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Eric Alm

Publications and source records attributed to Eric Alm.

9 recordsLinked to original sources

The evolution of two-component systems in bacteria reveals different strategies for niche adaptation.

Two-component systems including histidine protein kinases represent the primary signal transduction paradigm in prokaryotic organisms. To understand how these systems adapt to allow organisms to detect niche-specific signals, we analyzed the phylogenetic distribution of nearly 5,000 histidine protein kinases from 207 sequenced prokaryotic genomes. We found that many genomes carry a large repertoire of recently evolved signaling genes, which may reflect selective pressure to adapt to new environmental conditions. Both lineage-specific gene family expansion and horizontal gene transfer play major roles in the introduction of new histidine kinases into genomes; however, there are differences in how these two evolutionary forces act. Genes imported via horizontal transfer are more likely to retain their original functionality as inferred from a similar complement of signaling domains, while gene family expansion accompanied by domain shuffling appears to be a major source of novel genetic diversity. Family expansion is the dominant source of new histidine kinase genes in the genomes most enriched in signaling proteins, and detailed analysis reveals that divergence in domain structure and changes in expression patterns are hallmarks of recent expansions. Finally, while these two modes of gene acquisition are widespread across bacterial taxa, there are clear species-specific preferences for which mode is used.

Adaptation, Physiological↗

Cellular response of Shewanella oneidensis to strontium stress.

The physiology and transcriptome dynamics of the metal ion-reducing bacterium Shewanella oneidensis strain MR-1 in response to nonradioactive strontium (Sr) exposure were investigated. Studies indicated that MR-1 was able to grow aerobically in complex medium in the presence of 180 mM SrCl2 but showed severe growth inhibition at levels above that concentration. Temporal gene expression profiles were generated from aerobically grown, mid-exponential-phase MR-1 cells shocked with 180 mM SrCl2 and analyzed for significant differences in mRNA abundance with reference to data for nonstressed MR-1 cells. Genes with annotated functions in siderophore biosynthesis and iron transport were among the most highly induced (>100-fold [P < 0.05]) open reading frames in response to acute Sr stress, and a mutant (SO3032::pKNOCK) defective in siderophore production was found to be hypersensitive to SrCl2 exposure, compared to parental and wild-type strains. Transcripts encoding multidrug and heavy metal efflux pumps, proteins involved in osmotic adaptation, sulfate ABC transporters, and assimilative sulfur metabolism enzymes also were differentially expressed following Sr exposure but at levels that were several orders of magnitude lower than those for iron transport genes. Precipitate formation was observed during aerobic growth of MR-1 in broth cultures amended with 50, 100, or 150 mM SrCl2 but not in cultures of the SO3032::pKNOCK mutant or in the abiotic control. Chemical analysis of this precipitate using laser-induced breakdown spectroscopy and static secondary ion mass spectrometry indicated extracellular solid-phase sequestration of Sr, with at least a portion of the heavy metal associated with carbonate phases.

Bacterial Proteins↗

Transcriptome profiling of Shewanella oneidensis gene expression following exposure to acidic and alkaline pH.

The molecular response of Shewanella oneidensis MR-1 to variations in extracellular pH was investigated based on genomewide gene expression profiling. Microarray analysis revealed that cells elicited both general and specific transcriptome responses when challenged with environmental acid (pH 4) or base (pH 10) conditions over a 60-min period. Global responses included the differential expression of genes functionally linked to amino acid metabolism, transcriptional regulation and signal transduction, transport, cell membrane structure, and oxidative stress protection. Response to acid stress included the elevated expression of genes encoding glycogen biosynthetic enzymes, phosphate transporters, and the RNA polymerase sigma-38 factor (rpoS), whereas the molecular response to alkaline pH was characterized by upregulation of nhaA and nhaR, which are predicted to encode an Na+/H+ antiporter and transcriptional activator, respectively, as well as sulfate transport and sulfur metabolism genes. Collectively, these results suggest that S. oneidensis modulates multiple transporters, cell envelope components, and pathways of amino acid consumption and central intermediary metabolism as part of its transcriptome response to changing external pH conditions.

Acids↗

Transcriptome analysis of Shewanella oneidensis MR-1 in response to elevated salt conditions.

Whole-genomic expression patterns were examined in Shewanella oneidensis cells exposed to elevated sodium chloride. Genes involved in Na(+) extrusion and glutamate biosynthesis were significantly up-regulated, and the majority of chemotaxis/motility-related genes were significantly down-regulated. The data also suggested an important role for metabolic adjustment in salt stress adaptation in S. oneidensis.

Adaptation, Physiological↗

Reconstruction of regulatory and metabolic pathways in metal-reducing delta-proteobacteria.

BACKGROUND: Relatively little is known about the genetic basis for the unique physiology of metal-reducing genera in the delta subgroup of the proteobacteria. The recent availability of complete finished or draft-quality genome sequences for seven representatives allowed us to investigate the genetic and regulatory factors in a number of key pathways involved in the biosynthesis of building blocks and cofactors, metal-ion homeostasis, stress response, and energy metabolism using a combination of regulatory sequence detection and analysis of genomic context. RESULTS: In the genomes of delta-proteobacteria, we identified candidate binding sites for four regulators of known specificity (BirA, CooA, HrcA, sigma-32), four types of metabolite-binding riboswitches (RFN-, THI-, B12-elements and S-box), and new binding sites for the FUR, ModE, NikR, PerR, and ZUR transcription factors, as well as for the previously uncharacterized factors HcpR and LysX. After reconstruction of the corresponding metabolic pathways and regulatory interactions, we identified possible functions for a large number of previously uncharacterized genes covering a wide range of cellular functions. CONCLUSIONS: Phylogenetically diverse delta-proteobacteria appear to have homologous regulatory components. This study for the first time demonstrates the adaptability of the comparative genomic approach to de novo reconstruction of a regulatory network in a poorly studied taxonomic group of bacteria. Recent efforts in large-scale functional genomic characterization of Desulfovibrio species will provide a unique opportunity to test and expand our predictions.

Bacterial Proteins↗

Global transcriptome analysis of the heat shock response of Shewanella oneidensis.

Shewanella oneidensis is an important model organism for bioremediation studies because of its diverse respiratory capabilities. However, the genetic basis and regulatory mechanisms underlying the ability of S. oneidensis to survive and adapt to various environmentally relevant stresses is poorly understood. To define this organism's molecular response to elevated growth temperatures, temporal gene expression profiles were examined in cells subjected to heat stress by using whole-genome DNA microarrays for S. oneidensis. Approximately 15% (n = 711) of the total predicted S. oneidensis genes (n = 4,648) represented on the microarray were significantly up- or downregulated (P < 0.05) over a 25-min period after shift to the heat shock temperature. As expected, the majority of the genes that showed homology to known chaperones and heat shock proteins in other organisms were highly induced. In addition, a number of predicted genes, including those encoding enzymes in glycolysis and the pentose cycle, serine proteases, transcriptional regulators (MerR, LysR, and TetR families), histidine kinases, and hypothetical proteins were induced. Genes encoding membrane proteins were differentially expressed, suggesting that cells possibly alter their membrane composition or structure in response to variations in growth temperature. A substantial number of the genes encoding ribosomal proteins displayed downregulated coexpression patterns in response to heat stress, as did genes encoding prophage and flagellar proteins. Finally, a putative regulatory site with high conservation to the Escherichia coli sigma32-binding consensus sequence was identified upstream of a number of heat-inducible genes.

Bacterial Proteins↗

Biological networks.

Recent advances in high-throughput methods have provided us with a first glimpse of the overall structure of molecular interaction networks in biological systems. Ultimately, we expect that such information will change how we think about biological systems in a fundamental way. Instead of viewing the genetic parts list of an organism as a loose collection of biochemical activities, in the best case, we anticipate discrete networks of function to bridge the gap between genotype and phenotype, and to do so in a more profound way than the current qualitative classification of linked reactions into familiar pathways, such as glycolysis and the MAPK signal transduction cascades. At the present time, however, we are still far from a complete answer to the most basic question: what can we learn about biology by studying networks? Promising steps in this direction have come from such diverse approaches as mathematical analysis of global network structure, partitioning networks into functionally related modules and motifs, and even de novo design of networks. A complete picture will probably require integrating the data obtained from all of these approaches with modeling efforts at many different levels of detail.

Amino Acid Motifs↗

Contact order revisited: influence of protein size on the folding rate.

Guided by the recent success of empirical model predicting the folding rates of small two-state folding proteins from the relative contact order (CO) of their native structures, by a theoretical model of protein folding that predicts that logarithm of the folding rate decreases with the protein chain length L as L(2/3), and by the finding that the folding rates of multistate folding proteins strongly correlate with their sizes and have very bad correlation with CO, we reexamined the dependence of folding rate on CO and L in attempt to find a structural parameter that determines folding rates for the totality of proteins. We show that the Abs_CO = CO x L, is able to predict rather accurately folding rates for both two-state and multistate folding proteins, as well as short peptides, and that this Abs_CO scales with the protein chain length as L(0.70 +/- 0.07) for the totality of studied single-domain proteins and peptides.

Animals↗

Simple physical models connect theory and experiment in protein folding kinetics.

Our understanding of the principles underlying the protein-folding problem can be tested by developing and characterizing simple models that make predictions which can be compared to experimental data. Here we extend our earlier model of folding free energy landscapes, in which each residue is considered to be either folded as in the native state or completely disordered, by investigating the role of additional factors representing hydrogen bonding and backbone torsion strain, and by using a hybrid between the master equation approach and the simple transition state theory to evaluate kinetics near the free energy barrier in greater detail. Model calculations of folding phi-values are compared to experimental data for 19 proteins, and for more than half of these, experimental data are reproduced with correlation coefficients between r=0.41 and 0.88; calculations of transition state free energy barriers correlate with rates measured for 37 single domain proteins (r=0.69). The model provides insight into the contribution of alternative-folding pathways, the validity of quasi-equilibrium treatments of the folding landscape, and the magnitude of the Arrhenius prefactor for protein folding. Finally, we discuss the limitations of simple native-state-based models, and as a more general test of such models, provide predictions of folding rates and mechanisms for a comprehensive set of over 400 small protein domains of known structure.

Bacterial Proteins↗