Investigating the Functional Role of Hypothetical Proteins From an Antarctic Bacterium Pseudomonas sp. Lz4W: Emphasis on Identifying Proteins Involved in Cold Adaptation.

Exploring the molecular mechanisms behind bacterial adaptation to extreme temperatures has potential biotechnological applications. In the present study, Pseudomonas sp. Lz4W, a Gram-negative psychrophilic bacterium adapted to survive in Antarctica, was selected to decipher the molecular mechanism underlying the cold adaptation. Proteome analysis of the isolates grown at 4°C was performed to identify the proteins and pathways that are responsible for the adaptation. However, many proteins from the expressed proteome were found to be hypothetical proteins (HPs), whose function is unknown. Investigating the functional roles of these proteins may provide additional information in the biological understanding of the bacterial cold adaptation. Thus, our study aimed to assign functions to these HPs and understand their role at the molecular level. We used a structured insilico workflow combining different bioinformatics tools and databases for functional annotation. Pseudomonas sp. Lz4W genome (CP017432, version 1) contains 4493 genes and 4412 coding sequences (CDS), of which 743 CDS were annotated as HPs. Of these, from the proteome analysis, 61 HPs were found to be expressed consistently at the protein level. The amino acid sequences of these 61 HPs were submitted to our workflow and we could successfully assign a function to 18 HPs. Most of these proteins were predicted to be involved in biological mechanisms of cold adaptations such as peptidoglycan metabolism, cell wall organization, ATP hydrolysis, outer membrane fluidity, catalysis, and others. This study provided a better understanding of the functional significance of HPs in cold adaptation of Pseudomonas sp. Lz4W. Our approach emphasizes the importance of addressing the "hypothetical protein problem" for a thorough understanding of mechanisms at the cellular level, as well as, provided the assessment of integrating proteomics methods with various annotation and curation approaches to characterize hypothetical or uncharacterized protein data. The MS proteomics data generated from this study has been deposited to the ProteomeXchange through PRIDE with the dataset identifier-PXD029741.

Systems Challenges of Hepatic Carcinomas: A Review.

Hepatocellular Carcinoma (HCC) is ubiquitous in its prevalence in most of the developing countries. In the era of systems biology, multi-omics has evinced an extensive approach to define the underlying mechanism of disease progression. HCC is a multifactorial disease and the investigation of progression of liver cirrhosis becomes much extensive with cultivating omics approaches. We have performed a comprehensive review about such challenges in multi-omics approaches that are concerned to identify the immunological, genetics and epidemiological factors associated with HCC.

A model to predict the function of hypothetical proteins through a nine-point classification scoring schema.

BACKGROUND: Hypothetical proteins [HP] are those that are predicted to be expressed in an organism, but no evidence of their existence is known. In the recent past, annotation and curation efforts have helped overcome the challenge in understanding their diverse functions. Techniques to decipher sequence-structure-function relationship, especially in terms of functional modelling of the HPs have been developed by researchers, but using the features as classifiers for HPs has not been attempted. With the rise in number of annotation strategies, next-generation sequencing methods have provided further understanding the functions of HPs. RESULTS: In our previous work, we developed a six-point classification scoring schema with annotation pertaining to protein family scores, orthology, protein interaction/association studies, bidirectional best BLAST hits, sorting signals, known databases and visualizers which were used to validate protein interactions. In this study, we introduced three more classifiers to our annotation system, viz. pseudogenes linked to HPs, homology modelling and non-coding RNAs associated to HPs. We discuss the challenges and performance of these classifiers using machine learning heuristics with an improved accuracy from Perceptron (81.08 to 97.67), Naive Bayes (54.05 to 96.67), Decision tree J48 (67.57 to 97.00), and SMO_npolyk (59.46 to 96.67). CONCLUSION: With the introduction of three new classification features, the performance of the nine-point classification scoring schema has an improved accuracy to functionally annotate the HPs.

HYPO: A Database of Human Hypothetical Proteins.

BACKGROUND: There are genes whose function remains obscure as they may not have similarities to known regions in the genome. Such known 'unknown' genes constituting the Open Reading Frames (ORF) that remain in the epigenome are termed as orphan genes and the proteins encoded by them but having no experimental evidence of translation are termed as 'Hypothetical Proteins' (HPs). OBJECTIVES: We have enhanced our former database of Hypothetical Proteins (HP) in human (HypoDB) with added annotation, application programming interfaces and descriptive features. The database hosts 1000+ manually curated records of the known 'unknown' regions in the human genome. The new updated version of HypoDB with functionalities (Blast, Match) is freely accessible at http://www.bioclues.org/hypo2. METHODS: The total collection of HPs were checked using experimentally validated sets (from Swiss-Prot) or non-experimentally validated set (TrEMBL) or the complete set (UniProtKB). The database was designed with java at the core backend, integrated with databases, viz. EMBL, PIR, HPRD and those including descriptors for structural databases, interaction and association databases. RESULTS: The HypoDB constituted Application Programming Interfaces (API) for implicitly searching resources linking them to other databases like NCBI Link-out in addition to multiple search capabilities along with advanced searches using integrated bio-tools, viz. Match and BLAST were incorporated. CONCLUSION: The HypoDB is perhaps the only open-source HP database with a range of tools for common bioinformatics retrievals and serves as a standby reference to researchers who are interested in finding candidate sequences for their potential experimental work.

Annotation and curation of uncharacterized proteins- challenges.

Hypothetical proteins (HPs) are the proteins predicted to be expressed from an open reading frame, making a substantial fraction of proteomes in both prokaryotes and eukaryotes. Genome projects have led to the identification of many therapeutic targets, the putative function of the protein, and their interactions. In this review we enlist various methods linking annotation to structural and functional prediction of HPs that assist in the discovery of new structures and functions serving as markers and pharmacological targets for drug designing, discovery, and screening. Further we give an overview of how mass spectrometry as an analytical technique is used to validate protein characterisation. We discuss how microarrays and protein expression profiles help understanding the biological systems through a systems-wide study of proteins and their interactions with other proteins and non-proteinaceous molecules to control complex processes in cells. Finally, we articulate challenges on how next generation sequencing methods have accelerated multiple areas of genomics with special focus on uncharacterized proteins.