Shane C Burgess

PMID: 17135208;PMCID: PMC1751552;Abstract:

Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessible, public resource 'AgBase' (www.agbase.msstate.edu). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteogenomic mapping. Proteogenomic data are available from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The 'GO Consortium' gene association file contains the most rigorous GO annotations based solely on experimental data. The 'Community' gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted annotations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely available on request. A suite of tools for analyzing functional genomics datasets using the GO is available online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations. © 2007 Oxford University Press.

PMID: 18491321;Abstract:

Understanding the growth of bacterial pathogens in a micronutrient restricted host environment can identify potential virulence proteins that help overcome this nutritional barrier to productive infection. In this study, we investigated the pneumococcal protein expression response to iron limitation using an in vitro model. We identified S. pneumoniae TIGR4 proteins by 2-D LC ESI MS/MS and determined significant changes in protein expression in response to iron restriction using computer-intensive random resampling methods. Differential protein expression was studied in the context of a S. pneumoniae TIGR4 protein interaction network using Pathway Studio. Our analysis showed that pneumococcal iron restriction response was marked by increased expression of known virulence factors like PsaA. It involved changes in the expression of stress response, and phase variation and biofilm formation proteins. The net effect of changes in all these biological processes could increase the virulence of S. pneumoniae TIGR4 during in vivo infection. © 2008 Wiley-VCH Verlag GmbH & Co. KGaA.

PMID: 20138080;Abstract:

Resistance to Marek's disease (MD) in chickens is genetically regulated and there are lines of chickens with differential susceptibility or resistance to this disease. The present study was designed to study comparative changes in the spleen proteomes of MD-susceptible B19 and MD-resistant B21 chickens in response to MDV infection. Spleen proteomes were examined at 4, 7, 14 and 21 days post-infection (d.p.i.) using two-dimensional gel electrophoresis and subsequently the protein spots were identified by one-dimensional liquid chromatography electrospray ionization tandem mass spectrometry (1D LC ESI MS/MS). On average, there were 520 ± 27 distinct protein spots on each gel and 1.6 ± 0.7% of the spots differed quantitatively in their expression (p≤ 0.05 and fold change ≥2) between infected B19 and B21 chickens. There was one spot at 4. d.p.i. and three spots each at the rest of the time points, which had a qualitative difference in expression. Most of the differentially expressed proteins at 4 and 7. d.p.i. displayed increased expression in B21 chickens; conversely the differentially expressed proteins at 14 and 21. d.p.i. showed an increase in expression in B19 chickens. The differentially expressed proteins identified in the present study included antioxidants, molecular chaperones, proteins involved in the formation of cytoskeleton, protein degradation and antigen presentation, signal transduction, protein translation and elongation, RNA processing and cell proliferation. These findings shed light on some of the underlying processes of genetic resistance or susceptibility to MD. © 2010 Elsevier Ltd.

PMID: 22276113;PMCID: PMC3262788;Abstract:

Genome structural annotation, i.e., identification and demarcation of the boundaries for all the functional elements in a genome (e.g., genes, non-coding RNAs, proteins and regulatory elements), is a prerequisite for systems level analysis. Current genome annotation programs do not identify all of the functional elements of the genome, especially small non-coding RNAs (sRNAs). Whole genome transcriptome analysis is a complementary method to identify "novel" genes, small RNAs, regulatory regions, and operon structures, thus improving the structural annotation in bacteria. In particular, the identification of non-coding RNAs has revealed their widespread occurrence and functional importance in gene regulation, stress and virulence. However, very little is known about non-coding transcripts in Histophilus somni, one of the causative agents of Bovine Respiratory Disease (BRD) as well as bovine infertility, abortion, septicemia, arthritis, myocarditis, and thrombotic meningoencephalitis. In this study, we report a single nucleotide resolution transcriptome map of H. somni strain 2336 using RNA-Seq method. The RNA-Seq based transcriptome map identified 94 sRNAs in the H. somni genome of which 82 sRNAs were never predicted or reported in earlier studies. We also identified 38 novel potential protein coding open reading frames that were absent in the current genome annotation. The transcriptome map allowed the identification of 278 operon (total 730 genes) structures in the genome. When compared with the genome sequence of a non-virulent strain 129Pt, a disproportionate number of sRNAs (~30%) were located in genomic region unique to strain 2336 (~18% of the total genome). This observation suggests that a number of the newly identified sRNAs in strain 2336 may be involved in strain-specific adaptations. © 2012 Kumar et al.