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.

Precision Oncology: Between Vaguely Right and Precisely Wrong

Abstract: Precision Oncology seeks to identify and target the mutation that drives a tumor. Despite its straightforward rationale, concerns about its effectiveness are mounting. What is the biological explanation for the "imprecision?" First, Precision Oncology relies on indiscriminate sequencing of genomes in biopsies that barely represent the heterogeneous mix of tumor cells. Second, findings that defy the orthodoxy of oncogenic "driver mutations" are now accumulating: the ubiquitous presence of oncogenic mutations in silent premalignancies or the dynamic switching without mutations between various cell phenotypes that promote progression. Most troublesome is the observation that cancer cells that survive treatment still will have suffered cytotoxic stress and thereby enter a stem cell-like state, the seeds for recurrence. The benefit of "precision targeting" of mutations is inherently limited by this counterproductive effect. These findings confirm that there is no precise linear causal relationship between tumor genotype and phenotype, a reminder of logician Carveth Read's caution that being vaguely right may be preferable to being precisely wrong. An open-minded embrace of the latest inconvenient findings indicating nongenetic and "imprecise" phenotype dynamics of tumors as summarized in this review will be paramount if Precision Oncology is ultimately to lead to clinical benefits. Cancer Res; 77(23); 6473-9. ©2017 AACR.

Salmonella and Caspase-1: A complex Interplay of Detection and Evasion.

Abstract: Salmonellae are intracellular pathogens that replicate within epithelial cells and macrophages, and are a significant public health threat in both developed and developing countries. The innate immune system detects microbes through pattern recognition receptors, which are compartmentalized on the subcellular level to detect either extracellular (e.g. TLRs) or cytosolic (e.g. NLRs) perturbations. Salmonella infection is detected by the NLRC4 and NLRP3 inflammasomes, which activate Caspase-1, resulting in reduced bacterial burdens during infection. NLRC4 responds to the SPI1 type III secretion system via detection of inadvertently translocated flagellin and rod protein. The signals for NLRP3 detection during Salmonella infection remain undefined. Salmonella have evolved evasion strategies to attenuate Caspase-1 responses. We review recent findings describing the interplay between detection and evasion of S. typhimurium infection by the inflammasome. We discuss how the interplay between detection and evasion affects Caspase-1 effector functions mediated by IL-1β secretion, IL-18 secretion, and pyroptosis.

Model-driven analysis of experimentally determined growth phenotypes for 465 yeast gene deletion mutants under 16 different conditions

Abstract: Background Understanding the response of complex biochemical networks to genetic perturbations and environmental variability is a fundamental challenge in biology. Integration of high-throughput experimental assays and genome-scale computational methods is likely to produce insight otherwise unreachable, but specific examples of such integration have only begun to be explored.

Macromolecular networks and intelligence in microorganisms.

Abstract: Living organisms persist by virtue of complex interactions among many components organized into dynamic, environment-responsive networks that span multiple scales and dimensions. Biological networks constitute a type of information and communication technology (ICT): they receive information from the outside and inside of cells, integrate and interpret this information, and then activate a response. Biological networks enable molecules within cells, and even cells themselves, to communicate with each other and their environment. We have become accustomed to associating brain activity - particularly activity of the human brain - with a phenomenon we call "intelligence." Yet, four billion years of evolution could have selected networks with topologies and dynamics that confer traits analogous to this intelligence, even though they were outside the intercellular networks of the brain. Here, we explore how macromolecular networks in microbes confer intelligent characteristics, such as memory, anticipation, adaptation and reflection and we review current understanding of how network organization reflects the type of intelligence required for the environments in which they were selected. We propose that, if we were to leave terms such as "human" and "brain" out of the defining features of "intelligence," all forms of life - from microbes to humans - exhibit some or all characteristics consistent with "intelligence." We then review advances in genome-wide data production and analysis, especially in microbes, that provide a lens into microbial intelligence and propose how the insights derived from quantitatively characterizing biomolecular networks may enable synthetic biologists to create intelligent molecular networks for biotechnology, possibly generating new forms of intelligence, first in silico and then in vivo.