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Farooqui, A.

Publications and source records attributed to Farooqui, A..

2 recordsLinked to original sources

Feeding a low-protein diet exacerbates the susceptibility to Citrobacter rodentium and Dextran Sulfate Sodium-induced intestinal injury in mice.

Globally, almost half of all early childhood deaths are linked to severe undernutrition, herein referred to as severe malnutrition. Mortality in severely malnourished children is often attributed to common infectious diseases, including enteric infections. It has been proposed that impaired intestinal barrier function contributes to mortality, but direct evidence is limited and thus there exists a need to develop improved preclinical models to test these and other mechanistic hypotheses. In this study, we aimed to describe differences in response to enteric inflammation and infection in the colon of malnourished mice compared to well-nourished littermates. C57Bl/6 male weanlings were fed isocaloric diets, either a low 1% protein diet (LPD) or a control 18% protein diet (CPD) for 2-weeks either in combination with oral administration of dextran sodium sulfate (DSS), or Citrobacter rodentium (C. rodentium). LPD-fed mice were more susceptible to DSS or C. rodentium as evidenced by increased clinical severity scores, and reaching their humane endpoints. LPD-fed mice also showed more signs of colonic dysfunction with reduced levels of tight junction proteins, higher colonic pathogen load, and increased systemic inflammation and bacterial spread. Taken together, these observations show that malnourished animals have increased susceptibility to intestinal dysfunction caused by either chemical exposure or infection. These novel preclinical models can be used to further elucidate the processes involved in enteric dysfunction in malnutrition and to test therapies to improve intestinal repair and outcomes.

microbiology↗

Stage specific classification of DEGs via statistical profiling and network analysis reveals potential biomarker associated with various stages of TB

BackgroundTuberculosis (TB) is a deadly transmissible disease that can infect almost any body-part of the host but is mostly infect the lungs. It is one of the top 10 causes of death worldwide. In the 30 high TB burden countries, 87% of new TB cases occurred in 2016. Seven countries: India, Indonesia, China, Philippines, Pakistan, Nigeria, and South Africa accounted for 64% of the new TB cases. To stop the infection and progression of the disease, early detection of TB is important. In our study, we used microarray data set and compared the gene expression profiles obtained from blood samples of patients with different datasets of Healthy control, Latent infection, Active TB and performed network-based analysis of DEGs to identify potential biomarker.\n\nObjectivesWe want to observe the transition of genes from normal condition to different stages of the TB and identify, annotate those genes/pathways/processes that play key role in the progression of TB disease during its cyclic interventions in human body.\n\nResultsWe identified 319 genes that are differentially expressed in various stages of TB (Normal to LTTB, Normal to Active TB and LTTB to active TB) and allocated to pathways from multiple databases which comprised of curated class of associated genes. These pathways importance was then evaluated according to the no. of DEGs present in the pathway and these genes show the broad spectrum of processes that take part in every state. In addition, we studied the regulatory networks of these classified genes, network analysis does consider the interactions between genes (specific for TB) or proteins provide us new facts about TB disease, which in turn can be used for potential biomarkers identification. We identified total 29 biomarkers from various comparison groups of TB stages in which 14 genes are over expressed as host responses against pathogen, but 15 genes are down regulated that means these genes has allowed the process of host defense to cease and give time to pathogen for its progression.\n\nConclusionsThis study revealed that gene-expression profiles can be used to identify and classified the genes on stage specific pattern among normal, LTTB and active TB and network modules associated with various stages of TB were elucidated, which in turn provided a basis for the identification of potential pathways and key regulatory genes that may be involved in progression of TB disease.

systems biology↗