Corey M. Hudson

Resistance determinants and mobile genetic elements of an NDM-1-encoding Klebsiella pneumoniae strain.

Multidrug-resistant Enterobacteriaceae are emerging as a serious infectious disease challenge. These strains can accumulate many antibiotic resistance genes though horizontal transfer of genetic elements, those for β-lactamases being of particular concern. Some β-lactamases are active on a broad spectrum of β-lactams including the last-resort carbapenems. The gene for the broad-spectrum and carbapenem-active metallo-β-lactamase NDM-1 is rapidly spreading. We present the complete genome of Klebsiella pneumoniae ATCC BAA-2146, the first U.S. isolate found to encode NDM-1, and describe its repertoire of antibiotic-resistance genes and mutations, including genes for eight β-lactamases and 15 additional antibiotic-resistance enzymes. To elucidate the evolution of this rich repertoire, the mobile elements of the genome were characterized, including four plasmids with varying degrees of conservation and mosaicism and eleven chromosomal genomic islands. One island was identified by a novel phylogenomic approach, that further indicated the cps-lps polysaccharide synthesis locus, where operon translocation and fusion was noted. Unique plasmid segments and mosaic junctions were identified. Plasmid-borne bla CTX-M-15 was transposed recently to the chromosome by ISEcp1. None of the eleven full copies of IS26, the most frequent IS element in the genome, had the expected 8-bp direct repeat of the integration target sequence, suggesting that each copy underwent homologous recombination subsequent to its last transposition event. Comparative analysis likewise indicates IS26 as a frequent recombinational junction between plasmid ancestors, and also indicates a resolvase site. In one novel use of high-throughput sequencing, homologously recombinant subpopulations of the bacterial culture were detected. In a second novel use, circular transposition intermediates were detected for the novel insertion sequence ISKpn21 of the ISNCY family, suggesting that it uses the two-step transposition mechanism of IS3. Robust genome-based phylogeny showed that a unified Klebsiella cluster contains Enterobacter aerogenes and Raoultella, suggesting the latter genus should be abandoned.

Expression level, cellular compartment and metabolic network position all influence the average selective constraint on mammalian enzymes

BackgroundA genes position in regulatory, protein interaction or metabolic networks can be predictive of the strength of purifying selection acting on it, but these relationships are neither universal nor invariably strong. Following work in bacteria, fungi and invertebrate animals, we explore the relationship between selective constraint and metabolic function in mammals.ResultsWe measure the association between selective constraint, estimated by the ratio of nonsynonymous (Ka) to synonymous (Ks) substitutions, and several, primarily metabolic, measures of gene function. We find significant differences between the selective constraints acting on enzyme-coding genes from different cellular compartments, with the nucleus showing higher constraint than genes from either the cytoplasm or the mitochondria. Among metabolic genes, the centrality of an enzyme in the metabolic network is significantly correlated with Ka/Ks. In contrast to yeasts, gene expression magnitude does not appear to be the primary predictor of selective constraint in these organisms.ConclusionsOur results imply that the relationship between selective constraint and enzyme centrality is complex: the strength of selective constraint acting on mammalian genes is quite variable and does not appear to exclusively follow patterns seen in other organisms.

A Conserved Mammalian Protein Interaction Network

Physical interactions between proteins mediate a variety of biological functions, including signal transduction, physical structuring of the cell and regulation. While extensive catalogs of such interactions are known from model organisms, their evolutionary histories are difficult to study given the lack of interaction data from phylogenetic outgroups. Using phylogenomic approaches, we infer a upper bound on the time of origin for a large set of human protein-protein interactions, showing that most such interactions appear relatively ancient, dating no later than the radiation of placental mammals. By analyzing paired alignments of orthologous and putatively interacting protein-coding genes from eight mammals, we find evidence for weak but significant co-evolution, as measured by relative selective constraint, between pairs of genes with interacting proteins. However, we find no strong evidence for shared instances of directional selection within an interacting pair. Finally, we use a network approach to show that the distribution of selective constraint across the protein interaction network is non-random, with a clear tendency for interacting proteins to share similar selective constraints. Collectively, the results suggest that, on the whole, protein interactions in mammals are under selective constraint, presumably due to their functional roles.

Yeast as a Window into Changes in Genome Complexity Due to Polyploidization

Due to the long history of genetic analyses in yeasts and their experimental tractability, the yeast genome duplication provides important perspectives on the genome and population-level processes that follow whole-genome duplication (WGD). We discuss the history of the discovery of the Saccharomyces cerevisiae WGD, with special emphasis on the role of comparative genomics in its analysis. We then explore models of the WGD shaped population and species divergence, both at a gene level (e.g., Dobzhansky-Muller incompatibility) and from the perspective of recent work on secondary allopolyploidy in Saccharomyces pastorianus. Finally, we explore the selective forces that act on the WGD-produced paralogs and shape their patterns of loss and retention. In addition to discussing the dosage balance hypothesis as it applies to the yeast WGD, we explore the role of the WGD in shaping several complex metabolic and regulatory phenotypes.

Understanding and regulation of microbial lignolysis for renewable platform chemicals

Lignin is often overlooked in the valorization of lignocellulosic biomass, but lignin-based materials and chemicals represent potential value-added products for biorefineries that could significantly improve the economics of a biorefinery. Fluctuating crude oil prices and changing fuel specifications are some of the driving factors to develop new technologies that could be used to convert polymeric lignin into low molecular weight lignin and or monomeric aromatic feedstocks to assist in the displacement of the current products associated with the conversion of a whole barrel of oil. Our project of understanding microbial lignolysis for renewable platform chemicals aimed to understand microbial and enzymatic lignolysis processes to break down lignin for conversion into commercially viable drop-in fuels. We developed novel lignin analytics to interrogate enzymatic and microbial lignolysis of native polymeric lignin and established a detailed understanding of lignolysis as a function of fungal enzyme, microbes and endophytes. Bioinformatics pipeline was developed for metatranscryptomic analysis of aridland ecosystem for investigating the potential discovery of new lignolysis gene and gene products.