Biology subjects

Khan, A. M.

Publications and source records attributed to Khan, A. M..

21 records · Page 2Linked to original sources

bioRxiv2018

The parasitic worm product ES-62 normalises the gut microbiota/bone marrow axis in inflammatory arthritis

The human immune system has evolved in the context of our colonisation by bacteria, viruses, fungi and parasitic helminths. Reflecting this, the rapid eradication of pathogens appears to have resulted in reduced microbiome diversity and generation of chronically activated immune systems, presaging the recent rise of allergic, autoimmune and metabolic disorders. Certainly, gastrointestinal helminths can protect against gut and lung mucosa inflammatory conditions by modulating the microbiome and suppressing the chronic inflammation associated with dysbiosis. Here, we employ ES-62, an immunomodulator secreted by tissue-dwelling Acanthocheilonema viteae to show that modulation of the gut microbiome does not require live infection with gastrointestinal-based helminths nor is protection restricted to mucosal diseases. Specifically, subcutaneous administration of this defined parasitic worm product affords protection against joint disease in collagen-induced arthritis, a mouse model of rheumatoid arthritis, which is associated with normalisation of gut microbiota and prevention of loss of intestinal barrier integrity.

immunology↗

bioRxiv2018

Mapping molecular datasets back to the brain regions they are extracted from: Remembering the native countries of hypothalamic expatriates and refugees

This article, which includes novel unpublished data along with commentary and analysis, focuses on approaches to link transcriptomic, proteomic, and peptidomic datasets mined from brain tissue to the original locations within the brain that they are derived from using digital atlas mapping techniques. We use, as an example, the transcriptomic, proteomic and peptidomic analyses conducted in the mammalian hypothalamus. Following a brief historical overview, we highlight studies that have mined biochemical and molecular information from the hypothalamus and then lay out a strategy for how these data can be linked spatially to the mapped locations in a canonical brain atlas where the data come from, thereby allowing researchers to integrate these data with other datasets across multiple scales. A key methodology that enables atlas-based mapping of extracted datasets - laser-capture microdissection - is discussed in detail, with a view of how this technology is a bridge between systems biology and systems neuroscience.

neuroscience↗

bioRxiv2018

MGDb: An analyzed database and a genomic resource of mango (Mangifera Indica L.) cultivars for mango research

Mango is one of the famous and fifth most important subtropical/tropical fruit crops worldwide with the production centered in India and South-East Asia. Recently, there has been a worldwide interest in mango genomics to produce tools for Marker Assisted Selection and trait association. There are no web-based analyzed genomic resources available for mango particularly. Hence a complete mango genomic resource was required for improvement in research and management of mango germplasm. In this project, we have done comparative transcriptome analysis of four mango cultivars i.e. cv. Langra, cv. Zill, cv. Shelly and cv. Kent from Pakistan, China, Israel, and Mexico respectively. The raw data is obtained through De-novo sequence assembly which generated 30,953-85,036 unigenes from RNA-Seq datasets of mango cultivars. The project is aimed to provide the scientific community and general public a mango genomic resource and allow the user to examine their data against our analyzed mango genome databases of four cultivars (cv. Langra, cv. Zill, cv. Shelly and cv. Kent). A mango web genomic resource MGdb, is based on 3-tier architecture, developed using Python, flat file database, and JavaScript. It contains the information of predicted genes of the whole genome, the unigenes annotated by homologous genes in other species, and GO (Gene Ontology) terms which provide a glimpse of the traits in which they are involved. This web genomic resource can be of immense use in the assessment of the research, development of the medicines, understanding genetics and provides useful bioinformatics solution for analysis of nucleotide sequence data. We report here worlds first web-based genomic resource particularly of mango for genetic improvement and management of mango genome.

bioinformatics↗