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1.  Sequence of a Complete Chicken BG Haplotype Shows Dynamic Expansion and Contraction of Two Gene Lineages with Particular Expression Patterns 
PLoS Genetics  2014;10(6):e1004417.
Many genes important in immunity are found as multigene families. The butyrophilin genes are members of the B7 family, playing diverse roles in co-regulation and perhaps in antigen presentation. In humans, a fixed number of butyrophilin genes are found in and around the major histocompatibility complex (MHC), and show striking association with particular autoimmune diseases. In chickens, BG genes encode homologues with somewhat different domain organisation. Only a few BG genes have been characterised, one involved in actin-myosin interaction in the intestinal brush border, and another implicated in resistance to viral diseases. We characterise all BG genes in B12 chickens, finding a multigene family organised as tandem repeats in the BG region outside the MHC, a single gene in the MHC (the BF-BL region), and another single gene on a different chromosome. There is a precise cell and tissue expression for each gene, but overall there are two kinds, those expressed by haemopoietic cells and those expressed in tissues (presumably non-haemopoietic cells), correlating with two different kinds of promoters and 5′ untranslated regions (5′UTR). However, the multigene family in the BG region contains many hybrid genes, suggesting recombination and/or deletion as major evolutionary forces. We identify BG genes in the chicken whole genome shotgun sequence, as well as by comparison to other haplotypes by fibre fluorescence in situ hybridisation, confirming dynamic expansion and contraction within the BG region. Thus, the BG genes in chickens are undergoing much more rapid evolution compared to their homologues in mammals, for reasons yet to be understood.
Author Summary
Many immune genes are multigene families, presumably in response to pathogen variation. Some multigene families undergo expansion and contraction, leading to copy number variation (CNV), presumably due to more intense selection. Recently, the butyrophilin family in humans and other mammals has come under scrutiny, due to genetic associations with autoimmune diseases as well as roles in immune co-regulation and antigen presentation. Butyrophilin genes exhibit allelic polymorphism, but gene number appears stable within a species. We found that the BG homologues in chickens are very different, with great changes between haplotypes. We characterised one haplotype in detail, showing that there are two single BG genes, one on chromosome 2 and the other in the major histocompatibility complex (BF-BL region) on chromosome 16, and a family of BG genes in a tandem array in the BG region nearby. These genes have specific expression in cells and tissues, but overall are expressed in either haemopoietic cells or tissues. The two singletons have relatively stable evolutionary histories, but the BG region undergoes dynamic expansion and contraction, with the production of hybrid genes. Thus, chicken BG genes appear to evolve much more quickly than their closest homologs in mammals, presumably due to increased pressure from pathogens.
doi:10.1371/journal.pgen.1004417
PMCID: PMC4046983  PMID: 24901252
2.  Revolutionizing medicine in the 21st century through systems approaches 
Biotechnology journal  2012;7(8):992-1001.
Personalized medicine is a term for a revolution in medicine that envisions the individual patient as the central focus of healthcare in the future. The term “personalized medicine”, however, fails to reflect the enormous dimensionality of this new medicine that will be predictive, preventive, personalized, and participatory – a vision of medicine we have termed P4 medicine. This reflects a paradigm change in how medicine will be practiced that is revolutionary rather than evolutionary. P4 medicine arises from the confluence of a systems approach to medicine and from the digitalization of medicine that creates the large data sets necessary to deal with the complexities of disease. We predict that systems approaches will empower the transition from conventional reactive medical practice to a more proactive P4 medicine focused on wellness, and will reverse the escalating costs of drug development and will have enormous social and economic benefits. Our vision for P4 medicine in 10 years is that each patient will be associated with a virtual data cloud of billions of data points and that we will have the information technology for healthcare to reduce this enormous data dimensionality to simple hypotheses about health and/or disease for each individual. These data will be multi-scale across all levels of biological organization and extremely heterogeneous in type – this enormous amount of data represents a striking signal-to-noise (S/N) challenge. The key to dealing with this S/N challenge is to take a “holistic systems approach” to disease as we will discuss in this article.
doi:10.1002/biot.201100306
PMCID: PMC3962497  PMID: 22815171
Functional genomics; Network biology; Personalized medicine; Systems medicine
4.  Participatory medicine: a driving force for revolutionizing healthcare 
Genome Medicine  2013;5(12):110.
doi:10.1186/gm514
PMCID: PMC3978637  PMID: 24360023
5.  M19 Modulates Skeletal Muscle Differentiation and Insulin Secretion in Pancreatic β-Cells through Modulation of Respiratory Chain Activity 
PLoS ONE  2012;7(2):e31815.
Mitochondrial dysfunction due to nuclear or mitochondrial DNA alterations contributes to multiple diseases such as metabolic myopathies, neurodegenerative disorders, diabetes and cancer. Nevertheless, to date, only half of the estimated 1,500 mitochondrial proteins has been identified, and the function of most of these proteins remains to be determined. Here, we characterize the function of M19, a novel mitochondrial nucleoid protein, in muscle and pancreatic β-cells. We have identified a 13-long amino acid sequence located at the N-terminus of M19 that targets the protein to mitochondria. Furthermore, using RNA interference and over-expression strategies, we demonstrate that M19 modulates mitochondrial oxygen consumption and ATP production, and could therefore regulate the respiratory chain activity. In an effort to determine whether M19 could play a role in the regulation of various cell activities, we show that this nucleoid protein, probably through its modulation of mitochondrial ATP production, acts on late muscle differentiation in myogenic C2C12 cells, and plays a permissive role on insulin secretion under basal glucose conditions in INS-1 pancreatic β-cells. Our results are therefore establishing a functional link between a mitochondrial nucleoid protein and the modulation of respiratory chain activities leading to the regulation of major cellular processes such as myogenesis and insulin secretion.
doi:10.1371/journal.pone.0031815
PMCID: PMC3282743  PMID: 22363741
8.  Predictive, preventive, personalized and participatory medicine: back to the future 
Genome Medicine  2010;2(8):57.
The pioneering work of Jean Dausset on the HLA system established several principles that were later reflected in the Human Genome Project and contributed to the foundations of predictive, preventive, personalized and participatory (P4) medicine. To effectively develop systems medicine, we should take advantage of the lessons of the HLA saga, emphasizing the importance of exploring a fascinating but mysterious biology, now using systems principles, pioneering new technology developments and creating shared biological and information resources.
doi:10.1186/gm178
PMCID: PMC2945014  PMID: 20804580
9.  Report on EU–USA Workshop: How Systems Biology Can Advance Cancer Research (27 October 2008)☆ 
Molecular oncology  2008;3(1):9-17.
The main conclusion is that systems biology approaches can indeed advance cancer research, having already proved successful in a very wide variety of cancer-related areas, and are likely to prove superior to many current research strategies. Major points include: Systems biology and computational approaches can make important contributions to research and development in key clinical aspects of cancer and of cancer treatment, and should be developed for understanding and application to diagnosis, biomarkers, cancer progression, drug development and treatment strategies.Development of new measurement technologies is central to successful systems approaches, and should be strongly encouraged. The systems view of disease combined with these new technologies and novel computational tools will over the next 5–20 years lead to medicine that is predictive, personalized, preventive and participatory (P4 medicine).Major initiatives are in progress to gather extremely wide ranges of data for both somatic and germ-line genetic variations, as well as gene, transcript, protein and metabolite expression profiles that are cancer-relevant. Electronic databases and repositories play a central role to store and analyze these data. These resources need to be developed and sustained.Understanding cellular pathways is crucial in cancer research, and these pathways need to be considered in the context of the progression of cancer at various stages. At all stages of cancer progression, major areas require modelling via systems and developmental biology methods including immune system reactions, angiogenesis and tumour progression.A number of mathematical models of an analytical or computational nature have been developed that can give detailed insights into the dynamics of cancer-relevant systems. These models should be further integrated across multiple levels of biological organization in conjunction with analysis of laboratory and clinical data.Biomarkers represent major tools in determining the presence of cancer, its progression and the responses to treatments. There is a need for sets of high-quality annotated clinical samples, enabling comparisons across different diseases and the quantitative simulation of major pathways leading to biomarker development and analysis of drug effects.Education is recognized as a key component in the success of any systems biology programme, especially for applications to cancer research. It is recognized that a balance needs to be found between the need to be interdisciplinary and the necessity of having extensive specialist knowledge in particular areas.A proposal from this workshop is to explore one or more types of cancer over the full scale of their progression, for example glioblastoma or colon cancer. Such an exemplar project would require all the experimental and computational tools available for the generation and analysis of quantitative data over the entire hierarchy of biological information. These tools and approaches could be mobilized to understand, detect and treat cancerous processes and establish methods applicable across a wide range of cancers.
doi:10.1016/j.molonc.2008.11.003
PMCID: PMC2930781  PMID: 19383362
Systems biology; EU-USA workshop; Cancer
11.  Bridging the gap between systems biology and medicine 
Genome Medicine  2009;1(9):88.
Systems biology has matured considerably as a discipline over the last decade, yet some of the key challenges separating current research efforts in systems biology and clinically useful results are only now becoming apparent. As these gaps are better defined, the new discipline of systems medicine is emerging as a translational extension of systems biology. How is systems medicine defined? What are relevant ontologies for systems medicine? What are the key theoretic and methodologic challenges facing computational disease modeling? How are inaccurate and incomplete data, and uncertain biologic knowledge best synthesized in useful computational models? Does network analysis provide clinically useful insight? We discuss the outstanding difficulties in translating a rapidly growing body of data into knowledge usable at the bedside. Although core-specific challenges are best met by specialized groups, it appears fundamental that such efforts should be guided by a roadmap for systems medicine drafted by a coalition of scientists from the clinical, experimental, computational, and theoretic domains.
doi:10.1186/gm88
PMCID: PMC2768995  PMID: 19754960
12.  Computational disease modeling – fact or fiction? 
BMC Systems Biology  2009;3:56.
Background
Biomedical research is changing due to the rapid accumulation of experimental data at an unprecedented scale, revealing increasing degrees of complexity of biological processes. Life Sciences are facing a transition from a descriptive to a mechanistic approach that reveals principles of cells, cellular networks, organs, and their interactions across several spatial and temporal scales. There are two conceptual traditions in biological computational-modeling. The bottom-up approach emphasizes complex intracellular molecular models and is well represented within the systems biology community. On the other hand, the physics-inspired top-down modeling strategy identifies and selects features of (presumably) essential relevance to the phenomena of interest and combines available data in models of modest complexity.
Results
The workshop, "ESF Exploratory Workshop on Computational disease Modeling", examined the challenges that computational modeling faces in contributing to the understanding and treatment of complex multi-factorial diseases. Participants at the meeting agreed on two general conclusions. First, we identified the critical importance of developing analytical tools for dealing with model and parameter uncertainty. Second, the development of predictive hierarchical models spanning several scales beyond intracellular molecular networks was identified as a major objective. This contrasts with the current focus within the systems biology community on complex molecular modeling.
Conclusion
During the workshop it became obvious that diverse scientific modeling cultures (from computational neuroscience, theory, data-driven machine-learning approaches, agent-based modeling, network modeling and stochastic-molecular simulations) would benefit from intense cross-talk on shared theoretical issues in order to make progress on clinically relevant problems.
doi:10.1186/1752-0509-3-56
PMCID: PMC2697138  PMID: 19497118
13.  Origins of Systems Biology in William Harvey’s Masterpiece on the Movement of the Heart and the Blood in Animals 
In this article we continue our exploration of the historical roots of systems biology by considering the work of William Harvey. Central arguments in his work on the movement of the heart and the circulation of the blood can be shown to presage the concepts and methods of integrative systems biology. These include: (a) the analysis of the level of biological organization at which a function (e.g. cardiac rhythm) can be said to occur; (b) the use of quantitative mathematical modelling to generate testable hypotheses and deduce a fundamental physiological principle (the circulation of the blood) and (c) the iterative submission of his predictions to an experimental test. This article is the result of a tri-lingual study: as Harvey’s masterpiece was published in Latin in 1628, we have checked the original edition and compared it with and between the English and French translations, some of which are given as notes to inform the reader of differences in interpretation.
doi:10.3390/ijms10041658
PMCID: PMC2680639  PMID: 19468331
William Harvey; heart rhythm; circulation of the blood; mathematical deduction: experimental verification; systems biology
14.  A Functional and Regulatory Network Associated with PIP Expression in Human Breast Cancer 
PLoS ONE  2009;4(3):e4696.
Background
The PIP (prolactin-inducible protein) gene has been shown to be expressed in breast cancers, with contradictory results concerning its implication. As both the physiological role and the molecular pathways in which PIP is involved are poorly understood, we conducted combined gene expression profiling and network analysis studies on selected breast cancer cell lines presenting distinct PIP expression levels and hormonal receptor status, to explore the functional and regulatory network of PIP co-modulated genes.
Principal Findings
Microarray analysis allowed identification of genes co-modulated with PIP independently of modulations resulting from hormonal treatment or cell line heterogeneity. Relevant clusters of genes that can discriminate between [PIP+] and [PIP−] cells were identified. Functional and regulatory network analyses based on a knowledge database revealed a master network of PIP co-modulated genes, including many interconnecting oncogenes and tumor suppressor genes, half of which were detected as differentially expressed through high-precision measurements. The network identified appears associated with an inhibition of proliferation coupled with an increase of apoptosis and an enhancement of cell adhesion in breast cancer cell lines, and contains many genes with a STAT5 regulatory motif in their promoters.
Conclusions
Our global exploratory approach identified biological pathways modulated along with PIP expression, providing further support for its good prognostic value of disease-free survival in breast cancer. Moreover, our data pointed to the importance of a regulatory subnetwork associated with PIP expression in which STAT5 appears as a potential transcriptional regulator.
doi:10.1371/journal.pone.0004696
PMCID: PMC2650800  PMID: 19262752
15.  Sharing knowledge: a new frontier for public-private partnerships in medicine 
Genome Medicine  2009;1(3):29.
To help overcome the bottlenecks that limit the development of diagnostic and therapeutic products, academic and industrial researchers, patient organizations and charities, and regulatory and funding institutions should redefine the basis for sharing the knowledge collected in large-scale clinical and experimental studies.
doi:10.1186/gm29
PMCID: PMC2664940  PMID: 19341500
16.  Systems medicine: the future of medical genomics and healthcare 
Genome Medicine  2009;1(1):2.
High-throughput technologies for DNA sequencing and for analyses of transcriptomes, proteomes and metabolomes have provided the foundations for deciphering the structure, variation and function of the human genome and relating them to health and disease states. The increased efficiency of DNA sequencing opens up the possibility of analyzing a large number of individual genomes and transcriptomes, and complete reference proteomes and metabolomes are within reach using powerful analytical techniques based on chromatography, mass spectrometry and nuclear magnetic resonance. Computational and mathematical tools have enabled the development of systems approaches for deciphering the functional and regulatory networks underlying the behavior of complex biological systems. Further conceptual and methodological developments of these tools are needed for the integration of various data types across the multiple levels of organization and time frames that are characteristic of human development, physiology and disease. Medical genomics has attempted to overcome the initial limitations of genome-wide association studies and has identified a limited number of susceptibility loci for many complex and common diseases. Iterative systems approaches are starting to provide deeper insights into the mechanisms of human diseases, and to facilitate the development of better diagnostic and prognostic biomarkers for cancer and many other diseases. Systems approaches will transform the way drugs are developed through academy-industry partnerships that will target multiple components of networks and pathways perturbed in diseases. They will enable medicine to become predictive, personalized, preventive and participatory, and, in the process, concepts and methods from Western and oriental cultures can be combined. We recommend that systems medicine should be developed through an international network of systems biology and medicine centers dedicated to inter-disciplinary training and education, to help reduce the gap in healthcare between developed and developing countries.
doi:10.1186/gm2
PMCID: PMC2651587  PMID: 19348689
17.  Protein subnetwork markers improve prediction of cancer outcome 
doi:10.1038/msb4100183
PMCID: PMC2063583  PMID: 17940531
18.  The Cytoskeleton-associated PDZ-LIM Protein, ALP, Acts on Serum Response Factor Activity to Regulate Muscle Differentiation 
Molecular Biology of the Cell  2007;18(5):1723-1733.
In this report, an antisense RNA strategy has allowed us to show that disruption of ALP expression affects the expression of the muscle transcription factors myogenin and MyoD, resulting in the inhibition of muscle differentiation. Introduction of a MyoD expression construct into ALP-antisense cells is sufficient to restore the capacity of the cells to differentiate, illustrating that ALP function occurs upstream of MyoD. It is known that MyoD is under the control of serum response factor (SRF), a transcriptional regulator whose activity is modulated by actin dynamics. A dramatic reduction of actin filament bundles is observed in ALP-antisense cells and treatment of these cells with the actin-stabilizing drug jasplakinolide stimulates SRF activity and restores the capacity of the cells to differentiate. Furthermore, we show that modulation of ALP expression influences SRF activity, the level of its coactivator, MAL, and muscle differentiation. Collectively, these results suggest a critical role of ALP on muscle differentiation, likely via cytoskeletal regulation of SRF.
doi:10.1091/mbc.E06-09-0815
PMCID: PMC1855033  PMID: 17332502
19.  Deciphering cellular states of innate tumor drug responses 
Genome Biology  2006;7(3):R19.
Transcriptional profiling of colorectal cancer samples collected before chemotherapy provides cellular signatures that differentiate subsequently diagnosed chemosensitive and resistant patients.
Background
The molecular mechanisms underlying innate tumor drug resistance, a major obstacle to successful cancer therapy, remain poorly understood. In colorectal cancer (CRC), molecular studies have focused on drug-selected tumor cell lines or individual candidate genes using samples derived from patients already treated with drugs, so that very little data are available prior to drug treatment.
Results
Transcriptional profiles of clinical samples collected from CRC patients prior to their exposure to a combined chemotherapy of folinic acid, 5-fluorouracil and irinotecan were established using microarrays. Vigilant experimental design, power simulations and robust statistics were used to restrain the rates of false negative and false positive hybridizations, allowing successful discrimination between drug resistance and sensitivity states with restricted sampling. A list of 679 genes was established that intrinsically differentiates, for the first time prior to drug exposure, subsequently diagnosed chemo-sensitive and resistant patients. Independent biological validation performed through quantitative PCR confirmed the expression pattern on two additional patients. Careful annotation of interconnected functional networks provided a unique representation of the cellular states underlying drug responses.
Conclusion
Molecular interaction networks are described that provide a solid foundation on which to anchor working hypotheses about mechanisms underlying in vivo innate tumor drug responses. These broad-spectrum cellular signatures represent a starting point from which by-pass chemotherapy schemes, targeting simultaneously several of the molecular mechanisms involved, may be developed for critical therapeutic intervention in CRC patients. The demonstrated power of this research strategy makes it generally applicable to other physiological and pathological situations.
doi:10.1186/gb-2006-7-3-r19
PMCID: PMC1557757  PMID: 16542501
20.  Integration of Myeloblastosis Associated Virus proviral sequences occurs in the vicinity of genes encoding signaling proteins and regulators of cell proliferation 
Aims
Myeloblastosis Associated Virus type 1 (N) [MAV 1(N)] induces specifically nephroblastomas in 8–10 weeks when injected to newborn chicken. The MAV-induced nephroblastomas constitute a unique animal model of the pediatric Wilms' tumor. We have made use of three independent nephroblastomas that represent increasing tumor grades, to identify the host DNA regions in which MAV proviral sequences were integrated. METHODS Cellular sequences localized next to MAV-integration sites in the tumor DNAs were used to screen a Bacterial Artificial Chromosomes (BACs) library and isolate BACs containing about 150 kilobases of normal DNA corresponding to MAV integration regions (MIRs). These BACs were mapped on the chicken chromosomes by Fluorescent In Situ Hybridization (FISH) and used for molecular studies.
Results
The different MAV integration sites that were conserved after tumor cell selection identify genes involved in the control of cell signaling and proliferation. Syntenic fragments in human DNA contain genes whose products have been involved in normal and pathological kidney development, and several oncogenes responsible for tumorigenesis in human.
Conclusion
The identification of putative target genes for MAV provides important clues for the understanding of the MAV pathogenic potential. These studies identified ADAMTS1 as a gene upregulated in MAV-induced nephroblastoma and established that ccn3/nov is not a preferential site of integration for MAV as previously thought. The present results support our hypothesis that the highly efficient and specific MAV-induced tumorigenesis results from the alteration of multiple target genes in differentiating blastemal cells, some of which are required for the progression to highly aggressive stages. This study reinforces our previous conclusions that the MAV-induced nephroblastoma constitutes an excellent model in which to characterize new potential oncogenes and tumor suppressors involved in the establishment and maintenance of tumors.
doi:10.1186/1478-811X-4-1
PMCID: PMC1368981  PMID: 16403231
22.  Towards standardization of RNA quality assessment using user-independent classifiers of microcapillary electrophoresis traces 
Nucleic Acids Research  2005;33(6):e56.
While it is universally accepted that intact RNA constitutes the best representation of the steady-state of transcription, there is no gold standard to define RNA quality prior to gene expression analysis. In this report, we evaluated the reliability of conventional methods for RNA quality assessment including UV spectroscopy and 28S:18S area ratios, and demonstrated their inconsistency. We then used two new freely available classifiers, the Degradometer and RIN systems, to produce user-independent RNA quality metrics, based on analysis of microcapillary electrophoresis traces. Both provided highly informative and valuable data and the results were found highly correlated, while the RIN system gave more reliable data. The relevance of the RNA quality metrics for assessment of gene expression differences was tested by Q-PCR, revealing a significant decline of the relative expression of genes in RNA samples of disparate quality, while samples of similar, even poor integrity were found highly comparable. We discuss the consequences of these observations to minimize artifactual detection of false positive and negative differential expression due to RNA integrity differences, and propose a scheme for the development of a standard operational procedure, with optional registration of RNA integrity metrics in public repositories of gene expression data.
doi:10.1093/nar/gni054
PMCID: PMC1072807  PMID: 15800207
23.  Identification of genes involved in ceramide-dependent neuronal apoptosis using cDNA arrays 
Genome Biology  2002;3(8):research0042.1-research0042.22.
A cell-culture model was used to establish a profile of gene expression during the effector phase of ceramide-mediated cell death. Of the 239 genes that met the criteria for differential hybridization, 10 correspond to genes previously involved in C2-ceramide or TNF-α signaling pathways and 20 in neuronal disorders, oncogenesis or more broadly in the regulation of proliferation.
Background
Ceramide is important in many cell responses, such as proliferation, differentiation, growth arrest and apoptosis. Elevated ceramide levels have been shown to induce apoptosis in primary neuronal cultures and neuronally differentiated PC 12 cells.
Results
To investigate gene expression during ceramide-dependent apoptosis, we carried out a global study of gene expression in neuronally differentiated PC 12 cells treated with C2-ceramide using an array of 9,120 cDNA clones. Although the criteria adopted for differential hybridization were stringent, modulation of expression of 239 genes was identified during the effector phase of C2-ceramide-induced cell death. We have made an attempt at classifying these genes on the basis of their putative functions, first with respect to known effects of ceramide or ceramide-mediated transduction systems, and then with respect to regulation of cell growth and apoptosis.
Conclusions
Our cell-culture model has enabled us to establish a profile of gene expression during the effector phase of ceramide-mediated cell death. Of the 239 genes that met the criteria for differential hybridization, 10 correspond to genes previously involved in C2-ceramide or TNF-α signaling pathways and 20 in neuronal disorders, oncogenesis or more broadly in the regulation of proliferation. The remaining 209 genes, with or without known functions, constitute a pool of genes potentially implicated in the regulation of neuronal cell death.
PMCID: PMC126236  PMID: 12186649

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