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Eric J Alm

Publications and source records attributed to Eric J Alm.

11 recordsLinked to original sources
PubMed2024

Environmental stress mediates groundwater microbial community assembly.

Community assembly describes how different ecological processes shape microbial community composition and structure. How environmental factors impact community assembly remains elusive. Here we sampled microbial communities and >200 biogeochemical variables in groundwater at the Oak Ridge Field Research Center, a former nuclear waste disposal site, and developed a theoretical framework to conceptualize the relationships between community assembly processes and environmental stresses. We found that stochastic assembly processes were critical (>60% on average) in shaping community structure, but their relative importance decreased as stress increased. Dispersal limitation and 'drift' related to random birth and death had negative correlations with stresses, whereas the selection processes leading to dissimilar communities increased with stresses, primarily related to pH, cobalt and molybdenum. Assembly mechanisms also varied greatly among different phylogenetic groups. Our findings highlight the importance of microbial dispersal limitation and environmental heterogeneity in ecosystem restoration and management.

Phylogeny↗
PubMed2006

The life-cycle of operons.

Operons are a major feature of all prokaryotic genomes, but how and why operon structures vary is not well understood. To elucidate the life-cycle of operons, we compared gene order between Escherichia coli K12 and its relatives and identified the recently formed and destroyed operons in E. coli. This allowed us to determine how operons form, how they become closely spaced, and how they die. Our findings suggest that operon evolution may be driven by selection on gene expression patterns. First, both operon creation and operon destruction lead to large changes in gene expression patterns. For example, the removal of lysA and ruvA from ancestral operons that contained essential genes allowed their expression to respond to lysine levels and DNA damage, respectively. Second, some operons have undergone accelerated evolution, with multiple new genes being added during a brief period. Third, although genes within operons are usually closely spaced because of a neutral bias toward deletion and because of selection against large overlaps, genes in highly expressed operons tend to be widely spaced because of regulatory fine-tuning by intervening sequences. Although operon evolution may be adaptive, it need not be optimal: new operons often comprise functionally unrelated genes that were already in proximity before the operon formed.

Bacillus subtilis↗
PubMed2006

OpWise: operons aid the identification of differentially expressed genes in bacterial microarray experiments.

BACKGROUND: Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no systematic errors in the data even though several sources of systematic error are known. RESULTS: OpWise estimates the amount of systematic error in bacterial microarray data by assuming that genes in the same operon have matching expression patterns. OpWise then performs a Bayesian analysis of a linear model to estimate significance. In simulations, OpWise corrects for systematic error and is robust to deviations from its assumptions. In several bacterial data sets, significant amounts of systematic error are present, and replicate-based approaches overstate the confidence of the changers dramatically, while OpWise does not. Finally, OpWise can identify additional changers by assigning genes higher confidence if they are consistent with other genes in the same operon. CONCLUSION: Although microarray data can contain large amounts of systematic error, operons provide an external standard and allow for reasonable estimates of significance. OpWise is available at http://microbesonline.org/OpWise.

Algorithms↗
PubMed2006

Energetic consequences of nitrite stress in Desulfovibrio vulgaris Hildenborough, inferred from global transcriptional analysis.

Many of the proteins that are candidates for bioenergetic pathways involved with sulfate respiration in Desulfovibrio spp. have been studied, but complete pathways and overall cell physiology remain to be resolved for many environmentally relevant conditions. In order to understand the metabolism of these microorganisms under adverse environmental conditions for improved bioremediation efforts, Desulfovibrio vulgaris Hildenborough was used as a model organism to study stress response to nitrite, an important intermediate in the nitrogen cycle. Previous physiological studies demonstrated that growth was inhibited by nitrite and that nitrite reduction was observed to be the primary mechanism of detoxification. Global transcriptional profiling with whole-genome microarrays revealed coordinated cascades of responses to nitrite in pathways of energy metabolism, nitrogen metabolism, oxidative stress response, and iron homeostasis. In agreement with previous observations, nitrite-stressed cells showed a decrease in the expression of genes encoding sulfate reduction functions in addition to respiratory oxidative phosphorylation and ATP synthase activity. Consequently, the stressed cells had decreased expression of the genes encoding ATP-dependent amino acid transporters and proteins involved in translation. Other genes up-regulated in response to nitrite include the genes in the Fur regulon, which is suggested to be involved in iron homeostasis, and genes in the Per regulon, which is predicted to be responsible for oxidative stress response.

Desulfovibrio vulgaris↗
PubMed2006

Salt stress in Desulfovibrio vulgaris Hildenborough: an integrated genomics approach.

The ability of Desulfovibrio vulgaris Hildenborough to reduce, and therefore contain, toxic and radioactive metal waste has made all factors that affect the physiology of this organism of great interest. Increased salinity is an important and frequent fluctuation faced by D. vulgaris in its natural habitat. In liquid culture, exposure to excess salt resulted in striking elongation of D. vulgaris cells. Using data from transcriptomics, proteomics, metabolite assays, phospholipid fatty acid profiling, and electron microscopy, we used a systems approach to explore the effects of excess NaCl on D. vulgaris. In this study we demonstrated that import of osmoprotectants, such as glycine betaine and ectoine, is the primary mechanism used by D. vulgaris to counter hyperionic stress. Several efflux systems were also highly up-regulated, as was the ATP synthesis pathway. Increases in the levels of both RNA and DNA helicases suggested that salt stress affected the stability of nucleic acid base pairing. An overall increase in the level of branched fatty acids indicated that there were changes in cell wall fluidity. The immediate response to salt stress included up-regulation of chemotaxis genes, although flagellar biosynthesis was down-regulated. Other down-regulated systems included lactate uptake permeases and ABC transport systems. The results of an extensive NaCl stress analysis were compared with microarray data from a KCl stress analysis, and unlike many other bacteria, D. vulgaris responded similarly to the two stresses. Integration of data from multiple methods allowed us to develop a conceptual model for the salt stress response in D. vulgaris that can be compared to those in other microorganisms.

Bacterial Proteins↗
PubMed2005

Dissimilatory metabolism of nitrogen oxides in bacteria: comparative reconstruction of transcriptional networks.

Bacterial response to nitric oxide (NO) is of major importance since NO is an obligatory intermediate of the nitrogen cycle. Transcriptional regulation of the dissimilatory nitric oxides metabolism in bacteria is diverse and involves FNR-like transcription factors HcpR, DNR, and NnrR; two-component systems NarXL and NarQP; NO-responsive activator NorR; and nitrite-sensitive repressor NsrR. Using comparative genomics approaches, we predict DNA-binding motifs for these transcriptional factors and describe corresponding regulons in available bacterial genomes. Within the FNR family of regulators, we observed a correlation of two specificity-determining amino acids and contacting bases in corresponding DNA recognition motif. Highly conserved regulon HcpR for the hybrid cluster protein and some other redox enzymes is present in diverse anaerobic bacteria, including Clostridia, Thermotogales, and delta-proteobacteria. NnrR and DNR control denitrification in alpha- and beta-proteobacteria, respectively. Sigma-54-dependent NorR regulon found in some gamma- and beta-proteobacteria contains various enzymes involved in the NO detoxification. Repressor NsrR, which was previously known to control only nitrite reductase operon in Nitrosomonas spp., appears to be the master regulator of the nitric oxides' metabolism, not only in most gamma- and beta-proteobacteria (including well-studied species such as Escherichia coli), but also in gram-positive Bacillus and Streptomyces species. Positional analysis and comparison of regulatory regions of NO detoxification genes allows us to propose the candidate NsrR-binding motif. The most conserved member of the predicted NsrR regulon is the NO-detoxifying flavohemoglobin Hmp. In enterobacteria, the regulon also includes two nitrite-responsive loci, nipAB (hcp-hcr) and nipC (dnrN), thus confirming the identity of the effector, i.e. nitrite. The proposed NsrR regulons in Neisseria and some other species are extended to include denitrification genes. As the result, we demonstrate considerable interconnection between various nitrogen-oxides-responsive regulatory systems for the denitrification and NO detoxification genes and evolutionary plasticity of this transcriptional network.

Amino Acid Motifs↗
PubMed2005

Interruptions in gene expression drive highly expressed operons to the leading strand of DNA replication.

In bacteria, most genes are on the leading strand of replication, a phenomenon attributed to collisions between the DNA and RNA polymerases. In Escherichia coli, these collisions slow the movement of the replication fork through actively transcribed genes only if they are coded on the lagging strand. For genes on both strands, however, these collisions sever nascent transcripts and interrupt gene expression. Based on these observations, we propose a new theory to explain strand bias: genes whose expression is important for fitness are selected to the leading strand because this reduces the duration of these interruptions. Our theory predicts that multi-gene operons, which are subject to longer interruptions, should be more strongly selected to the leading strand than singleton transcripts. We show that this is true even after controlling for the tendency for essential genes, which are strongly biased to the leading strand, to occur in operons. Our theory also predicts that other factors that are associated with strand bias should have stronger effects for genes that are in operons. We find that expression level and phylogenetic ubiquity are correlated with strand bias for both essential and non-essential genes, but only for genes in operons.

DNA Replication↗
PubMed2005

A novel method for accurate operon predictions in all sequenced prokaryotes.

We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacter pylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, and its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from six phylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC 6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.

Base Sequence↗
PubMed2005

Operon formation is driven by co-regulation and not by horizontal gene transfer.

The organization of bacterial genes into operons was originally ascribed to the benefits of co-regulation. More recently, the "selfish operon" model, in which operons are formed by repeated gain and loss of genes, was proposed. Indeed, operons are often subject to horizontal gene transfer (HGT). On the other hand, non-HGT genes are particularly likely to be in operons. To clarify whether HGT is involved in operon formation, we identified recently formed operons in Escherichia coli K12. We show that genes that have homologs in distantly related bacteria but not in close relatives of E. coli--indicating HGT--form new operons at about the same rates as native genes. Furthermore, genes in new operons are no more likely than other genes to have phylogenetic trees that are inconsistent with the species tree. In contrast, essential genes and ubiquitous genes without paralogs--genes believed to undergo HGT rarely--often form new operons. We conclude that HGT is not a cause of operon formation but instead promotes the prevalence of pre-existing operons. To explain operon formation, we propose that new operons reduce the amount of regulatory information required to specify optimal expression patterns and infer that operons should be more likely to evolve than independent promoters when regulation is complex. Consistent with this hypothesis, operons have greater amounts of conserved regulatory sequences than do individually transcribed genes.

Escherichia coli K12↗
PubMed2005

The MicrobesOnline Web site for comparative genomics.

At present, hundreds of microbial genomes have been sequenced, and hundreds more are currently in the pipeline. The Virtual Institute for Microbial Stress and Survival has developed a publicly available suite of Web-based comparative genomic tools (http://www.microbesonline.org) designed to facilitate multispecies comparison among prokaryotes. Highlights of the MicrobesOnline Web site include operon and regulon predictions, a multispecies genome browser, a multispecies Gene Ontology browser, a comparative KEGG metabolic pathway viewer, a Bioinformatics Workbench for in-depth sequence analysis, and Gene Carts that allow users to save genes of interest for further study while they browse. In addition, we provide an interface for genome annotation, which like all of the tools reported here, is freely available to the scientific community.

Animals↗