Biology subjects

Mohan, S.

Publications and source records attributed to Mohan, S..

5 recordsLinked to original sources

bioRxiv2018

Long-read amplicon denoising

Long-read next generation amplicon sequencing shows promise for studying complete genes or genomes from complex and diverse populations. Current long-read sequencing technologies have challenging error profiles, hindering data processing and incorporation into downstream analyses. Here we consider the problem of how to reconstruct, free of sequencing error, the true sequence variants and their associated frequencies. Called \"amplicon denoising\", this problem has been extensively studied for short-read sequencing technologies, but current solutions do not appear to generalize well to long reads with high indel error rates. We introduce two methods: one that runs nearly instantly and is very accurate for medium length reads (here ~2.6kb) and high template coverage, and another, slower method that is more robust when reads are very long or coverage is lower.\n\nOn one real dataset with ground truth, and on a number of simulated datasets, we compare our two approaches to each other and to existing algorithms. We outperform all tested methods in accuracy, with competitive run times even for our slower method.\n\nFast Amplicon Denoising (FAD) and Robust Amplicon Denoising (RAD) are implemented purely in the Julia scientific computing language, and are hereby released along with a complete toolkit of functions that allow long-read amplicon sequence analysis pipelines to be constructed in pure Julia. Further, we make available a webserver to dramatically simplify the processing of long-read PacBio sequences.

bioinformatics↗

bioRxiv2018

Structural insight into the mechanism of neuraminidase inhibitor-resistant mutations in human-infecting H10N8 Influenza A virus

The emergence of drug resistance in avian influenza virus (AIV) is a serious concern for public health. Neuraminidase (NA) isolated from a fatal case of avian-origin H10N8 influenza virus infection was found to carry a drug-resistant mutation, NA-Arg292Lys (291 in N8 numbering). In order to understand the full potential of H10N8 drug resistance, the virus was first passaged in the presence of the most commonly used neuraminidase inhibitors (NAIs), oseltamivir and zanamivir. As expected, the Arg292Lys substitution was detected after oseltamivir treatment, however a novel Val116Asp substitution (114 in N8 numbering) was selected by zanamivir treatment. Next generation sequencing (NGS) confirmed that the mutations arose early (after passages 1-3) and became dominant in the presence of the NAI inhibitors. Extensive crystallographic studies revealed that N8-Arg292Lys resistance results mainly from loss of interactions with the inhibitor carboxylate, while rotation of Glu276 was not impaired as observed in the N9-Arg292Lys, a group 2 NA structure. In the case of Val116Asp, the binding mode between oseltamivir and zanamivir is different. Asp151 forms stabilized hydrogen bond to guanidine group of zanamivir, which may compensate the resistance caused by Val116Asp. By contrast, the amino group of oseltamivir is too short to maintain this hydrogen bond, which result in resistant. Moreover, the oseltamivir-zanamivir hybrid inhibitor MS-257 displays higher effectiveness to Val116Asp than oseltamivir, which support this notion.\n\nAuthor SummaryAside from vaccination, NAIs are currently the only alternative for the clinical treatment and prophylaxis of influenza. Understanding the mechanisms of resistance is critical to guide in drug development. In this study, two drug-resistant NA substitutions, Val116Asp and Arg292Lys, were discovered from oseltamivir and zanamivir treatment of H10N8 virus. Crystal structural analyses revealed two distinct mechanisms of these two resistant mutations and provide the explanation for the difference in susceptibility of different NAIs. Zanamivir and laninamivir were more effective against the resistant variants than oseltamivir, and Arg292Lys results in more serious oseltamivir resistance in N9 than N8 subtype. This study is well-correlated to influenza pandemic/epidemic pre-warning, as the discovery of inhibitor resistant viruses will help for new drug preparedness.

microbiology↗

bioRxiv2018

Maternal effects influence temperature-dependent offspring survival in Drosophila melanogaster

Mothers may modulate the phenotype of their offspring by affecting their development based on her own environment. In changing environments, these maternal effects are thought to adjust offspring physiology and development and thus produce offspring better prepared to the environment experienced by the mother. However, evidence for this is scarce. Here we test the consequences of a match or mismatch between mother and offspring temperature conditions on growth, adult morphology and reproduction into the grandchildren generation in the fruit fly Drosophila melanogaster. This experimental design tests the relative contribution of maternal effects and offspring intrinsic plasticity to the phenotypic response to temperature conditions. We manipulated maternal temperature conditions by exposing mothers to either 18{degrees}C or 29{degrees}C conditions. Their eggs developed at a temperature that was either matched or mismatched with the maternal one. Survival from egg to adult was higher when the maternal and offspring environments matched, showing maternal effects affecting a trait that is a close proxy for fitness. However developmental speed, adult size and fecundity responded to temperature mostly through offspring phenotypic plasticity and maternal effects only had a small contribution. The results provide experimental evidence for maternal effects in influencing a potentially adaptive offspring response to temperature in the model organism Drosophila melanogaster. These effects appear to modulate early embryonic phenotypes such as survival, more than the adult phenotypes of the offspring.

ecology↗

bioRxiv2018

UNC-16/JIP3 and UNC-76/FEZ1 limit the density of mitochondria in C. elegans neurons by maintaining the balance of anterograde and retrograde mitochondrial transport

We investigate the role of axonal transport in regulating neuronal mitochondrial density. We show that the density of mitochondria in the touch receptor neuron (TRN) of adult Caenorhabditis elegans is constant. Mitochondrial density and transport are controlled both by the Kinesin heavy chain and the Dynein-Dynactin complex. However, unlike in other models, the presence of mitochondria in C. elegans TRNs depends on Kinesin light chain as well. Mutants in the three C. elegans miro genes do not alter mitochondrial density in the TRNs. Mutants in the Kinesin-1 associated proteins, UNC-16/JIP3 and UNC-76/FEZ1, show increased mitochondrial density and also have elevated levels of both the Kinesin Heavy and Light Chains in neurons. Genetic analyses suggest that, the increased mitochondrial density at the distal end of the neuronal process in unc-16 and unc-76 depends partly on Dynein. We observe a net anterograde bias in the ratio of anterograde to retrograde mitochondrial flux in the neuronal processes of unc-16 and unc-76, likely due to both increased Kinesin-1 and decreased Dynein in the neuronal processes. Our study shows that UNC-16 and UNC-76 indirectly limit mitochondrial density in the neuronal process maintaining a balance in anterograde and retrograde mitochondrial axonal transport.

genetics↗

bioRxiv2017

Full-Length Envelope Analyzer (FLEA): A tool for longitudinal analysis of viral amplicons

Next generation sequencing of viral populations has advanced our understanding of viral population dynamics, the development of drug resistance, and escape from host immune responses. Many applications require complete gene sequences, which can be impossible to reconstruct from short reads. HIV-1 env, the protein of interest for HIV vaccine studies, is exceptionally challenging for long-read sequencing and analysis due to its length, high substitution rate, and extensive indel variation. While long-read sequencing is attractive in this setting, the analysis of such data is not well handled by existing methods. To address this, we introduce FLEA (Full-Length Envelope Analyzer), which performs end-to-end analysis and visualization of long-read sequencing data.\n\nFLEA consists of both a pipeline (optionally run on a high-performance cluster), and a client-side web application that provides interactive results. The pipeline transforms FASTQ reads into high-quality consensus sequences (HQCSs) and uses them to build a codon-aware multiple sequence alignment. The resulting alignment is then used to infer phylogenies, selection pressure, and evolutionary dynamics. The web application provides publication-quality plots and interactive visualizations, including an annotated viral alignment browser, time series plots of evolutionary dynamics, visualizations of gene-wide selective pressures (such as dN /dS) across time and across protein structure, and a phylogenetic tree browser.\n\nWe demonstrate how FLEA may be used to process Pacific Biosciences HIV-1 env data and describe recent examples of its use. Simulations show how FLEA dramatically reduces the error rate of this sequencing platform, providing an accurate portrait of complex and variable HIV-1 env populations.\n\nA public instance of FLEA is hosted at http://flea.datamonkey.org. The Python source code for the FLEA pipeline can be found at https://github.com/veg/flea-pipeline. The client-side application is available at https://github.com/veg/flea-web-app. A live demo of the P018 results can be found at http://flea.murrell.group/view/P018.

bioinformatics↗