Biology subjects

Gautam, A.

Publications and source records attributed to Gautam, A..

4 recordsLinked to original sources

bioRxiv2018

A web bench for analysis and prediction of oncological status from proteomics data of urine samples

Urine-based cancer biomarkers offer numerous advantages over the other biomarkers and play a crucial role in cancer management. In this study, an attempt has been made to develop proteomics-based prediction models to discriminate patients of oncological disorders related to urinary tract and healthy controls from their urine samples. The dataset used in this study was obtained from human urinary peptide database that contains urine proteomics data of 1525 oncological and 1503 healthy controls with the spectral intensity of 5605 peptides. First, we identified peptide spectra using various feature selection techniques, which display different intensity and occurrence in oncological samples and healthy controls. Based on selected 173 peptide-based biomarkers, we developed models for predicting oncological samples and achieved maximum accuracy of 91.94% with 0.84 MCC. Prediction models were also developed based on spectral intensities with known peptide sequences. We also quantitated the amount of protein in a sample based on intensities of its fragments/peptides and developed prediction models based on protein expression. It was observed that certain proteins and their peptides such as fragments of collagen protein are more abundant in oncological samples. Based on this study, we also developed a web bench, CancerUBM, for mining proteomics data, which is freely available at http://webs.iiitd.edu.in/raghava/cancerubm/.

bioinformatics↗

bioRxiv2018

Altered Fecal Microbiota and Urine Metabolome as Signatures of Soman Poisoning

The experimental pathophysiology of organophosphorus (OP) chemical exposure has been extensively reported. Here, we describe an altered fecal microbiota and urine metabolome that follows intoxication with soman, a lipophilic G class chemical warfare nerve agent. Non-anaesthetized Sprague-Dawley male rats were subcutaneously administered soman at 0.8 - 1.0 of the median lethal dose (LD50) and evaluated for signs of toxicity. Animals were stratified based on seizing activity to evaluate effects of soman exposure on fecal bacterial biota and urine metabolites. Soman exposure reshaped fecal bacterial biota by preferentially expanding Facklamia, Agrobacterium, Bilophila, Enterobacter, and Morganella genera of the Firmicutes and Proteobacteria phyla, some of which are known to hydrolyze OPs. However, analogous changes were not observed in the bacterial biota of the ileum, which remained the same irrespective of dose or seizing status of animals after exposure. Interestingly, when considering just the seizing status of animals, we found that the urine metabolome was markedly altered. Leukotriene C4, kynurenic acid, 5-hydroxyindoleacetic acid, norepinephrine, and aldosterone were excreted at much higher rates at 72 hrs in seizing animals, consistent with early multi-organ involvement during soman poisoning. However, at 75 days post soman exposure, bacterial biota stabilized and no differences were observed. These findings demonstrate the feasibility of using the dysbiosis of fecal bacterial biota in combination with urine metabolome alterations as forensic evidence for OP exposure temporally.\n\nImportanceThe paucity of assays to determine physiologically relevant OP exposure presents an opportunity to explore the use bacterial sentinels in combination with urine to assess changes in the exposed host. Recent advances in technologies and computational approaches have enabled researches to survey large community level changes of gut bacterial biota and metabolomic changes in various biospecimens. Here, we profile combined changes in bacterial biota and urine metabolome due to chemical warfare OP exposure. The significance of our work is to reveal that monitoring bacterial biota and urine metabolites as surrogates of OP exposure in biospecimens suitable for existing clinical laboratory workflows is plausible without the need for the development of new technology, invasive procedures, or complicated analytical approaches. The larger value of such an approach is that any setting with a moderate clinical chemistry and microbiology capability can determine pre-symptomatic exposure to enhance current triage standards in case of mass exposures, refugee movements, humanitarian missions, and training settings once an algorithm has been validated. In the event of \"potential\" exposures by time or distance, this assay can be further developed to estimate affected radius or time dimension for health monitoring and treatment interventions.

physiology↗

bioRxiv2017

SEA: The Small RNA Expression Atlas

We present the Small RNA Expression Atlas (SEA), a web application that allows for the interactive querying, visualization, and analysis of known and novel small RNAs across ten organisms. It contains sRNA and pathogen expression information for over 4,200 published samples with standardized search terms and ontologies. In addition, SEA allows for the interactive visualization and re-analysis of 879 differential expression and 514 classification comparisons. SEAs user model enables sRNA researchers to compare and re-analyze user-specific and published datasets, highlighting common and distinct sRNA expression patterns.\n\nWe provide evidence for SEAs fidelity by (i) generating a set of 591 tissue specific miRNAs across 30 tissues, (ii) finding known and novel bacterial and viral infections across diseases, and (iii) determining a Parkinsons disease-specific blood biomarker signature using novel data.\n\nWe believe that SEAs simple semantic search interface, the flexible interactive reports, and the user model with rich analysis capabilities will enable researchers to better understand the potential function and diagnostic value of sRNAs or pathogens across tissues, diseases, and organisms.\n\nAvailability and ImplementationSEA is implemented in Java, J2EE, spring, Django, html5, css3, JavaScript, Bootstrap, Vue.js, D3, mongodb and neo4j. It is freely available at http://sea.ims.bio/.

bioinformatics↗

bioRxiv2017

Oasis2.0: improved online analysis of small RNA-seq data

Oasis 2 is a new main release of the Oasis web application for the detection, differential expression, and classification of small RNAs in deep sequencing data. Compared to its predecessor Oasis, Oasis 2 features a novel and speed-optimized sRNA detection module that supports the identification of small RNAs in any organism with higher accuracy. Next to the improved detection of small RNAs in a target organism, the software now also recognizes potential cross-species miRNAs and viral and bacterial sRNAs in infected samples. In addition, novel miRNAs can now be queried and visualized interactively, providing essential information for over 700 high-quality miRNA predictions across 14 organisms. Robust biomarker signatures can now be obtained using the novel enhanced classification module. Oasis 2 enables biologists and medical researchers to rapidly analyze and query small RNA deep sequencing data with improved precision, recall, and speed, in an interactive and user-friendly environment.\n\nAvailability and Implementation: Oasis 2 is implemented in Java, J2EE, mysql, Python, R, PHP and JavaScript. It is freely available at http://oasis.dzne.de

bioinformatics↗