Project description:Background: Germ-free or axenic organisms are valuable tools for studying immunity, digestion, and development in different hosts. Although most of these studies have been conducted on mice, recently, germ-free invertebrate models (e.g. Drosophila and Apis) are used due to their easy husbandry, low cost for production, maintenance and the high number of individuals per generation they produce. However, a limitation of using these insects is the simple bacterial community present in their guts. The gut of the American cockroach Periplaneta americana displays a complex gut bacterial community composed of hundreds of species. Using P. americana, we developed a germ-free omnivorous invertebrate model to investigate how gut bacteria stimulate and shape normal gut development and metabolism. To determine if the insect host is directly affected by the presence of specific members of their bacterial community, gnotobiotic cockroaches were generated by inoculating a set of various P. americana gut-endemic Gram-negative (Bacteroidetes; n=11) and Gram-positive (Firmicutes; n=2) bacterial strains into germ-free insects. Additionally, we were able to recover the ‘normal’ bacterial-induced gut phenotype by co-housing germ-free cockroaches with wildtype P. americana to produce gut-bacteria conventionalized insects. Changes in gene expression profiles from two distinct regions (midgut and hindgut) of P. americana guts were quantified by RNA-Seq analysis of the germfree, gnotobiotic and conventionalized insects. Basic transcriptomics description: High-resolution transcriptome profiling of germ-free, gnotobiotic, and conventionalized treated P. americana midgut and hindguts. Ca. 43 million reads were obtained for each treatment. A de-novo assembly of all sequence reads was performed by Trinity assembler. Transcriptome assembly yielded 369,082 gene models and 554,155 isoforms. After running Trinotate pipeline, 65,047 (12 %) these transcripts matched an annotated product in at least one of the reference databases used (Uniprot, pfam, KEGG, COG). Additionally, 1,008 putative bacterial genes were annotated in the P. americana genome and ultimately excluded from these analyses. After bacteria decontamination, 553,147 assembled isoforms were used for transcript quantification and differential expression analysis using the DESeq2 pipeline. DESeq2 analysis detected 6,730 and 3,958 differentially expressed transcripts among the germ-free, gnotobiotic and conventionalized treatments in P. americana hindgut and midgut, respectively.
Project description:Small RNAs (21-24 nt) are pivotal regulators of gene expression that guide both transcriptional and post-transcriptional silencing mechanisms in diverse eukaryotes, including most if not all plants. MicroRNAs (miRNAs) and short interfering RNAs (siRNAs) are the two major types, both of which have a demonstrated and important role in plant development, stress responses and pathogen resistance. In this work, we used a deep sequencing approach (Sequencing-By-Synthesis, or SBS) to develop sequence resources of small RNAs from Persea americana tissues (including leaves, flowers and fruit). The high depth of the resulting datasets enabled us to examine in detail critical small RNA features as size distribution, tissue-specific regulation and sequence conservation between different organs in this species. We also developed database resources and a dedicated website (http://smallrna.udel.edu/) with computational tools for allowing other users to identify new miRNAs or siRNAs involved in specific regulatory pathways, verify the degree of conservation of these sequences in other plant species and map small RNAs on genes or larger regions of the maize genome under study. Small RNA libraries were derived from leaves, flowers and fruit of Persea americana. Total RNA was isolated using the Plant RNA Purification Reagent (Invitrogen), and submitted to Illumina (Hayward, CA, http://www.illumina.com) for small RNA library construction using approaches described in (Lu et al., 2007) with minor modifications. The small RNA libraries were sequenced with the Sequencing-By-Synthesis (SBS) technology by Illumina. PERL scripts were designed to remove the adapter sequences and determine the abundance of each distinct small RNA. We thank Doug Soltis for providing the plant material as well as Kan Nobuta and Gayathri Mahalingam for assistance with the computational methods.