Over the years, IGBB scientists have gained a reputation for publishing papers that are widely cited. Below are papers that are (a) authored/co-authored by an IGBB employee, faculty fellow, or affiliate and (b) fall within the top ten percent of scientific publications with regard to citation impact. Citation benchmarking values are from Scopus. Papers in the 99th percentile are in the top 1% globally. Citation benchmarking takes into account
the date of publication, the document type, and discipline-specific factors. For a particular IGBB fellow/affiliate/staff member, only those papers published while at MS State are included. The list below is updated periodically.
ABSTRACT In this mini-review, recent advances in plant developmental proteomics are summarized. The growing interest in plant proteomics continually produces large numbers of developmental studies on plant cell division, elongation, differentiation, and formation of various organs. The brief overview of changes in proteome profiles emphasizes the participation of stress-related proteins in all developmental processes, which substantially changes the view on functional classification of these proteins. Next, it is noteworthy that proteomics helped to recognize some metabolic and housekeeping proteins as important signaling inducers of developmental pathways. Further, cell division and elongation are dependent on proteins involved in membrane trafficking and cytoskeleton dynamics. These protein groups are less prevalently represented in studies concerning cell differentiation and organ formation, which do not target primarily cell division. The synthesis of new proteins, generally observed during developmental processes, is followed by active protein folding. In this respect, disulfide isomerase was found to be commonly up-regulated during several developmental processes. The future progress in plant proteomics requires new and/or complementary approaches including cell fractionation, specific chemical treatments, molecular cloning and subcellular localization of proteins combined with more sensitive methods for protein detection and identification. -¬ 2011 Elsevier B.V.
ProtQuant: a tool for the label-free quantification of MudPIT proteomics data
IGBB Authors: Susan M. Bridges, Shane C. Burgess, Bindu Nanduri
Bridges SM, Magee GB, Wang N, Williams WP, Burgess SC, Nanduri B (2007) ProtQuant: a tool for the label-free quantification of MudPIT proteomics data. BMC Bioinformatics 8(Suppl 7): S24.
ABSTRACT BACKGROUND: Effective and economical methods for quantitative analysis of high throughput mass spectrometry data are essential to meet the goals of directly identifying, characterizing, and quantifying proteins from a particular cell state. Multidimensional Protein Identification Technology (MudPIT) is a common approach used in protein identification. Two types of methods are used to detect differential protein expression in MudPIT experiments: those involving stable isotope labelling and the so-called label-free methods. Label-free methods are based on the relationship between protein abundance and sampling statistics such as peptide count, spectral count, probabilistic peptide identification scores, and sum of peptide Sequest XCorr scores (SigmaXCorr). Although a number of label-free methods for protein quantification have been described in the literature, there are few publicly available tools that implement these methods. We describe ProtQuant, a Java-based tool for label-free protein quantification that uses the previously published SigmaXCorr method for quantification and includes an improved method for handling missing data. RESULTS: ProtQuant was designed for ease of use and portability for the bench scientist. It implements the SigmaXCorr method for label free protein quantification from MudPIT datasets. ProtQuant has a graphical user interface, accepts multiple file formats, is not limited by the size of the input files, and can process any number of replicates and any number of treatments. In addition, ProtQuant implements a new method for dealing with missing values for peptide scores used for quantification. The new algorithm, called SigmaXCorr.
Proteomic analysis using an unfinished bacterial genome: the effects of subminimum inhibitory concentrations of antibiotics on Mannheimia haemolytica virulence factor expression
IGBB Authors: Bindu Nanduri, Mark L. Lawrence, Shane C. Burgess
Nanduri B, Lawrence ML, Vanguri S, Burgess SC (2005) Proteomic analysis using an unfinished bacterial genome: the effects of subminimum inhibitory concentrations of antibiotics on Mannheimia haemolytica virulence factor expression. Proteomics 5(18): 4852-4863.
ABSTRACT Here we identify, using nonelectrophoretic proteomics, effects of subminimum inhibitory concentrations (subMIC) of two antibiotic preparations, chlortetracycline (CTC), and chlortetracycline-sulfamethazine (CTC + SMZ), on protein expression in the bovine respiratory pathogen Mannheimia haemolytica. The M. haemolytica genome is currently in draft form, and annotation is incomplete. Relying on the principle of gene sequence conservation across species, we used annotated genomes from closely related species to identify, confirm, and functionally annotate 495 M. haemolytica proteins. To conduct quantitative comparative proteomics, we developed a protein quantitation method based on the cross correlation function of the SEQUEST algorithm. When M. haemolytica was cultivated in the presence of 1/4 MIC of CTC and CTC + SMZ, expression of proteins involved in energy production, nucleotide metabolism, translation, and the bacterial stress response (chaperones) were affected. The most notable subMIC effect was a significant decrease in the expression of leukotoxin A, which is an important M. haemolytica virulence factor. Reduction in leukotoxin expression could be one of the molecular mechanisms responsible for the efficacy of these antibiotics against bovine respiratory disease.
ABSTRACT Blackberry and raspberry are members of the family Rosaceae. They are classified in the genus Rubus, which comprises hundreds of species and has a center of origin in the Far East. Rubus is divided into 15 subgenera with blackberries classified in the Rubus (formerly Eubatus) and raspberries in the Idaeobatus subgenera. Rubus species are propagated vegetatively and are subject to infection by viruses during development, propagation, and fruit production stages. Reports of initial detection and symptoms of more than 30 viruses, virus-like diseases, and phytoplasmas affecting Rubus spp. were reviewed more than 20 years ago. Since the last review on Rubus viruses, significant progress has been made in the molecular characterization of many of the viruses that infect Rubus spp. Currently, reverse transcription–polymerase chain reaction detection methods are available for most of the viruses known to infect Rubus. The goals of this article are to update the knowledge on previously characterized viruses of Rubus, highlight recently described viruses, review the virus-induced symptoms, describe the advances made in their detection, and discuss our knowledge about several virus complexes that cause serious diseases in Rubus. Virus complexes have been identified recently as the major cause of diseases in blackberries and raspberries.
Page 9 of 9 
