Showing papers by "Institute for Systems Biology published in 2011"

Caspase-1-induced pyroptosis is an innate immune effector mechanism against intracellular bacteria (111.33)

Abstract: Macrophages mediate crucial innate immune responses via caspase-1-dependent processing and secretion of IL-1β and IL-18. While wild type Salmonella typhimurium infection is lethal to mice, a strain that persistently expresses flagellin was cleared by the cytosolic flagellin detection pathway via NLRC4 activation of caspase-1; however, this clearance was independent of IL-1β and IL-18. Instead, caspase-1 induced pyroptotic cell death released bacteria from macrophages, exposing them to uptake and killing by reactive oxygen species in neutrophils. Similarly, caspase-1 cleared Legionella and Burkholderia by cytokine independent mechanisms. Our results show, for the first time, that caspase-1 can clear intracellular bacteria in vivo independent of IL-1β and IL-18, and establish pyroptosis as an efficient mechanism of bacterial clearance by the innate immune system.

Systems biology of vaccination for seasonal influenza in humans

Abstract: Here we have used a systems biology approach to study innate and adaptive responses to vaccination against influenza in humans during three consecutive influenza seasons. We studied healthy adults vaccinated with trivalent inactivated influenza vaccine (TIV) or live attenuated influenza vaccine (LAIV). TIV induced higher antibody titers and more plasmablasts than LAIV did. In subjects vaccinated with TIV, early molecular signatures correlated with and could be used to accurately predict later antibody titers in two independent trials. Notably, expression of the kinase CaMKIV at day 3 was inversely correlated with later antibody titers. Vaccination of CaMKIV-deficient mice with TIV induced enhanced antigen-specific antibody titers, which demonstrated an unappreciated role for CaMKIV in the regulation of antibody responses. Thus, systems approaches can be used to predict immunogenicity and provide new mechanistic insights about vaccines.

Predictive, personalized, preventive, participatory (P4) cancer medicine

Abstract: Medicine will move from a reactive to a proactive discipline over the next decade--a discipline that is predictive, personalized, preventive and participatory (P4) P4 medicine will be fueled by systems approaches to disease, emerging technologies and analytical tools There will be two major challenges to achieving P4 medicine--technical and societal barriers--and the societal barriers will prove the most challenging How do we bring patients, physicians and members of the health-care community into alignment with the enormous opportunities of P4 medicine? In part, this will be done by the creation of new types of strategic partnerships--between patients, large clinical centers, consortia of clinical centers and patient-advocate groups For some clinical trials it will necessary to recruit very large numbers of patients--and one powerful approach to this challenge is the crowd-sourced recruitment of patients by bringing large clinical centers together with patient-advocate groups

Extracellular microRNA: A new source of biomarkers

Abstract: MicroRNAs (miRNAs) are a recently discovered class of small, non-coding RNAs that regulate protein levels post-transcriptionally. miRNAs play important regulatory roles in many cellular processes, including differentiation, neoplastic transformation, and cell replication and regeneration. Because of these regulatory roles, it is not surprising that aberrant miRNA expression has been implicated in several diseases. Recent studies have reported significant levels of miRNAs in serum and other body fluids, raising the possibility that circulating miRNAs could serve as useful clinical biomarkers. Here, we provide a brief overview of miRNA biogenesis and function, the identification and potential roles of circulating extracellular miRNAs, and the prospective uses of miRNAs as clinical biomarkers. Finally, we address several issues associated with the accurate measurement of miRNAs from biological samples.

Comparative and demographic analysis of orang-utan genomes.

Abstract: 'Orang-utan' is derived from a Malay term meaning 'man of the forest' and aptly describes the southeast Asian great apes native to Sumatra and Borneo. The orang-utan species, Pongo abelii (Sumatran) and Pongo pygmaeus (Bornean), are the most phylogenetically distant great apes from humans, thereby providing an informative perspective on hominid evolution. Here we present a Sumatran orang-utan draft genome assembly and short read sequence data from five Sumatran and five Bornean orang-utan genomes. Our analyses reveal that, compared to other primates, the orang-utan genome has many unique features. Structural evolution of the orang-utan genome has proceeded much more slowly than other great apes, evidenced by fewer rearrangements, less segmental duplication, a lower rate of gene family turnover and surprisingly quiescent Alu repeats, which have played a major role in restructuring other primate genomes. We also describe a primate polymorphic neocentromere, found in both Pongo species, emphasizing the gradual evolution of orang-utan genome structure. Orang-utans have extremely low energy usage for a eutherian mammal, far lower than their hominid relatives. Adding their genome to the repertoire of sequenced primates illuminates new signals of positive selection in several pathways including glycolipid metabolism. From the population perspective, both Pongo species are deeply diverse; however, Sumatran individuals possess greater diversity than their Bornean counterparts, and more species-specific variation. Our estimate of Bornean/Sumatran speciation time, 400,000 years ago, is more recent than most previous studies and underscores the complexity of the orang-utan speciation process. Despite a smaller modern census population size, the Sumatran effective population size (N(e)) expanded exponentially relative to the ancestral N(e) after the split, while Bornean N(e) declined over the same period. Overall, the resources and analyses presented here offer new opportunities in evolutionary genomics, insights into hominid biology, and an extensive database of variation for conservation efforts.

Association of BRCA1 and BRCA2 mutations with survival, chemotherapy sensitivity, and gene mutator phenotype in patients with ovarian cancer

Abstract: Context Attempts to determine the clinical significance of BRCA1/2 mutations in ovarian cancer have produced conflicting results. Objective To determine the relationships between BRCA1/2 deficiency (ie, mutation and promoter hypermethylation) and overall survival (OS), progression-free survival (PFS), chemotherapy response, and whole-exome mutation rate in ovarian cancer. Design, Setting, and Patients Observational study of multidimensional genomics and clinical data on 316 high-grade serous ovarian cancer cases that were made public between 2009 and 2010 via The Cancer Genome Atlas project. Main Outcome Measures OS and PFS rates (primary outcomes) and chemotherapy response (secondary outcome). Results BRCA2 mutations (29 cases) were associated with significantly better OS (adjusted hazard ratio [HR], 0.33; 95% CI, 0.16-0.69; P = .003 and 5-year OS, 61% for BRCA2-mutated vs 25% for BRCA wild-type cases) and PFS (adjusted HR, 0.40; 95% CI, 0.22-0.74; P = .004 and 3-year PFS, 44% for BRCA2-mutated vs 16% for BRCA wild-type cases), whereas neither BRCA1 mutations (37 cases) nor BRCA1 methylation (33 cases) was associated with prognosis. Moreover, BRCA2 mutations were associated with a significantly higher primary chemotherapy sensitivity rate (100% for BRCA2-mutated vs 82% [P = .02] and 80% [P = .05] for BRCA wild-type and BRCA1-mutated cases, respectively) and longer platinum-free duration (median platinum-free duration, 18.0 months for BRCA2-mutated vs 11.7 [P = .02] and 12.5 [P = .04] months for BRCA wild-type and BRCA1-mutated cases, respectively). BRCA2-mutated, but not BRCA1-mutated cases, exhibited a “mutator phenotype” by containing significantly more mutations than BRCA wild-type cases across the whole exome (median mutation number per sample, 84 for BRCA2-mutated vs 52 for BRCA wild-type cases, false discovery rate Conclusion Among women with high-grade serous ovarian cancer, BRCA2 mutation, but not BRCA1 deficiency, was associated with improved survival, improved chemotherapy response, and genome instability compared with BRCA wild-type.

mProphet: automated data processing and statistical validation for large-scale SRM experiments

Abstract: Selected reaction monitoring (SRM) is a targeted mass spectrometric method that is increasingly used in proteomics for the detection and quantification of sets of preselected proteins at high sensitivity, reproducibility and accuracy. Currently, data from SRM measurements are mostly evaluated subjectively by manual inspection on the basis of ad hoc criteria, precluding the consistent analysis of different data sets and an objective assessment of their error rates. Here we present mProphet, a fully automated system that computes accurate error rates for the identification of targeted peptides in SRM data sets and maximizes specificity and sensitivity by combining relevant features in the data into a statistical model.

Transport in two-dimensional paper networks

Abstract: Two-dimensional paper networks (2DPNs) hold great potential for transcending the capabilities and performance of today’s paper-based analytical devices. Specifically, 2DPNs enable sophisticated multi-step chemical processing sequences for sample pretreatment and analysis at a cost and ease-of-use that make them appropriate for use in settings with low resources. A quantitative understanding of flow in paper networks is essential to realize the potential of these networks. In this report, we provide a framework for understanding flow in simple 2DPNs using experiments, analytical expressions, and computational simulations.

Marine microgels as a source of cloud condensation nuclei in the high Arctic

Abstract: Marine microgels play an important role in regulating ocean basin-scale biogeochemical dynamics. In this paper, we demonstrate that, in the high Arctic, marine gels with unique physicochemical characteristics originate in the organic material produced by ice algae and/or phytoplankton in the surface water. The polymers in this dissolved organic pool assembled faster and with higher microgel yields than at other latitudes. The reversible phase transitions shown by these Arctic marine gels, as a function of pH, dimethylsulfide, and dimethylsulfoniopropionate concentrations, stimulate the gels to attain sizes below 1 μm in diameter. These marine gels were identified with an antibody probe specific toward material from the surface waters, sized, and quantified in airborne aerosol, fog, and cloud water, strongly suggesting that they dominate the available cloud condensation nuclei number population in the high Arctic (north of 80°N) during the summer season. Knowledge about emergent properties of marine gels provides important new insights into the processes controlling cloud formation and radiative forcing, and links the biology at the ocean surface with cloud properties and climate over the central Arctic Ocean and, probably, all oceans.

Systems medicine and integrated care to combat chronic noncommunicable diseases

Abstract: We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

KAVIAR: an accessible system for testing SNV novelty

Abstract: Summary: With the rapidly expanding availability of data from personal genomes, exomes and transcriptomes, medical researchers will frequently need to test whether observed genomic variants are novel or known. This task requires downloading and handling large and diverse datasets from a variety of sources, and processing them with bioinformatics tools and pipelines. Alternatively, researchers can upload data to online tools, which may conflict with privacy requirements. We present here Kaviar, a tool that greatly simplifies the assessment of novel variants. Kaviar includes: (i) an integrated and growing database of genomic variation from diverse sources, including over 55 million variants from personal genomes, family genomes, transcriptomes, SNV databases and population surveys; and (ii) software for querying the database efficiently. Availability: Kaviar is programmed in Perl and offered free of charge as Open Source Software. Kaviar may be used online as a programmatic web service or downloaded for local use from http://db.systemsbiology.net/kaviar. The database is also provided.

Adaptation of cells to new environments

Abstract: The evolutionary success of an organism is a testament to its inherent capacity to keep pace with environmental conditions that change over short and long periods. Mechanisms underlying adaptive processes are being investigated with renewed interest and excitement. This revival is partly fueled by powerful technologies that can probe molecular phenomena at a systems scale. Such studies provide spectacular insight into the mechanisms of adaptation, including rewiring of regulatory networks via natural selection of horizontal gene transfers, gene duplication, deletion, readjustment of kinetic parameters, and myriad other genetic reorganizational events. Here, we will discuss advances in prokaryotic systems biology from the perspective of evolutionary principles that have shaped regulatory networks for dynamic adaptation to environmental change.

The SOX2 response program in glioblastoma multiforme: an integrated ChIP-seq, expression microarray, and microRNA analysis

Abstract: Background SOX2 is a key gene implicated in maintaining the stemness of embryonic and adult stem cells. SOX2 appears to re-activate in several human cancers including glioblastoma multiforme (GBM), however, the detailed response program of SOX2 in GBM has not yet been defined.

Genome-wide analysis of yeast stress survival and tolerance acquisition to analyze the central trade-off between growth rate and cellular robustness.

Abstract: All organisms have evolved to cope with changes in environmental conditions, ensuring the optimal combination of proliferation and survival. In yeast, exposure to a mild stress leads to an increased tolerance for other stresses. This suggests that yeast uses information from the environment to prepare for future threats. We used the yeast knockout collection to systematically investigate the genes and functions involved in severe stress survival and in the acquisition of stress (cross-) tolerance. Besides genes and functions relevant for survival of heat, acid, and oxidative stress, we found an inverse correlation between mutant growth rate and stress survival. Using chemostat cultures, we confirmed that growth rate governs stress tolerance, with higher growth efficiency at low growth rates liberating the energy for these investments. Cellular functions required for stress tolerance acquisition, independent of the reduction in growth rate, were involved in vesicular transport, the Rpd3 histone deacetylase complex, and the mitotic cell cycle. Stress resistance and acquired stress tolerance in Saccharomyces cerevisiae are governed by a combination of stress-specific and general processes. The reduction of growth rate, irrespective of the cause of this reduction, leads to redistribution of resources toward stress tolerance functions, thus preparing the cells for impending change.

The NLRP3 Inflammasome Detects Encephalomyocarditis Virus and Vesicular Stomatitis Virus Infection

Abstract: Inflammasomes are cytosolic protein complexes that regulate caspase-1 activation and the secretion of interleukin-1β (IL-1β) and IL-18. Several different inflammasome complexes have been identified, but the NLRP3 inflammasome is particularly notable because of its central role in diseases of inflammation. Recent work has demonstrated an essential role for the NLRP3 inflammasome in host defense against influenza virus. We show here that two other RNA viruses, encephalomyocarditis virus (EMCV) and vesicular stomatitis virus (VSV), activate the NLRP3 inflammasome in dendritic cells and macrophages through a mechanism requiring viral replication. Inflammasome activation in response to both viruses does not require MDA5 or RIG-I signaling. Despite the ability of the NLRP3 inflammasome to detect EMCV and VSV, wild-type and caspase-1-deficient mice were equally susceptible to infection with both viruses. These findings indicate that the NLRP3 inflammasome may be a common pathway for RNA virus detection, but its precise role in the host response may be variable.

Differential Requirements for NAIP5 in Activation of the NLRC4 Inflammasome

Abstract: Inflammasomes are cytosolic multiprotein complexes that assemble in response to infectious or noxious stimuli and activate the CASPASE-1 protease. The inflammasome containing the nucleotide binding domain-leucine-rich repeat (NBD-LRR) protein NLRC4 (interleukin-converting enzyme protease-activating factor [IPAF]) responds to the cytosolic presence of bacterial proteins such as flagellin or the inner rod component of bacterial type III secretion systems (e.g., Salmonella PrgJ). In some instances, such as infection with Legionella pneumophila, the activation of the NLRC4 inflammasome requires the presence of a second NBD-LRR protein, NAIP5. NAIP5 also is required for NLRC4 activation by the minimal C-terminal flagellin peptide, which is sufficient to activate NLRC4. However, NLRC4 activation is not always dependent upon NAIP5. In this report, we define the molecular requirements for NAIP5 in the activation of the NLRC4 inflammasome. We demonstrate that the N terminus of flagellin can relieve the requirement for NAIP5 during the activation of the NLRC4 inflammasome. We also demonstrate that NLRC4 responds to the Salmonella protein PrgJ independently of NAIP5. Our results indicate that NAIP5 regulates the apparent specificity of the NLRC4 inflammasome for distinct bacterial ligands.

Lethal Synergism of 2009 Pandemic H1N1 Influenza Virus and Streptococcus pneumoniae Coinfection Is Associated with Loss of Murine Lung Repair Responses

Abstract: Secondary bacterial infections increase disease severity of influenza virus infections and contribute greatly to increased morbidity and mortality during pandemics. To study secondary bacterial infection following influenza virus infection, mice were inoculated with sublethal doses of 2009 seasonal H1N1 virus (NIH50) or pandemic H1N1 virus (Mex09) followed by inoculation with Streptococcus pneumoniae 48 h later. Disease was characterized by assessment of weight loss and survival, titration of virus and bacteria by quantitative reverse transcription-PCR (qRT-PCR), histopathology, expression microarray, and immunohistochemistry. Mice inoculated with virus alone showed 100% survival for all groups. Mice inoculated with Mex09 plus S. pneumoniae showed severe weight loss and 100% mortality with severe alveolitis, denuded bronchiolar epithelium, and widespread expression of apoptosis marker cleaved caspase 3. In contrast, mice inoculated with NIH50 plus S. pneumoniae showed increased weight loss, 100% survival, and slightly enhanced lung pathology. Mex09-S. pneumoniae coinfection also resulted in increased S. pneumoniae replication in lung and bacteremia late in infection. Global gene expression profiling revealed that Mex09-S. pneumoniae coinfection did not induce significantly more severe inflammatory responses but featured significant loss of epithelial cell reproliferation and repair responses. Histopathological examination for cell proliferation marker MCM7 showed significant staining of airway epithelial cells in all groups except Mex09-S. pneumoniae-infected mice. This study demonstrates that secondary bacterial infection during 2009 H1N1 pandemic virus infection resulted in more severe disease and loss of lung repair responses than did seasonal influenza viral and bacterial coinfection. Moreover, this study provides novel insights into influenza virus and bacterial coinfection by showing correlation of lethal outcome with loss of airway basal epithelial cells and associated lung repair responses. IMPORTANCE Secondary bacterial pneumonias lead to increased disease severity and have resulted in a significant percentage of deaths during influenza pandemics. To understand the biological basis for the interaction of bacterial and viral infections, mice were infected with sublethal doses of 2009 seasonal H1N1 and pandemic H1N1 viruses followed by infection with Streptococcus pneumoniae 48 h later. Only infection with 2009 pandemic H1N1 virus and S. pneumoniae resulted in severe disease with a 100% fatality rate. Analysis of the host response to infection during lethal coinfection showed a significant loss of responses associated with lung repair that was not observed in any of the other experimental groups. This group of mice also showed enhanced bacterial replication in the lung. This study reveals that the extent of lung damage during viral infection influences the severity of secondary bacterial infections and may help explain some differences in mortality during influenza pandemics.

COL4A1 mutations cause ocular dysgenesis, neuronal localization defects, and myopathy in mice and Walker-Warburg syndrome in humans.

Abstract: Muscle-eye-brain disease (MEB) and Walker Warburg Syndrome (WWS) belong to a spectrum of autosomal recessive diseases characterized by ocular dysgenesis, neuronal migration defects, and congenital muscular dystrophy. Until now, the pathophysiology of MEB/WWS has been attributed to alteration in dystroglycan post-translational modification. Here, we provide evidence that mutations in a gene coding for a major basement membrane protein, collagen IV alpha 1 (COL4A1), are a novel cause of MEB/WWS. Using a combination of histological, molecular, and biochemical approaches, we show that heterozygous Col4a1 mutant mice have ocular dysgenesis, neuronal localization defects, and myopathy characteristic of MEB/WWS. Importantly, we identified putative heterozygous mutations in COL4A1 in two MEB/WWS patients. Both mutations occur within conserved amino acids of the triple-helix-forming domain of the protein, and at least one mutation interferes with secretion of the mutant proteins, resulting instead in intracellular accumulation. Expression and posttranslational modification of dystroglycan is unaltered in Col4a1 mutant mice indicating that COL4A1 mutations represent a distinct pathogenic mechanism underlying MEB/WWS. These findings implicate a novel gene and a novel mechanism in the etiology of MEB/WWS and expand the clinical spectrum of COL4A1-associated disorders.

A CD133-related gene expression signature identifies an aggressive glioblastoma subtype with excessive mutations

Abstract: Cancer cells are heterogeneous and, it has been proposed, fall into at least two classes: the tumor-initiating cancer stem cells (CSC) and the more differentiated tumor cells. The transmembrane protein CD133 has been widely used to isolate putative CSC populations in several cancer types, but its validity as a CSC marker and hence its clinical ramifications remain controversial. Here, we conducted transcriptomic profiling of sorted CD133+ and CD133− cells from human glioblastoma multiforme (GBM) and, by subtractive analysis, established a CD133 gene expression signature composed of 214 differentially expressed genes. Extensive computational comparisons with a compendium of published gene expression profiles reveal that the CD133 gene signature transcriptionally resembles human ES cells and in vitro cultured GBM stem cells, and this signature successfully distinguishes GBM from lower-grade gliomas. More importantly, the CD133 gene signature identifies an aggressive subtype of GBM seen in younger patients with shorter survival who bear excessive genomic mutations as surveyed through the Cancer Genome Atlas Network GBM mutation spectrum. Furthermore, the CD133 gene signature distinguishes higher-grade breast and bladder cancers from their lower-grade counterparts. Our systematic analysis provides molecular and genetic support for the stem cell-like nature of CD133+ cells and an objective means for evaluating cancer aggressiveness.

Genetics. Systems genetics.

Abstract: From studies with peas over 150 years ago, Gregor Mendel deduced the laws that govern the inheritance of traits in most organisms. The brilliance, but also the limitation, of Mendel’s work was its focus on single-gene traits, such as flower color and plant height. However, phenotypic variation, including that which underlies health and disease in humans, often results from multiple interactions among numerous genetic and environmental factors. Systems genetics seeks to understand this complexity by integrating the questions and methods of systems biology with those of genetics to solve the fundamental problem of interrelating genotype and phenotype in complex traits and disease. This global perspective is possible because of the technologies, information, and infrastructure that derive from the Human Genome Project, which sequenced the genome as a way to locate genes and other functional DNA sequence elements. These advances now allow comprehensive “-omic” measurements of RNAs, proteins, small molecules, and chemical modifications of DNA. The application of these technologies has enabled an unprecedented scale and scope of genetic and phenotypic surveys. But this does not in itself constitute a new field of study. Instead, the defining principle of systems genetics is understanding how genetic information is integrated, coordinated, and ultimately transmitted through molecular, cellular, and physiological networks to enable the higher-order functions and emergent properties of biological systems. In contrast to the networks of molecular and physical interactions that dominate the field of systems biology, systems genetics focuses on networks of interactions between genes and traits, as well as between traits themselves. The analytical foundations for characterizing these relationships are based on graph theory and the statistics of correlation and causality (1, 2). Predictions that result from these network models can be tested with genetic mutations, chemical agents, or environmental exposures as single-factor perturbations. Machine learning methods (3) can prioritize candidate genes and network functions for further study. Typically, gene expression levels based on global profiles have been analyzed as quantitative phenotypes, so-called eQTLs (expression quantitative trait loci) (4) to study diverse biological phenomena in yeasts, plants, flies, worms, mice, and humans. Examples range from sleep patterns in flies (5) to metabolite concentrations in plants (6). To date, however, most of the pioneering studies in this field have focused on classically reductionist questions, such as gene discovery, rather than systems problems, such as homeostasis. An essential but not yet fully exploited application of systems genetics is the inference of higher-order functionality in complex systems from patterns of covariation among underlying molecular and physiological phenotypes. A proof-of-concept study showed, for example, that an established inverse relationship between distinct systems, namely muscle mass and heart rate, emerged from echocardiographic measures of heart structure and function in a genetically heterogeneous population (7). Then, with single-gene mutations as perturbations, conserved and compromised network features were identified as clues to the mechanistic and systems basis for cardiac homeostasis and dysfunction. This paradigm represents a powerful strategy to solve systems problems such as the coordination of physiological functions within and among organs that are difficult to address with conventional reductionist approaches. An important goal of systems genetics is identifying targets for modulating phenotypic outcomes to treat and prevent disease. This is difficult to achieve, however, because the sensitivity of particular trait relationships to perturbation is usually not evident. Modifier genes—variants in one gene that modulate the phenotypic manifestations of another gene—could be an efficient means of identifying such network targets. These variant genes often restore normal biological functionality despite the presence of the original disease-causing gene. Modifier effects are ubiquitous in both simple and complex traits in many organisms (8, 9). Examples in the mouse include modifiers that modulate the extent of Purkinje cell loss and dysfunction in models of neurodegenerative diseases (10), and others that control the severity of type 2 diabetes in obese mice (11). An especially exciting application of modifier genetics is the use of complete genome sequencing of families (12) that show variation in the clinical presentation of disease. With the increasing power of new technologies to provide complete genome sequences at dramatically reduced costs, systematic surveys to identify modifier genes should now be possible in humans and model organisms. Although the goal of understanding how genetic and phenotypic variants interact to create the functional diversity of organismal biology has not changed since Mendel, the experimental and computational methods of systems genetics will finally enable studies of previously intractable problems. For example, it may be possible to determine whether genetic networks governing different biological processes (development versus physiology, for example) have distinct network features, structures, and parameters. In addition, variation in robustness, criticality, and other systems properties can be studied among individuals or populations, or in healthy versus disease states. Finally, computational models of underlying network architectures and properties can be developed to predict phenotypic outcome in response to different genetic backgrounds, environmental factors, or targeted perturbations aimed at reversing disease outcome. Systems genetics is now poised to address these and other fundamental questions in biology and medicine.

Systems biology of interstitial lung diseases: integration of mRNA and microRNA expression changes.

Abstract: The molecular pathways involved in the interstitial lung diseases (ILDs) are poorly understood. Systems biology approaches, with global expression data sets, were used to identify perturbed gene networks, to gain some understanding of the underlying mechanisms, and to develop specific hypotheses relevant to these chronic lung diseases. Lung tissue samples from patients with different types of ILD were obtained from the Lung Tissue Research Consortium and total cell RNA was isolated. Global mRNA and microRNA were profiled by hybridization and amplification-based methods. Differentially expressed genes were compiled and used to identify critical signaling pathways and potential biomarkers. Modules of genes were identified that formed a regulatory network, and studies were performed on cultured cells in vitro for comparison with the in vivo results. By profiling mRNA and microRNA (miRNA) expression levels, we found subsets of differentially expressed genes that distinguished patients with ILDs from controls and that correlated with different disease stages and subtypes of ILDs. Network analysis, based on pathway databases, revealed several disease-associated gene modules, involving genes from the TGF-β, Wnt, focal adhesion, and smooth muscle actin pathways that are implicated in advancing fibrosis, a critical pathological process in ILDs. A more comprehensive approach was also adapted to construct a putative global gene regulatory network based on the perturbation of key regulatory elements, transcription factors and microRNAs. Our data underscores the importance of TGF-β signaling and the persistence of smooth muscle actin-containing fibroblasts in these diseases. We present evidence that, downstream of TGF-β signaling, microRNAs of the miR-23a cluster and the transcription factor Zeb1 could have roles in mediating an epithelial to mesenchymal transition (EMT) and the resultant persistence of mesenchymal cells in these diseases. We present a comprehensive overview of the molecular networks perturbed in ILDs, discuss several potential key molecular regulatory circuits, and identify microRNA species that may play central roles in facilitating the progression of ILDs. These findings advance our understanding of these diseases at the molecular level, provide new molecular signatures in defining the specific characteristics of the diseases, suggest new hypotheses, and reveal new potential targets for therapeutic intervention.

Metabolite profiling of recombinant CHO cells: Designing tailored feeding regimes that enhance recombinant antibody production

Abstract: Chinese hamster ovary (CHO) cells are the primary platform for commercial expression of recombinant therapeutic proteins. Obtaining maximum production from the expression platform requires optimal cell culture medium (and associated nutrient feeds). We have used metabolite profiling to define the balance of intracellular and extracellular metabolites during the production process of a CHO cell line expressing a recombinant IgG4 antibody. Using this metabolite profiling approach, it was possible to identify nutrient limitations, which acted as bottlenecks for antibody production, and subsequently develop a simple feeding regime to relieve these metabolic bottlenecks. This metabolite profiling-based strategy was used to design a targeted, low cost nutrient feed that increased cell biomass by 35% and doubled the antibody titer. This approach, with the potential for utilization in non-specialized laboratories, can be applied universally to the optimization of production of commercially important biopharmaceuticals.

A Systems Biology Approach to Infectious Disease Research: Innovating the Pathogen-Host Research Paradigm

Abstract: The twentieth century was marked by extraordinary advances in our understanding of microbes and infectious disease, but pandemics remain, food and waterborne illnesses are frequent, multidrug-resistant microbes are on the rise, and the needed drugs and vaccines have not been developed. The scientific approaches of the past-including the intense focus on individual genes and proteins typical of molecular biology-have not been sufficient to address these challenges. The first decade of the twenty-first century has seen remarkable innovations in technology and computational methods. These new tools provide nearly comprehensive views of complex biological systems and can provide a correspondingly deeper understanding of pathogen-host interactions. To take full advantage of these innovations, the National Institute of Allergy and Infectious Diseases recently initiated the Systems Biology Program for Infectious Disease Research. As participants of the Systems Biology Program, we think that the time is at hand to redefine the pathogen-host research paradigm.

Absolute quantification of microbial proteomes at different states by directed mass spectrometry.

Abstract: Over the past decade, liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has evolved into the main proteome discovery technology. Up to several thousand proteins can now be reliably identified from a sample and the relative abundance of the identified proteins can be determined across samples. However, the remeasurement of substantially similar proteomes, for example those generated by perturbation experiments in systems biology, at high reproducibility and throughput remains challenging. Here, we apply a directed MS strategy to detect and quantify sets of pre-determined peptides in tryptic digests of cells of the human pathogen Leptospira interrogans at 25 different states. We show that in a single LC-MS/MS experiment around 5000 peptides, covering 1680 L. interrogans proteins, can be consistently detected and their absolute expression levels estimated, revealing new insights about the proteome changes involved in pathogenic progression and antibiotic defense of L. interrogans. This is the first study that describes the absolute quantitative behavior of any proteome over multiple states, and represents the most comprehensive proteome abundance pattern comparison for any organism to date.