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Lee Ann McCue

Publications and source records attributed to Lee Ann McCue.

12 recordsLinked to original sources
PubMed2026

Integrating multi-omics technologies to decipher microbiome functions.

Multi-omics approaches have revolutionized our understanding of microbial communities by enabling simultaneous interrogation of genomic, transcriptomic, proteomic, and metabolomic data. The systematic integration and analysis of these deep datasets help decipher the functional roles of microbiomes, providing critical insights into microbial activities, interactions, and dynamics across diverse environments. Biological complexity makes multi-omics analysis of a single, isolated organism demanding but highly informative, yet this complexity increases further when samples comprise hundreds to thousands of individual species. As microbiome research continues to expand into clinical, environmental, and engineered systems, standardized workflows, benchmarked datasets, and community-driven initiatives are essential to ensure reproducibility, standardization and interpretability. Establishing and disseminating best practices for experimental design, data processing, and integrative analyses will be critical for maximizing comparability and scientific rigor across studies. This perspective highlights recent advances in multi-omics microbiome research, outlines key obstacles in data integration and metadata harmonization, and proposes a collaborative roadmap for scalable, FAIR-compliant multi-omics investigations and potentially disruptive Artificial Intelligence (AI) advances comparable to those of AlphaFold in the field of microbiome science.

Multiomics↗
PubMed2005

The relative inefficiency of sequence weights approaches in determining a nucleotide position weight matrix.

Approaches based upon sequence weights, to construct a position weight matrix of nucleotides from aligned inputs, are popular but little effort has been expended to measure their quality. We derive optimal sequence weights that minimize the sum of the variances of the estimators of base frequency parameters for sequences related by a phylogenetic tree. Using these we find that approaches based upon sequence weights can perform very poorly in comparison to approaches based upon a theoretically optimal maximum-likelihood method in the inference of the parameters of a position-weight matrix. Specifically, we find that among a collection of primate sequences, even an optimal sequences-weights approach is only 51% as efficient as the maximum-likelihood approach in inferences of base frequency parameters. We also show how to employ the variance estimators to obtain a greedy ordering of species for sequencing. Application of this ordering for the weighted estimators to a primate collection yields a curve with a long plateau that is not observed with maximum-likelihood estimators. This plateau indicates that the use of weighted estimators on these data seriously limits the utility of obtaining the sequences of more than two or three additional species.

Journal Article↗
PubMed2005

Making connections between novel transcription factors and their DNA motifs.

The key components of a transcriptional regulatory network are the connections between trans-acting transcription factors and cis-acting DNA-binding sites. In spite of several decades of intense research, only a fraction of the estimated approximately 300 transcription factors in Escherichia coli have been linked to some of their binding sites in the genome. In this paper, we present a computational method to connect novel transcription factors and DNA motifs in E. coli. Our method uses three types of mutually independent information, two of which are gleaned by comparative analysis of multiple genomes and the third one derived from similarities of transcription-factor-DNA-binding-site interactions. The different types of information are combined to calculate the probability of a given transcription-factor-DNA-motif pair being a true pair. Tested on a study set of transcription factors and their DNA motifs, our method has a prediction accuracy of 59% for the top predictions and 85% for the top three predictions. When applied to 99 novel transcription factors and 70 novel DNA motifs, our method predicted 64 transcription-factor-DNA-motif pairs. Supporting evidence for some of the predicted pairs is presented. Functional annotations are made for 23 novel transcription factors based on the predicted transcription-factor-DNA-motif connections.

Algorithms↗
PubMed2005

Rhodopseudomonas palustris regulons detected by cross-species analysis of alphaproteobacterial genomes.

Rhodopseudomonas palustris, an alpha-proteobacterium, carries out three of the chemical reactions that support life on this planet: the conversion of sunlight to chemical-potential energy; the absorption of carbon dioxide, which it converts to cellular material; and the fixation of atmospheric nitrogen into ammonia. Insight into the transcription-regulatory network that coordinates these processes is fundamental to understanding the biology of this versatile bacterium. With this goal in mind, we predicted regulatory signals genomewide, using a two-step phylogenetic-footprinting and clustering process that we had developed previously. In the first step, 4,963 putative transcription factor binding sites, upstream of 2,044 genes and operons, were identified using cross-species Gibbs sampling. Bayesian motif clustering was then employed to group the cross-species motifs into regulons. We have identified 101 putative regulons in R. palustris, including 8 that are of particular interest: a photosynthetic regulon, a flagellar regulon, an organic hydroperoxide resistance regulon, the LexA regulon, and four regulons related to nitrogen metabolism (FixK2, NnrR, NtrC, and sigma54). In some cases, clustering allowed us to assign functions to proteins that previously had been annotated with only putative functions; we have identified RPA0828 as the organic hydroperoxide resistance regulator and RPA1026 as a cell cycle methylase. In addition to predicting regulons, we identified a novel inverted repeat that likely forms a highly conserved stem-loop and that occurs downstream of over 100 genes.

Alphaproteobacteria↗
PubMed2005

Characterization of Mycobacterium tuberculosis Rv3676 (CRPMt), a cyclic AMP receptor protein-like DNA binding protein.

Little is known about cyclic AMP (cAMP) function in Mycobacterium tuberculosis, despite its ability to encode 15 adenylate cyclases and 10 cNMP-binding proteins. M. tuberculosis Rv3676, which we have designated CRP(Mt), is predicted to be a cAMP-dependent transcription factor. In this study, we characterized CRP(Mt)'s interactions with DNA and cAMP, using experimental and computational approaches. We used Gibbs sampling to define a CRP(Mt) DNA motif that resembles the cAMP receptor protein (CRP) binding motif model for Escherichia coli. CRP(Mt) binding sites were identified in a total of 73 promoter regions regulating 114 genes in the M. tuberculosis genome, which are being explored as a regulon. Specific CRP(Mt) binding caused DNA bending, and the substitution of highly conserved nucleotides in the binding site resulted in a complete loss of binding to CRP(Mt). cAMP enhanced CRP(Mt)'s ability to bind DNA and caused allosteric alterations in CRP(Mt) conformation. These results provide the first direct evidence for cAMP binding to a transcription factor in M. tuberculosis, suggesting a role for cAMP signal transduction in M. tuberculosis and implicating CRP(Mt) as a cAMP-responsive global regulator.

Bacterial Proteins↗
PubMed2004

Transcriptomic and proteomic characterization of the Fur modulon in the metal-reducing bacterium Shewanella oneidensis.

The availability of the complete genome sequence for Shewanella oneidensis MR-1 has permitted a comprehensive characterization of the ferric uptake regulator (Fur) modulon in this dissimilatory metal-reducing bacterium. We have employed targeted gene mutagenesis, DNA microarrays, proteomic analysis using liquid chromatography-mass spectrometry, and computational motif discovery tools to define the S. oneidensis Fur regulon. Using this integrated approach, we identified nine probable operons (containing 24 genes) and 15 individual open reading frames (ORFs), either with unknown functions or encoding products annotated as transport or binding proteins, that are predicted to be direct targets of Fur-mediated repression. This study suggested, for the first time, possible roles for four operons and eight ORFs with unknown functions in iron metabolism or iron transport-related functions. Proteomic analysis clearly identified a number of transporters, binding proteins, and receptors related to iron uptake that were up-regulated in response to a fur deletion and verified the expression of nine genes originally annotated as pseudogenes. Comparison of the transcriptome and proteome data revealed strong correlation for genes shown to be undergoing large changes at the transcript level. A number of genes encoding components of the electron transport system were also differentially expressed in a fur deletion mutant. The gene omcA (SO1779), which encodes a decaheme cytochrome c, exhibited significant decreases in both mRNA and protein abundance in the fur mutant and possessed a strong candidate Fur-binding site in its upstream region, thus suggesting that omcA may be a direct target of Fur activation.

Bacterial Proteins↗
PubMed2003

Identification of co-regulated genes through Bayesian clustering of predicted regulatory binding sites.

The identification of co-regulated genes and their transcription-factor binding sites (TFBS) are key steps toward understanding transcription regulation. In addition to effective laboratory assays, various computational approaches for the detection of TFBS in promoter regions of coexpressed genes have been developed. The availability of complete genome sequences combined with the likelihood that transcription factors and their cognate sites are often conserved during evolution has led to the development of phylogenetic footprinting. The modus operandi of this technique is to search for conserved motifs upstream of orthologous genes from closely related species. The method can identify hundreds of TFBS without prior knowledge of co-regulation or coexpression. Because many of these predicted sites are likely to be bound by the same transcription factor, motifs with similar patterns can be put into clusters so as to infer the sets of co-regulated genes, that is, the regulons. This strategy utilizes only genome sequence information and is complementary to and confirmative of gene expression data generated by microarray experiments. However, the limited data available to characterize individual binding patterns, the variation in motif alignment, motif width, and base conservation, and the lack of knowledge of the number and sizes of regulons make this inference problem difficult. We have developed a Gibbs sampling-based Bayesian motif clustering (BMC) algorithm to address these challenges. Tests on simulated data sets show that BMC produces many fewer errors than hierarchical and K-means clustering methods. The application of BMC to hundreds of predicted gamma-proteobacterial motifs correctly identified many experimentally reported regulons, inferred the existence of previously unreported members of these regulons, and suggested novel regulons.

Algorithms↗
PubMed2003

A family of acr-coregulated Mycobacterium tuberculosis genes shares a common DNA motif and requires Rv3133c (dosR or devR) for expression.

Previous work has shown that the divergently transcribed Mycobacterium tuberculosis genes acr (hspX, Rv2031c) and acg (Rv2032) are induced under conditions of shallow standing culture and low oxygen and intracellularly within macrophages. We used a combination of computational and experimental methods to identify promoters for eight additional genes that are regulated in a similar manner and that comprise an acr-coregulated promoter (ACP) family. Transcriptional regulation of these ACP family members was evaluated by using a plasmid-based promoter-green fluorescent protein fusion system and flow cytometry. All promoters showed increased expression in shallow standing versus shaking cultures, in low- versus high-oxygen conditions, and intracellularly within macrophages versus extracellularly in tissue culture medium. However, there were quantitative differences in expression among promoters and among conditions for each promoter. A conserved 18-bp palindromic sequence motif was identified in all ACPs by Gibbs sampling-based computational analyses. Two such motifs overlap regions in the acr and acg promoters that were previously shown to be required for their expression. In addition, we found that 5% carbon dioxide was required for growth of Mycobacterium bovis BCG under microaerophilic (1.3% O(2)) culture conditions and fully prevented the growth cessation typically associated with rapid removal of oxygen. These findings are likely to be relevant to the in vivo environment and will contribute to our understanding of the pathogenesis of tuberculosis infection.

Bacteriological Techniques↗
PubMed2002

Identification of a novel class in the alpha/beta hydrolase fold superfamily: the N-myc differentiation-related proteins.

The alpha/beta hydrolases constitute a large protein superfamily that mainly consists of enzymes that catalyze a diverse range of reactions. These proteins exhibit the alpha/beta hydrolase fold, the essential features of which have recently been delineated: the presence of at least five parallel beta-strands, a catalytic triad in a specific order (nucleophile-acid-histidine), and a nucleophilic elbow. Because of the difficulties experimentally in identifying protein structures, we have used a Bayesian computational algorithm (PROBE) to identify the members of this superfamily based on distant sequence relationships. We found that the presence of five sequence motifs, which contain residues important for substrate binding and stabilization of the fold, are required for membership in this superfamily. The superfamily consists of at least 909 members, including the N-myc downstream regulated proteins, which are believed to be involved in cell differentiation. Unlike most of the other superfamily members, the N-myc downstream regulated proteins have never been proposed to possess the alpha/beta hydrolase fold and do not appear to be hydrolases.

Amino Acid Motifs↗
PubMed2002

Factors influencing the identification of transcription factor binding sites by cross-species comparison.

As the number of sequenced genomes has grown, the questions of which species are most useful and how many genomes are sufficient for comparison have become increasingly important for comparative genomics studies. We have systematically addressed these questions with respect to phylogenetic footprinting of transcription factor (TF) binding sites in the gamma-proteobacteria, and have evaluated the statistical significance of our motif predictions. We used a study set of 166 Escherichia coli genes that have experimentally identified TF binding sites upstream of the gene, with orthologous data from nine additional gamma-proteobacteria for phylogenetic footprinting. Just three species were sufficient for approximately 74.0% of the motif predictions to correspond to the experimentally reported E. coli sites, and important characteristics to consider when choosing species were phylogenetic distance, genome size, and natural habitat. We also performed simulations using randomized data to determine the critical maximum a posteriori probability (MAP) values for statistical significance of our motif predictions (P = 0.05). Approximately 60% of motif predictions containing sites from just three species had average MAP values above these critical MAP values. The inclusion of a species very closely related to E. coli increased the number of statistically significant motif predictions, despite substantially increasing the critical MAP value.

Binding Sites↗
PubMed2002

Identification of a Mycobacterium tuberculosis putative classical nitroreductase gene whose expression is coregulated with that of the acr aene within macrophages, in standing versus shaking cultures, and under low oxygen conditions.

Tuberculosis remains a leading killer worldwide, and new approaches for its treatment and prevention are urgently needed. This effort will benefit greatly from a better understanding of gene regulation in Mycobacterium tuberculosis, particularly with respect to this pathogen's response to its host environment. We examined the behavior of two promoters from the divergently transcribed M. tuberculosis genes acr/hspX/Rv2031c (alpha-crystallin homolog) and Rv2032/acg (acr-coregulated gene) by using a promoter-GFP fusion assay in Mycobacterium bovis BCG. We found that Rv2032 is a novel macrophage-induced gene whose expression is coregulated with that of acr. Relative levels of intracellular induction for both promoters were significantly affected by shallow standing versus shaking bacterial culture conditions prior to macrophage infection, and both promoters were strongly induced under low oxygen conditions. Deletion analyses showed that DNA sequences within a 43-bp region were required for expression of these promoters under all conditions. Multiple sequence alignment and database searches performed with PROBE indicated that Rv2032 is one of eight M. tuberculosis genes of previously unknown function that belong to an unusual superfamily of classical nitroreductases, which may have a role for bacteria within the host environment. These findings show that mycobacterial culture conditions can greatly influence the results and interpretation of subsequent gene regulation experiments. We propose that these differences might be exploited for dissection of the regulatory factors that affect mycobacterial gene expression within the host.

Amino Acid Motifs↗