolism, defense and cellular biogenesis, are unique in tolerant cultivar and showed positive interactions with other proteins. In addition, four proteins: serine/threonine protein phosphate PP1, choline monooxygenase, peroxidase 43, and SNF1-related protein kinase regulatory subunit beta-2, that play a role as cryoprotectants through signal transduction, were induced in drought tolerant cultivar following WS. Eleven interologs of these proteins were found in Arabidopsis interacting with several proteins and it is believed that similar mechanisms/pathways exist in peanut. SIGNIFICANCE Peanuts (Arachis hypogaea L.) are a major source of plant protein grown in subtropical and tropical regions of the world. Pre-harvest aflatoxin contamination is a major problem that affects peanut crop yield and food safety. Poor understanding of molecular and cellular mechanisms associated with aflatoxin resistance is largely responsible for the lack of progress in elucidating a process/methodology for reducing aflatoxin contamination in peanuts. Drought perturbs the invasion of the aflatoxin producing fungus and thus affects the quality and yield of peanut. Therefore, more studies involving the effects of drought stress to determine the molecular changes will enhance our understanding of the key metabolic pathways involved in the combined stresses. The changes associated with the biotic and abiotic interactions within the peanut will be used to determine the metabolic pathways involved in the stress tolerance. This research would be beneficial in identifying the tolerant molecular signatures and promoting food safety and consumer health through breeding superior quality peanut cultivars.

Functional and structural insights into novel DREB1A transcription factors in common wheat (Triticum aestivum L.)

Triticum aestivum L. known as common wheat is one of the most important cereal crops feeding a large and growing population. Various environmental stress factors including drought, high salinity and heat etc. adversely affect wheat production in a significant manner. Dehydration-responsive element-binding (DREB1A) factors, a class of transcription factors (TF) play an important role in combating drought stress. It is known that DREB1A specifically interacts with the dehydration responsive elements (DRE/CRT) inducing expression of genes involved in environmental stress tolerance in plants. Despite its critical interplay in plants, the structural and functional aspects of DREB1A TF in wheat remain unresolved. Previous studies showed that wheat DREBs (DREB1 and DREB2) were isolated using various methods including yeast two-hybrid screens but no extensive structural models were reported. In this study, we made an extensive in silico study to gain insight into DREB1A TF and reported the location of novel DREB1A in wheat chromosomes. We inferred the three-dimensional structural model of DREB1A using homology modelling and further evaluated them using molecular dynamics(MD) simulations yielding refined modelled structures. Our biochemical function predictions suggested that the wheat DREB1A orthologs have similar biochemical functions and pathways to that of AtDREB1A. In conclusion, the current study presents a structural perspective of wheat DREB1A and helps in understanding the molecular basis for the mechanism of DREB1A in response to environmental stress.

PSPDB: Plant Stress Protein Database

Plants produce various proteins to overcome biotic and abiotic stresses. Current plant stress databases report plant genes without protein annotations specific to these stresses. To date, according to our findings, a unique plant stress protein database for both biotic and abiotic stresses is not available explicitly for plant biologists that describe linking out to other related databases. This need initiated us to formulate a distinctive database that includes important resources for stress-based factors. We developed the Plant Stress Protein Database (PSPDB), a web-accessible resource that covers 2,064 manually curated plant stress proteins from a wide array of 134 plant species with 30 different types of biotic and abiotic stresses. Functional and experimental validation of proteins associated with biotic and abiotic stresses has been employed as the sole criterion for inclusion in the database. The database is available at http://www.bioclues.org/pspdb/.

Making novel proteins from pseudogenes

MOTIVATION Recently, we made synthetic proteins from non-coding DNA of Escherichia coli. Encouraged by this, we asked: can we artificially express pseudogenes into novel and functional proteins? What kind of structures would be generated? Would these proteins be stable? How would the organism respond to the artificial reactivation of pseudogenes? RESULTS To answer these questions, we studied 16 full-length protein equivalents of pseudogenes. The sequence-based predictions indicated interesting molecular and cellular functional roles for pseudogene-derived proteins. Most of the proteins were predicted to be involved in the amino acid biosynthesis, energy metabolism, purines and pyrimidine biosynthesis, central intermediary metabolism, transport and binding. Interestingly, many of the pseudogene-derived proteins were predicted to be enzymes. Furthermore, proteins showed strong evidence of stable tertiary structures. The prediction scores for structure, function and stability were found to be favorable in most of the cases. IMPACT To our best knowledge, this is the first such report that predicts the possibility of making functional and stable proteins from pseudogenes. In future, it would be interesting to experimentally synthesize and validate these predictions.

Identifying pseudogenes from hypothetical proteins for making synthetic proteins

Nature selected certain regions of the genome for encoding proteins. Most of the sequences were used to encode only RNA. What happened to the remaining sections of the genome? It is possible that some sequences were retired and retained as non-functional entities called pseudogenes. Though several evolutionary prospects with functional endpoints exist, we looked at the possibility of hypothetical proteins correlating with the emergence of pseudogenes and potential of such genes to make novel synthetic molecules. In this commentary, we consider two key aspects: (1) does any correlation exist between hypothetical proteins and pseudogenes and (2)—can we make novel and functional proteins from pseudogenes?

A Web-resource for Nutrient Use Efficiency related Genes, QTLs, and microRNA in important cereals and model plants

Cereals are the key contributors to global food security. Genes involved in uptake (transport), assimilation and utilization of macro- and micro-nutrients are responsible for their content in grain and straw. Although many cereal genomic databases are available, currently there is no cohesive web-resource of manually curated nutrient use efficiency (NtUE) related genes and QTLs, etc. In this study, we present a web-resource containing information on NtUE related genes/QTLs and the corresponding available microRNAs for some of these genes in four major cereal crops [wheat (Triticum aestivum), rice (Oryza sativa), maize (Zea mays), barley (Hordeum vulgare)], two alien species (Triticum urartu and Aegilops tauschii) related to wheat, and two model species including Brachypodium distachyon and Arabidopsis thaliana. Gene annotations integrated in the current web-resource were collected from the existing databases and the available literature. The primary goal of developing this web-resource is to provide descriptions of the NtUE related genes and their functional annotation. MicroRNA targeting some of the NtUE related genes and the quantitative trait loci (QTLs) for NtUE related traits are also included. The available information in the web-resource should help the users to readily search the desired information. Web-resource URL http://bioclues.org/NtUE/

Twelve years of BIOinformatics CLUb for Experimenting Scientists (Bioclues)

We describe the scientific community of an India effort, the Bioinfomatics Club for Experimenting Scientists (Bioclues) whose aim works on four avenues, viz. Mentoring, Outreach, Research and Entrepreneurship (MORE). Incepted in the year 2005, the organization went on to become an affiliate of International Society for Computational Biology (ISCB) in 2011. Ably supported by Asia pacific Bioinformatics Network (APBioNet), we are one of the fastest growing bioinformatics societies in India, currently serving over 3400 members from nearly 30 countries. Bioclues adheres Creative Commons License with the prime focus to help the bioinformaticists in India to promote open access. In the year 2010, when we setup vision 2020, we aimed to bring together the Indian bioinformaticians, foster a strong working mentor-mentee relationship, provide access to bioinformatics resources, organize conferences and workshops besides imparting information about research, training, education, employment and current events and news from bioinformatics, genomics, and related fields. In this article, we describe the challenges across the four avenues and further highlight the opportunities the organization has met the last decade in understanding the core necessity of computational biology virtual projects driven by these avenues viz. MORE.

Draft Genome Sequence of the Plant Growth-Promoting Rhizobacterium Pseudomonas protegens Strain BNJ-SS-45, Isolated from Rhizosphere Soil of Wheat (Triticum aestivum)

Here, we present the draft genome sequence of Pseudomonas protegens strain BNJ-SS-45, which was isolated from wheat rhizosphere. The genome is assembled with 7,116,445 bp with a GC content of 63.34% consisting of 32 scaffolds. ABSTRACT Here, we present the draft genome sequence of Pseudomonas protegens strain BNJ-SS-45, which was isolated from wheat rhizosphere. The genome is assembled with 7,116,445 bp with a GC content of 63.34% consisting of 32 scaffolds. The genome is useful in prediction of secondary metabolites, particularly rhizoxin, pyoverdine, and bacteriocin.

Genetics of Lipodystrophy: Can It Help in Understanding the Pathophysiology of Metabolic Syndrome?

Understanding phenotypes and their genetic determinants for metabolic syndrome (MetS) has been quite challenging. With the advent of systems genomic approaches, there is a need to decipher methods for identification and evaluating the functional role of phenotypic traits associated with complex diseases, such as MetS. The monogenic syndromes of lipodystrophy are well understood, but the molecular pathophysiology of insulin resistance (IR) underpinning the obesity, diabetes mellitus, and dyslipidemia is not well deciphered. In this commentary, we argue the role of pathophysiology of MetS, and its effects into possible understanding of genetic determinants associated with lipodystrophy-mediated diabetes mellitus.