Institute for Systems Biology

About: Institute for Systems Biology is a nonprofit organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Population & Proteomics. The organization has 1277 authors who have published 2777 publications receiving 353165 citations.

TL1A–DR3 interaction regulates Th17 cell function and Th17-mediated autoimmune disease

Abstract: T helper type 17 (Th17) cells play an important pathogenic function in autoimmune diseases; their regulation, however, is not well understood. We show that the expression of a tumor necrosis factor receptor family member, death receptor 3 (DR3; also known as TNFRSF25), is selectively elevated in Th17 cells, and that TL1A, its cognate ligand, can promote the proliferation of effector Th17 cells. To further investigate the role of the TL1A–DR3 pathway in Th17 regulation, we generated a TL1A-deficient mouse and found that TL1A−/− dendritic cells exhibited a reduced capacity in supporting Th17 differentiation and proliferation. Consistent with these data, TL1A−/− animals displayed decreased clinical severity in experimental autoimmune encephalomyelitis (EAE). Finally, we demonstrated that during EAE disease progression, TL1A was required for the optimal differentiation as well as effector function of Th17 cells. These observations thus establish an important role of the TL1A–DR3 pathway in promoting Th17 cell function and Th17-mediated autoimmune disease.

Label-free quantitative detection of tumor-derived exosomes through surface plasmon resonance imaging.

Abstract: Exosomes are endosome-derived membrane vesicles carrying proteins and nucleic acids that are involved in cellular functions such as intercellular communication, protein and RNA secretion, and antigen presentation. Therefore, exosomes serve as potential biomarkers for many diseases including cancer. Because exosomes are difficult to enrich or purify from biofluids, quantification of exosomes is tedious and inaccurate. Here, we present a real-time, label-free, and quantitative method to detect and characterize tumor-derived exosomes without enrichment or purification. Utilizing surface plasmon resonance imaging (SPRi) in combination with antibody microarrays specific to the extracellular domains of exosome membrane proteins, exosomes in tumor cell culture medium can be quantitatively detected. We found a positive correlation between the metastatic potential of tumor cell lines and exosome secretion. This method provides an easy, efficient, and novel way to detect exosome secretion and thus an avenue toward the diagnosis and prognosis prediction of cancer.

Revolutionizing medicine in the 21st century through systems approaches

Abstract: 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 an 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.

Gut microbiome pattern reflects healthy ageing and predicts survival in humans

Abstract: The gut microbiome has important effects on human health, yet its importance in human ageing remains unclear. In the present study, we demonstrate that, starting in mid-to-late adulthood, gut microbiomes become increasingly unique to individuals with age. We leverage three independent cohorts comprising over 9,000 individuals and find that compositional uniqueness is strongly associated with microbially produced amino acid derivatives circulating in the bloodstream. In older age (over ~80 years), healthy individuals show continued microbial drift towards a unique compositional state, whereas this drift is absent in less healthy individuals. The identified microbiome pattern of healthy ageing is characterized by a depletion of core genera found across most humans, primarily Bacteroides. Retaining a high Bacteroides dominance into older age, or having a low gut microbiome uniqueness measure, predicts decreased survival in a 4-year follow-up. Our analysis identifies increasing compositional uniqueness of the gut microbiome as a component of healthy ageing, which is characterized by distinct microbial metabolic outputs in the blood.