Nicole Baldwin

Complex trait analysis of gene expression uncovers polygenic and pleiotropic networks that modulate nervous system function.

Patterns of gene expression in the central nervous system are highly variable and heritable. This genetic variation among normal individuals leads to considerable structural, functional and behavioral differences. We devised a general approach to dissect genetic networks systematically across biological scale, from base pairs to behavior, using a reference population of recombinant inbred strains. We profiled gene expression using Affymetrix oligonucleotide arrays in the BXD recombinant inbred strains, for which we have extensive SNP and haplotype data. We integrated a complementary database comprising 25 years of legacy phenotypic data on these strains. Covariance among gene expression and pharmacological and behavioral traits is often highly significant, corroborates known functional relations and is often generated by common quantitative trait loci. We found that a small number of major-effect quantitative trait loci jointly modulated large sets of transcripts and classical neural phenotypes in patterns specific to each tissue. We developed new analytic and graph theoretical approaches to study shared genetic modulation of networks of traits using gene sets involved in neural synapse function as an example. We built these tools into an open web resource called WebQTL that can be used to test a broad array of hypotheses.

A Modular Analysis Framework for Blood Genomics Studies: Application to Systemic Lupus Erythematosus

The analysis of patient blood transcriptional profiles offers a means to investigate the immunological mechanisms relevant to human diseases on a genome-wide scale. In addition, such studies provide a basis for the discovery of clinically relevant biomarker signatures. We designed a strategy for microarray analysis that is based on the identification of transcriptional modules formed by genes coordinately expressed in multiple disease data sets. Mapping changes in gene expression at the module level generated disease-specific transcriptional fingerprints that provide a stable framework for the visualization and functional interpretation of microarray data. These transcriptional modules were used as a basis for the selection of biomarkers and the development of a multivariate transcriptional indicator of disease progression in patients with systemic lupus erythematosus. Thus, this work describes the implementation and application of a methodology designed to support systems-scale analysis of the human immune system in translational research settings.

Democratizing systems immunology with modular transcriptional repertoire analyses.

Individual elements that constitute the immune system have been characterized over the few past decades, mostly through reductionist approaches. The introduction of large-scale profiling platforms has more recently facilitated the assessment of these elements on a global scale. However, the analysis and the interpretation of such large-scale datasets remains a challenge and a barrier for the wider adoption of systems approaches in immunological and clinical studies. In this Innovation article, we describe an analytical strategy that relies on the a priori determination of co-dependent gene sets for a given biological system. Such modular transcriptional repertoires can in turn be used to simplify the analysis and the interpretation of large-scale datasets, and to design targeted immune fingerprinting assays and web applications that will further facilitate the dissemination of systems approaches in immunology.

Genome-Scale Computational Approaches to Memory-Intensive Applications in Systems Biology

Graph-theoretical approaches to biological network analysis have proven to be effective for small networks but are computationally infeasible for comprehensive genome-scale systems-level elucidation of these networks. The difficulty lies in the NP-hard nature of many global systems biology problems that, in practice, translates to exponential (or worse) run times for finding exact optimal solutions. Moreover, these problems, especially those of an enumerative flavor, are often memory-intensive and must share very large sets of data effectively across many processors. For example, the enumeration of maximal cliques - a core component in gene expression networks analysis, cis regulatory motif finding, and the study of quantitative trait loci for high-throughput molecular phenotypes can result in as many as 3^n/3 maximal cliques for a graph with n vertices. Memory requirements to store those cliques reach terabyte scales even on modest-sized genomes. Emerging hardware architectures with ultra-large globally addressable memory such as the SGI Altix and Cray X1 seem to be well suited for addressing these types of data-intensive problems in systems biology. This paper presents a novel framework that provides exact, parallel and scalable solutions to various graph-theoretical approaches to genome-scale elucidation of biological networks. This framework takes advantage of these large-memory architectures by creating globally addressable bitmap memory indices with potentially high compression rates, fast bitwise-logical operations, and reduced search space. Augmented with recent theoretical advancements based on fixed-parameter tractability, this framework produces computationally feasible performance for genome-scale combinatorial problems of systems biology.

Host immune transcriptional profiles reflect the variability in clinical disease manifestations in patients with Staphylococcus aureus infections.

Staphylococcus aureus infections are associated with diverse clinical manifestations leading to significant morbidity and mortality. To define the role of the host response in the clinical manifestations of the disease, we characterized whole blood transcriptional profiles of children hospitalized with community-acquired S. aureus infection and phenotyped the bacterial strains isolated. The overall transcriptional response to S. aureus infection was characterized by over-expression of innate immunity and hematopoiesis related genes and under-expression of genes related to adaptive immunity. We assessed individual profiles using modular fingerprints combined with the molecular distance to health (MDTH), a numerical score of transcriptional perturbation as compared to healthy controls. We observed significant heterogeneity in the host signatures and MDTH, as they were influenced by the type of clinical presentation, the extent of bacterial dissemination, and time of blood sampling in the course of the infection, but not by the bacterial isolate. System analysis approaches provide a new understanding of disease pathogenesis and the relation/interaction between host response and clinical disease manifestations.

Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively coregulated genes and their annotation using gene ontology analysis and cis-regulatory element discovery. The causal basis for coregulation is detected through the use of quantitative trait locus mapping.

Transcriptional specialization of human dendritic cell subsets in response to microbial vaccines

The mechanisms by which microbial vaccines interact with human APCs remain elusive. Herein, we describe the transcriptional programs induced in human DCs by pathogens, innate receptor ligands and vaccines. Exposure of DCs to influenza, Salmonella enterica and Staphylococcus aureus allows us to build a modular framework containing 204 transcript clusters. We use this framework to characterize the responses of human monocytes, monocyte-derived DCs and blood DC subsets to 13 vaccines. Different vaccines induce distinct transcriptional programs based on pathogen type, adjuvant formulation and APC targeted. Fluzone, Pneumovax and Gardasil, respectively, activate monocyte-derived DCs, monocytes and CD1c+ blood DCs, highlighting APC specialization in response to vaccines. Finally, the blood signatures from individuals vaccinated with Fluzone or infected with influenza reveal a signature of adaptive immunity activation following vaccination and symptomatic infections, but not asymptomatic infections. These data, offered with a web interface, may guide the development of improved vaccines.

Development of Smallpox Vaccine Candidates with Integrated Interleukin-15 That Demonstrate Superior Immunogenicity, Efficacy, and Safety in Mice

ABSTRACT The potential use of variola virus, the etiological agent of smallpox, as a bioterror agent has heightened the interest in the reinitiation of smallpox vaccination. However, the currently licensed Dryvax vaccine, despite its documented efficacy in eradicating smallpox, is not optimal for the vaccination of contemporary populations with large numbers of individuals with immunodeficiencies because of severe adverse effects that can occur in such individuals. Therefore, the development of safer smallpox vaccines that can match the immunogenicity and efficacy of Dryvax for the vaccination of contemporary populations remains a priority. Using the Wyeth strain of vaccinia virus derived from the Dryvax vaccine, we generated a recombinant Wyeth interleukin-15 (IL-15) with integrated IL-15, a cytokine with potent immunostimulatory functions. The integration of IL-15 into the Wyeth strain resulted in a >1,000-fold reduction in lethality of vaccinated athymic nude mice and induced severalfold-higher cellular and humoral immune responses in wild-type mice that persisted longer than those induced by the parental Wyeth strain. The superior efficacy of Wyeth IL-15 was further demonstrated by the ability of vaccinated mice to fully survive a lethal intranasal challenge of virulent vaccinia virus even 10 months after vaccination, whereas all mice vaccinated with parental Wyeth strain succumbed. By integrating IL-15 into modified vaccinia virus Ankara (MVA), a virus currently under consideration as a substitute for the Dryvax vaccine, we developed a second vaccine candidate (MVA IL-15) with greater immunogenicity and efficacy than Dryvax. Thus, Wyeth IL-15 and MVA IL-15 viruses hold promise as more-efficacious and safe alternatives to the Dryvax vaccine.

Erratum: Personalized immunomonitoring uncovers molecular networks that stratify lupus patients ((Cell (2016) 165 (551-565))

Romain Banchereau, Seunghee Hong, Brandi Cantarel, Nicole Baldwin, Jeanine Baisch, Michelle Edens, Alma-Martina Cepika, Peter Acs, Jacob Turner, Esperanza Anguiano, Parvathi Vinod, Shaheen Khan, Gerlinde Obermoser, Derek Blankenship, Edward Wakeland, Lorien Nassi, Alisa Gotte, Marilynn Punaro, Yong-Jun Liu, Jacques Banchereau, Jose Rossello-Urgell, Tracey Wright, and Virginia Pascual* *Correspondence: virginia.pascual@bswhealth.org http://dx.doi.org/10.1016/j.cell.2016.05.057

Novel Evidence for Curcumin and Boswellic Acid–Induced Chemoprevention through Regulation of miR-34a and miR-27a in Colorectal Cancer

Colorectal cancer is one of the most common causes of cancer-associated mortality worldwide, but it is truly a preventable disease. Both curcumin and boswellic acids are well-established dietary botanicals with potent antitumorigenic properties that have been shown to modulate multiple oncogenic pathways. Recent data suggest that the chemopreventive effects of these botanicals may, in part, be mediated through regulation of key cancer-related microRNAs (miRNA) and their downstream gene targets. Here, we investigated the antitumorigenic effects of curcumin and 3 acetyl-11-keto-β-boswellic acid (AKBA) on modulation of specific cancer-related miRNAs in colorectal cancer cells and validated their protective effects in vivo using a xenograft mouse model. Both curcumin and AKBA inhibited cellular proliferation, induced apoptosis and cell-cycle arrest in colorectal cancer cell lines, and these effects were significantly enhanced with combined treatment. Gene-expression arrays revealed that curcumin and AKBA regulated distinct cancer signaling pathways, including key cell-cycle regulatory genes. Combined bioinformatics and in silico analysis identified apoptosis, proliferation, and cell-cycle regulatory signaling pathways as key modulators of curcumin and AKBA-induced anticancer effects. We discovered that curcumin and AKBA induced upregulation of tumor-suppressive miR-34a and downregulation of miR-27a in colorectal cancer cells. Furthermore, we demonstrated in a mouse xenograft model that both curcumin and AKBA treatments suppressed tumor growth, which corresponded with alterations in the expression of miR-34a and miR-27a, consistent with our in vitro findings. Herein, we provide novel mechanistic evidence for the chemopreventive effects of curcumin and AKBA through regulation of specific miRNAs in colorectal cancer. Cancer Prev Res; 8(5); 431–43. ©2015 AACR.