A Systems Biology Approach for Understanding Granuloma Formation and Function in Tuberculosis

2012 ◽  
pp. 127-155 ◽  
Author(s):  
Mohammad Fallahi-Sichani ◽  
Simeone Marino ◽  
JoAnne L. Flynn ◽  
Jennifer J. Linderman ◽  
Denise E. Kirschner
Keyword(s):  
Systems Biology ◽  
Granuloma Formation ◽  
And Function

scholarly journals Systems biology analysis of omeprazole therapy in cirrhosis demonstrates significant shifts in gut microbiota composition and function

2014 ◽  
Vol 307 (10) ◽  
pp. G951-G957 ◽  
Author(s):  
Jasmohan S. Bajaj ◽  
I. Jane Cox ◽  
Naga S. Betrapally ◽  
Douglas M. Heuman ◽  
Mitchell L. Schubert ◽  
...  
Keyword(s):  
Systems Biology ◽  
Gut Microbiota ◽  
Serum Gastrin ◽  
Bacterial Overgrowth ◽  
Infectious Complications ◽  
Functional Change ◽  
Microbiota Composition ◽  
And Function ◽  
Stool Microbiota ◽  
Gut Microbiota Composition

Proton pump inhibitors (PPI) have been associated with infectious complications in cirrhosis, but their impact on distal gut microbiota composition and function is unclear. We aimed to evaluate changes in stool microbiota composition and function in patients with cirrhosis and healthy controls after omeprazole therapy. Both 15 compensated cirrhotic patients and 15 age-matched controls underwent serum gastrin measurement, stool microbiota profiling with multitagged pyrosequencing, and urinary metabolic profiling with NMR spectroscopy to assess microbial cometabolites before/after a 14-day course of 40 mg/day omeprazole under constant diet conditions. Results before (pre) and after PPI were compared in both groups, compared with baseline by systems biology techniques. Adherence was >95% without changes in diet or MELD (model for end-stage liver disease) score during the study. Serum gastrin concentrations significantly increased after PPI in cirrhosis (pre 38.3 ± 35.8 vs. 115.6 ± 79.3 pg/ml P < 0.0001) and controls (pre 29.9 ± 14.5 vs. 116.0 ± 74.0 pg/ml, P = 0.001). A significant microbiota change was seen in both controls and cirrhosis after omeprazole (QIIME P < 0.0001). Relative Streptococcaceae abundance, normally abundant in saliva, significantly increased postomeprazole in controls (1 vs. 5%) and cirrhosis (0 vs. 9%) and was correlated with serum gastrin levels ( r = 0.4, P = 0.005). We found significantly reduced hippurate in cirrhosis vs. controls both pre- and postomeprazole and increased lactate in both groups post vs. preomeprazole, whereas dimethylamine (DMA) decreased in cirrhosis only. On correlation network analysis, significant changes in linkages of bacteria with metabolites (hippurate/DMA/lactate) were found postomeprazole, compared with pre-PPI in cirrhosis patients. In conclusion, omeprazole is associated with a microbiota shift and functional change in the distal gut in patients with compensated cirrhosis that could set the stage for bacterial overgrowth.

Complex systems in pulmonary medicine: a systems biology approach to lung disease

2011 ◽  
Vol 110 (6) ◽  
pp. 1716-1722 ◽  
Author(s):  
David A. Kaminsky ◽  
Charles G. Irvin ◽  
Peter J. Sterk
Keyword(s):  
Systems Biology ◽  
Lung Disease ◽  
Clinical Medicine ◽  
Molecular Genetic ◽  
Whole Body ◽  
Pulmonary Medicine ◽  
Pulmonary Physiology ◽  
The Many ◽  
And Function ◽  
Work Done

The lung is a highly complex organ that can only be understood by integrating the many aspects of its structure and function into a comprehensive view. Such a view is provided by a systems biology approach, whereby the many layers of complexity, from the molecular genetic, to the cellular, to the tissue, to the whole organ, and finally to the whole body, are synthesized into a working model of understanding. The systems biology approach therefore relies on the expertise of many disciplines, including genomics, proteomics, metabolomics, physiomics, and, ultimately, clinical medicine. The overall structure and functioning of the lung cannot be predicted from studying any one of these systems in isolation, and so this approach highlights the importance of emergence as the fundamental feature of systems biology. In this paper, we will provide an overview of a systems biology approach to lung disease by briefly reviewing the advances made at many of these levels, with special emphasis on recent work done in the realm of pulmonary physiology and the analysis of clinical phenotypes.

scholarly journals Monocytes in sarcoidosis are potent TNF producers and predict disease outcome

2021 ◽  
pp. 2003468
Author(s):  
Rico Lepzien ◽  
Sang Liu ◽  
Paulo Czarnewski ◽  
Mu Nie ◽  
Björn Österberg ◽  
...  
Keyword(s):  
Progressive Disease ◽  
Pulmonary Sarcoidosis ◽  
Mononuclear Phagocytes ◽  
Granuloma Formation ◽  
Disease Outcome ◽  
Healthy Controls ◽  
High Frequencies ◽  
And Function ◽  
Intermediate Monocytes

BackgroundPulmonary sarcoidosis is an inflammatory disease characterised by granuloma formation and heterogeneous clinical outcome. TNF is a proinflammatory cytokine contributing to granuloma formation and high levels of TNF have been shown to associate with progressive disease. Mononuclear phagocytes (MNPs) are potent producers of TNF and highly responsive to inflammation. In sarcoidosis, alveolar macrophages (AMs) have been well studied. However, MNPs also include monocytes/monocyte-derived cells and dendritic cells (DCs) that despite their central role in inflammation are poorly studied in sarcoidosis.ObjectiveTo determine the role of pulmonary monocyte-derived cells and DCs during sarcoidosis.MethodsWe performed in-depth phenotypic, functional and transcriptomic analysis of MNPs subsets from blood and bronchoalveolar lavage (BAL) fluid from 108 sarcoidosis patients and 30 healthy controls. We followed the clinical development of patients and assessed how the repertoire and function of MNP subsets at diagnosis correlated with 2-year disease outcome.ResultsMonocytes/monocyte-derived cells were increased in blood and BAL of sarcoidosis patients compared to healthy controls. Interestingly, high frequencies of blood intermediate monocytes at time of diagnosis associated with chronic disease development. RNAseq analysis showed highly inflammatory MNPs in BAL of sarcoidosis patients. Furthermore, frequencies of BAL monocytes/monocyte-derived cells producing TNF without exogenous stimulation at time of diagnosis increased in patients that were followed longitudinally. In contrast to AMs, the frequency of TNF producing BAL monocytes/monocyte-derived cells at time of diagnosis was highest in sarcoidosis patients that developed progressive disease.ConclusionOur data show that pulmonary monocytes/monocyte-derived cells are highly inflammatory and can be used as a predictor of disease outcome in sarcoidosis patients.

scholarly journals A zebrafish model for Mycobacterium leprae granulomatous infection

2017 ◽  
Author(s):  
Cressida A. Madigan ◽  
James Cameron ◽  
Lalita Ramakrishnan
Keyword(s):  
Animal Models ◽  
Experimental Animal ◽  
Mycobacterium Leprae ◽  
Granuloma Formation ◽  
Granulomatous Disease ◽  
Zebrafish Model ◽  
Experimental Animal Models ◽  
Adaptive Immune ◽  
Noncaseating Granulomas ◽  
And Function

AbstractUnderstanding the pathogenesis of leprosy granulomas has been hindered by a paucity of tractable experimental animal models. Mycobacterium leprae, which causes leprosy, grows optimally at ~30°C, so we sought to model granulomatous disease in the ectothermic zebrafish. We find noncaseating granulomas develop rapidly, and eventually eradicate infection. rag1 mutant zebrafish, which lack lymphocytes, also form noncaseating granulomas with similar kinetics, but these control infection more slowly. Our findings establish the zebrafish as a facile, genetically tractable model for leprosy, and reveal the interplay between innate and adaptive immune determinants mediating leprosy granuloma formation and function.

Aquamoleculomics: A Thermodynamic Cornerstone of Systems Biology

2021 ◽  
Author(s):  
Zilin Nie ◽  
Yanming Nie
Keyword(s):  
Systems Biology ◽  
Thermodynamic Characteristics ◽  
Living System ◽  
Structure And Function ◽  
Biological Processes ◽  
Modern Biology ◽  
Cell Tissue ◽  
Novel Concept ◽  
And Function ◽  
Current Systems

Systems biology has been established for more than a decade in the post-genomic era. With the help of the computational and mathematical tools, systems biology reconstitutes the entire scenario of the cell, tissue and even organism from the pieces data generated in the past decades. However, the modern biology is mainly focusing on the structure and function of the biomolecule, cell, tissue or organ, which are far from the essence of the life because of missing thermodynamic information. It is doubtable that the current systems biology-based omics is no-how to fully understand the dynamic courses of the structure, function and information in life. For this reason, we promote a novel concept of aquamoleculomics, in which the biological structure and function as well as thermodynamic characteristics and bioinformation of the aquamolecule complexes are included in this theoretical model of systems biology. Water is mother of life, matter and matrix of organism. Indeed, the fundamental roles of H2O molecules in biological processes might be dramatically underestimated. Extremely speaking, H2O networks in the living system might be engaged in all the biological processes including building all the biological structures, the residential places of the motherhood molecules as the honeycombs of honeybees.

Computer Aided Knowledge Discovery in Biomedicine

2012 ◽  
pp. 1389-1403
Author(s):  
Vanathi Gopalakrishnan
Keyword(s):  
Protein Structure ◽  
Systems Biology ◽  
Knowledge Discovery ◽  
Structure Prediction ◽  
Biomarker Discovery ◽  
Protein Structure Determination ◽  
Mass Spectral ◽  
Computer Aided ◽  
And Function ◽  
Macromolecular Crystallization

This chapter provides a perspective on 3 important collaborative areas in systems biology research. These areas represent biological problems of clinical significance. The first area deals with macromolecular crystallization, which is a crucial step in protein structure determination. The second area deals with proteomic biomarker discovery from high-throughput mass spectral technologies; while the third area is protein structure prediction and complex fold recognition from sequence and prior knowledge of structure properties. For each area, successful case studies are revisited from the perspective of computer- aided knowledge discovery using machine learning and statistical methods. Information about protein sequence, structure, and function is slowly accumulating in standardized forms within databases. Methods are needed to maximize the use of this prior information for prediction and analysis purposes. This chapter provides insights into such methods by which available information in existing databases can be processed and combined with systems biology expertise to expedite biomedical discoveries.

Computer Aided Knowledge Discovery in Biomedicine

2009 ◽  
pp. 126-141
Author(s):  
Vanathi Gopalakrishnan
Keyword(s):  
Protein Structure ◽  
Systems Biology ◽  
Knowledge Discovery ◽  
Structure Prediction ◽  
Biomarker Discovery ◽  
Protein Structure Determination ◽  
Mass Spectral ◽  
Computer Aided ◽  
And Function ◽  
Macromolecular Crystallization

This chapter provides a perspective on 3 important collaborative areas in systems biology research. These areas represent biological problems of clinical significance. The first area deals with macromolecular crystallization, which is a crucial step in protein structure determination. The second area deals with proteomic biomarker discovery from high-throughput mass spectral technologies; while the third area is protein structure prediction and complex fold recognition from sequence and prior knowledge of structure properties. For each area, successful case studies are revisited from the perspective of computer- aided knowledge discovery using machine learning and statistical methods. Information about protein sequence, structure, and function is slowly accumulating in standardized forms within databases. Methods are needed to maximize the use of this prior information for prediction and analysis purposes. This chapter provides insights into such methods by which available information in existing databases can be processed and combined with systems biology expertise to expedite biomedical discoveries.

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