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      Gene expression in Lucilia sericata ( Diptera : Calliphoridae ) larvae exposed to Pseudomonas aeruginosa and Acinetobacter baumannii identifies shared and microbe‐specific induction of immune genes

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          Abstract

          <p class="first" id="d33118e142">Antibiotic resistance is a continuing challenge in medicine. There are various strategies for expanding antibiotic therapeutic repertoires, including the use of blow flies. Their larvae exhibit strong antibiotic and antibiofilm properties that alter microbiome communities. One species, Lucilia sericata, is used to treat problematic wounds due to its debridement capabilities and its excretions and secretions that kill some pathogenic bacteria. There is much to be learned about how L. sericata interacts with microbiomes at the molecular level. To address this deficiency, gene expression was assessed after feeding exposure (1 h or 4 h) to two clinically problematic pathogens: Pseudomonas aeruginosa and Acinetobacter baumannii. The results identified immunity-related genes that were differentially expressed when exposed to these pathogens, as well as non-immune genes possibly involved in gut responses to bacterial infection. There was a greater response to P. aeruginosa that increased over time, while few genes responded to A. baumannii exposure, and expression was not time-dependent. The response to feeding on pathogens indicates a few common responses and features distinct to each pathogen, which is useful in improving the wound debridement therapy and helps to develop biomimetic alternatives. </p>

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Is Open Access

            edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

            Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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              Author and article information

              Contributors
              Journal
              Insect Molecular Biology
              Insect Molecular Biology
              Wiley
              0962-1075
              1365-2583
              February 2022
              October 17 2021
              February 2022
              : 31
              : 1
              : 85-100
              Affiliations
              [1 ]Department of Entomology Texas A&amp;M University College Station TX USA
              [2 ]Department of Biology and Biochemistry University of Houston Houston TX USA
              [3 ]Southern Plains Agricultural Research Center, Agricultural Research Service US Department of Agriculture College Station TX USA
              [4 ]BioTherapeutics Education and Research (BTER) Foundation Irvine CA USA
              [5 ]Monarch Labs Irvine CA USA
              Article
              10.1111/imb.12740
              34613655
              81c7eeaa-882e-48c9-b5f5-95435765afb0
              © 2022

              http://onlinelibrary.wiley.com/termsAndConditions#am

              http://onlinelibrary.wiley.com/termsAndConditions#vor

              http://doi.wiley.com/10.1002/tdm_license_1.1

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