The implications of APOBEC3-mediated C-to-U RNA editing for human disease

Intra-organism biodiversity is thought to arise from epigenetic modification of constituent genes and post-translational modifications of translated proteins. Here, we show that post-transcriptional modifications, like RNA editing, may also contribute. RNA editing enzymes APOBEC3A and APOBEC3G catalyze the deamination of cytosine to uracil. RNAsee (RNA site editing evaluation) is a computational tool developed to predict the cytosines edited by these enzymes. We find that 4.5% of non-synonymous DNA single nucleotide polymorphisms that result in cytosine to uracil changes in RNA are probable sites for APOBEC3A/G RNA editing; the variant proteins created by such polymorphisms may also result from transient RNA editing. These polymorphisms are associated with over 20% of Medical Subject Headings across ten categories of disease, including nutritional and metabolic, neoplastic, cardiovascular, and nervous system diseases. Because RNA editing is transient and not organism-wide, future work is necessary to confirm the extent and effects of such editing in humans.

The Role of C-to-U RNA Editing in Human Biodiversity

Intra-organism biodiversity is thought to arise from epigenetic modification of our constituent genes and post-translational modifications after mRNA is translated into proteins. We have found that post-transcriptional modification, also known as RNA editing, is also responsible for a significant amount of our biodiversity, substantively expanding this story. The APOBEC (apolipoprotein B mRNA editing catalytic polypeptide-like) family RNA editing enzymes APOBEC3A and APOBEC3G catalyze the deamination of cytosines to uracils (C>U) in specific stem-loop structures.1,2 We used RNAsee (RNA site editing evaluation), a tool developed to predict the locations of APOBEC3A/G RNA editing sites, to determine whether known single nucleotide polymorphisms (SNPs) in DNA could be replicated in RNA via RNA editing. About 4.5% of non-synonymous SNPs which result in C>U changes in RNA, and about 5.4% of such SNPs labelled as pathogenic, were identified as probable sites for APOBEC3A/G editing. This suggests that the variant proteins created by these DNA mutations may also be created by transient RNA editing, with the potential to affect human health. Those SNPs identified as potential APOBEC3A/G-mediated RNA editing sites were disproportionately associated with cardiovascular diseases, digestive system diseases, and musculoskeletal diseases. Future work should focus on common sites of RNA editing, any variant proteins created by these RNA editing sites, and the effects of these variants on protein diversity and human health. Classically, our biodiversity is thought to come from our constitutive genetics, epigenetic phenomenon, transcriptional differences, and post-translational modification of proteins. Here, we have shown evidence that RNA editing, often stimulated by environmental factors, could account for a significant degree of the protein biodiversity leading to human disease. In an era where worries about our changing environment are ever increasing, from the warming of our climate to the emergence of new diseases to the infiltration of microplastics and pollutants into our bodies, understanding how environmentally sensitive mechanisms like RNA editing affect our own cells is essential.

Integrating Multi-Omics Data to Construct Reliable Interconnected Models of Signaling, Gene Regulatory, and Metabolic Pathways

Alteration of the status of the metabolic enzymes could be a probable way to regulate metabolic reprogramming, which is a critical cellular adaptation mechanism especially for cancer cells. Coordination among biological pathways, such as gene-regulatory, signaling, and metabolic pathways is crucial for regulating metabolic adaptation. Also, incorporation of resident microbial metabolic potential in human body can influence the interplay between the microbiome and the systemic or tissue metabolic environments. Systemic framework for model-based integration of multi-omics data can ultimately improve our understanding of metabolic reprogramming at holistic level. However, the interconnectivity and novel meta-pathway regulatory mechanisms are relatively lesser explored and understood. Hence, we propose a computational protocol that utilizes multi-omics data to identify probable cross-pathway regulatory and protein-protein interaction (PPI) links connecting signaling proteins or transcription factors or miRNAs to metabolic enzymes and their metabolites using network analysis and mathematical modeling. These cross-pathway links were shown to play important roles in metabolic reprogramming in cancer scenarios.

Association of C>U RNA Editing with Human Disease Variants

RNA-editing is an important post-transcriptional RNA sequence modification performed by two catalytic enzymes, "ADAR"(A>I) and "APOBEC"(C>U). Although APOBEC-mediated C>U editing has been associated with a number of human cancers, the extent of C>U editing in human disease remains unclear. Here, we performed an association study and found that at least 1293 human disease variants occur at sites predicted by sequence motif analysis (RNASee protocol) to undergo APOBEC3A/G C>U editing. These variants were associated with a wide array of human disease conditions ranging from cancer, metabolic disorders, retinopathies, cardiomyopathies, neurodegenerative disorders and immunodeficiencies. These results indicate that APOBEC mediated C>U RNA editing may have widespread and previously unreported contributions to human disease conditions.

Connecting signaling and metabolic pathways in EGF receptor-mediated oncogenesis of glioblastoma

As malignant transformation requires synchronization of growth-driving signaling (S) and metabolic (M) pathways, defining cancer-specific S-M interconnected networks (SMINs) could lead to better understanding of oncogenic processes. In a systems-biology approach, we developed a mathematical model for SMINs in mutated EGF receptor (EGFRvIII) compared to wild-type EGF receptor (EGFRwt) expressing glioblastoma multiforme (GBM). Starting with experimentally validated human protein-protein interactome data for S-M pathways, and incorporating proteomic data for EGFRvIII and EGFRwt GBM cells and patient transcriptomic data, we designed a dynamic model for EGFR-driven GBM-specific information flow. Key nodes and paths identified by in silico perturbation were validated experimentally when inhibition of signaling pathway proteins altered expression of metabolic proteins as predicted by the model. This demonstrated capacity of the model to identify unknown connections between signaling and metabolic pathways, explain the robustness of oncogenic SMINs, predict drug escape, and assist identification of drug targets and the development of combination therapies.

Complex and highly dynamic interconnected networks allow cancer to take different routes and circumvent chemotherapy. Therefore, understanding these context-specific networks and their dynamics of molecular interactions driven by different oncogenic signaling and metabolic pathways is very much needed to predict drug targets and the effect of therapeutics. We incorporated high-throughput transcriptome and proteome data into mathematical models to deduce properties of cancer cells through systems biology approach. Here we report the development, testing and validation of an integrated systems biology model of information flow between signaling and metabolic pathways to understand the regulation of the interconnection between them in cancer. Our model efficiently identified unique connections and key nodes important in signaling-metabolic information flow. We predicted some potential novel targets before performing actual drug tests. We have successfully applied this model to identify the interconnections altered in the constitutive signaling of the mutated EGFR by comparing EGF-dependent and wild-type EGFR signaling in glioblastoma multiforme.

Protein sites with more coevolutionary connections tend to evolve slower, while more variable protein families acquire higher coevolutionary connections

Background: Amino acid exchanges within proteins sometimes compensate for one another and could therefore be co-evolved. It is essential to investigate the intricate relationship between the extent of coevolution and the evolutionary variability exerted at individual protein sites, as well as the whole protein. Methods: In this study, we have used a reliable set of coevolutionary connections (sites within 10Å spatial distance) and investigated their correlation with the evolutionary diversity within the respective protein sites. Results: Based on our observations, we propose an interesting hypothesis that higher numbers of coevolutionary connections are associated with lesser evolutionary variable protein sites, while higher numbers of the coevolutionary connections can be observed for a protein family that has higher evolutionary variability. Our findings also indicate that highly coevolved sites located in a solvent accessible state tend to be less evolutionary variable. This relationship reverts at the whole protein level where cytoplasmic and extracellular proteins show moderately higher anti-correlation between the number of coevolutionary connections and the average evolutionary conservation of the whole protein. Conclusions: Observations and hypothesis presented in this study provide intriguing insights towards understanding the critical relationship between coevolutionary and evolutionary changes observed within proteins. Our observations encourage further investigation to find out the reasons behind subtle variations in the relationship between coevolutionary connectivity and evolutionary diversity for proteins located at various cellular localizations and/or involved in different molecular-biological functions.

Integrative genomic and network analysis identified novel genes associated with the development of advanced cervical squamous cell carcinoma

BACKGROUND

CSCC is one of the most common cancer affecting women globally. Though it is caused by the infection of hrHPV but long latency period for malignant outcome in only a subset of hrHPV infected women indicates involvement of additional alterations, primarily CNVs. Here, we showed how CNVs played a crucial role in development of advanced tumors (stage III/IV) in Indian patients.

METHODS

Initially, high-resolution CGH-SNP microarray analysis pointed out frequent CNVs followed by significantly altered genes. After comparison with TCGA dataset, expressions of the genes were checked in three CSCC datasets to identify key genes followed by Ingenuity® Pathway analysis. Then node effect property analysis was applied on the constructed PPI network to rank the key proteins. Finally, validations in independent samples were performed.

RESULTS

For the first time, frequent chromosomal amplifications at 3q13.13-3q29, 1p36.11-1p31.1, 1q21.1-1q44 and 5p15.33-5p12 followed by common deletions at 11q14.1-11q25, 2q34-2q37.3, 4p16.3-4p12 and 13q13.3-13q14.3 were identified in Indian CSCC patients. Integrative analysis found 78 key genes including several novel ones, which were mostly associated with 'Cancer' and may regulate DNA repair and metabolic pathways. Analysis showed PARP1 and ATR were among the top ranking protein interactors.

CONCLUSIONS

Frequent amplification and over-expression of ATR and PARP1 were further confirmed in cervical lesions, indicating their association with poor prognosis of advanced CSCC patients.

GENERAL SIGNIFICANCE

Our novel approach identified precise CNVs along with several novel genes within these loci and showed that PARP1 and ATR, having biologically significant interactions, may be involved in development of advanced CSCC.

Cholesterol Corrects Altered Conformation of MHC-II Protein in Leishmania donovani Infected Macrophages: Implication in Therapy

Background

Previously we reported that Kala-azar patients show progressive decrease in serum cholesterol as a function of splenic parasite burden. Splenic macrophages (MΦ) of Leishmania donovani (LD) infected mice show decrease in membrane cholesterol, while LD infected macrophages (I-MΦ) show defective T cell stimulating ability that could be corrected by liposomal delivery of cholesterol. T helper cells recognize peptide antigen in the context of class II MHC molecule. It is known that the conformation of a large number of membrane proteins is dependent on membrane cholesterol. In this investigation we tried to understand the influence of decreased membrane cholesterol in I-MΦ on the conformation of MHC-II protein and peptide-MHC-II stability, and its bearing on the antigen specific T-cell activation.

Methodology/Principal Findings

MΦ of CBA/j mice were infected with Leishmania donovani (I-MΦ). Two different anti-A^κ mAbs were used to monitor the status of MHC-II protein under parasitized condition. One of them (11.5–2) was conformation specific, whereas the other one (10.2.16) was not. Under parasitized condition, the binding of 11.5–2 decreased significantly with respect to the normal counterpart, whereas that of 10.2.16 remained unaltered. The binding of 11.5–2 was restored to normal upon liposomal delivery of cholesterol in I-MΦ. By molecular dynamics (MD) simulation studies we found that there was considerable conformational fluctuation in the transmembrane domain of the MHC-II protein in the presence of membrane cholesterol than in its absence, which possibly influenced the distal peptide binding groove. This was evident from the faster dissociation of the cognate peptide from peptide-MHC complex under parasitized condition, which could be corrected by liposomal delivery of cholesterol in I-MΦ.

Conclusion

The decrease in membrane cholesterol in I-MΦ may lead to altered conformation of MHC II, and this may contribute to a faster dissociation of the peptide. Furthermore, liposomal delivery of cholesterol in I-MΦ restored its normal antigen presenting function. This observation brings strength to our previous observation on host directed therapeutic application of liposomal cholesterol in experimental visceral leishmaniasis.

The disease visceral leishmaniasis is caused by the protozoan parasite Leishmania donovani (LD). One of the hallmarks of the disease is immune suppression. The parasites replicate within the macrophages and dendritic cells, and such cells are known as antigen presenting cells (APCs). APCs present peptide to T-helper cells in association with the transplantation antigen-II (MHC-II). The infected macrophages show decrease in membrane cholesterol leading to increase in membrane fluidity. The membrane cholesterol is important for maintaining conformation of membrane proteins. Here we show that conformation of MHC-II protein is altered in parasitized macrophages, which results faster dissociation of peptide from peptide-MHC-II complex as compared to normal counterpart. The conformational change in MHC-II protein is also supported by molecular dynamic simulation studies, as there is considerable structural fluctuation of MHC-II peptide binding domain in presence and absence of cholesterol. This observation indicated that cholesterol is important for maintaining conformation of MHC-II protein and stability of the peptide-MHC complex. Thus, Leishmania parasites by modulating membrane cholesterol influence above processes leading to defective T-cell stimulation in leishmaniasis. The above defects displayed by infected macrophages could be corrected by liposomal delivery of cholesterol indicating a possible therapeutic role of liposomal cholesterol in infection.

MicroRNA profiling of cisplatin-resistant oral squamous cell carcinoma cell lines enriched with cancer-stem-cell-like and epithelial-mesenchymal transition-type features

Oral cancer is of major public health problem in India. Current investigation was aimed to identify the specific deregulated miRNAs which are responsible for development of resistance phenotype through regulating their resistance related target gene expression in oral squamous cell carcinoma (OSCC). Cisplatin-resistant OSCC cell lines were developed from their parental human OSCC cell lines and subsequently characterised. The resistant cells exhibited enhanced proliferative, clonogenic capacity with significant up-regulation of P-glycoprotein (ABCB1), c-Myc, survivin, β-catenin and a putative cancer-stem-like signature with increased expression of CD44, whereas the loss of E-cadherin signifies induced EMT phenotype. A comparative analysis of miRNA expression profiling in parental and cisplatin-resistant OSCC cell lines for a selected sets (deregulated miRNAs in head and neck cancer) revealed resistance specific signature. Moreover, we observed similar expression pattern for these resistance specific signature miRNAs in neoadjuvant chemotherapy treated and recurrent tumours compared to those with newly diagnosed primary tumours in patients with OSCC. All these results revealed that these miRNAs play an important role in the development of cisplatin-resistance mainly through modulating cancer stem-cell-like and EMT-type properties in OSCC.

PALM-IST: Pathway Assembly from Literature Mining--an Information Search Tool

Manual curation of biomedical literature has become extremely tedious process due to its exponential growth in recent years. To extract meaningful information from such large and unstructured text, newer and more efficient mining tool is required. Here, we introduce PALM-IST, a computational platform that not only allows users to explore biomedical abstracts using keyword based text mining but also extracts biological entity (e.g., gene/protein, drug, disease, biological processes, cellular component, etc.) information from the extracted text and subsequently mines various databases to provide their comprehensive inter-relation (e.g., interaction, expression, etc.). PALM-IST constructs protein interaction network and pathway information data relevant to the text search using multiple data mining tools and assembles them to create a meta-interaction network. It also analyzes scientific collaboration by extraction and creation of "co-authorship network," for a given search context. Hence, this useful combination of literature and data mining provided in PALM-IST can be used to extract novel protein-protein interaction (PPI), to generate meta-pathways and further to identify key crosstalk and bottleneck proteins. PALM-IST is available at www.hpppi.iicb.res.in/ctm.

SPEER-SERVER: a web server for prediction of protein specificity determining sites

Sites that show specific conservation patterns within subsets of proteins in a protein family are likely to be involved in the development of functional specificity. These sites, generally termed specificity determining sites (SDS), might play a crucial role in binding to a specific substrate or proteins. Identification of SDS through experimental techniques is a slow, difficult and tedious job. Hence, it is very important to develop efficient computational methods that can more expediently identify SDS. Herein, we present Specificity prediction using amino acids’ Properties, Entropy and Evolution Rate (SPEER)-SERVER, a web server that predicts SDS by analyzing quantitative measures of the conservation patterns of protein sites based on their physico-chemical properties and the heterogeneity of evolutionary changes between and within the protein subfamilies. This web server provides an improved representation of results, adds useful input and output options and integrates a wide range of analysis and data visualization tools when compared with the original standalone version of the SPEER algorithm. Extensive benchmarking finds that SPEER-SERVER exhibits sensitivity and precision performance that, on average, meets or exceeds that of other currently available methods. SPEER-SERVER is available at http://www.hpppi.iicb.res.in/ss/.