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Mapping human microbiome drug metabolism by gut bacteria and their genes | Nature

Individuals vary widely in their responses to medicinal drugs, which can be dangerous and expensive owing to treatment delays and adverse effects. Although increasing evidence implicates the gut microbiome in this variability, the molecular mechanisms involved remain largely unknown. Here we show, by measuring the ability of 76 human gut bacteria from diverse clades to metabolize 271 orally administered drugs, that many drugs are chemically modified by microorganisms.

The 'pathobiome' -- a new understanding of disease -- ScienceDaily

The concept acknowledges that all organisms are in fact complex communities of viruses, microbes and other small organisms (e.g. parasites) which can interact to affect health or disease status at any given time. These complex communities continually interact with their hosts, sometimes conferring benefits (e.g. "good" bacteria in the human gut microbiome), and at other times causing harm by contributing to disease. When these communities combine to cause disease they are termed "pathobiomes" -- a recognition of their collective shift away from the healthy-state "symbiome."

Computer crashes repeatedly in final 4 minutes of Apollo landing


Unexplored neural circuit modulates memory strength -- ScienceDaily


Four Rules To Guide Expectations Of Artificial Intelligence


Fireflies, Heart Beats, and the Science of Sync – Neuroscience News

“The perplexing feature of these particular states is that the Rockettes in our metaphor can only see their nearest neighbor, yet manage to be coordinating with their neighbor’s neighbor,” says lead author Matthew Matheny, a research scientist at Caltech and member of the Kavli Nanoscience Institute. “We didn’t know what we were going to see,” says Matheny. “But what these experiments are telling us is that you can get complexity out of a very simple system. This was something that was hinted at before but not shown experimentally until now.” “These exotic states arising from a simple system are what we call emergent,” says Roukes. “The whole is greater than the sum of the parts.”


But it has also been observed since the early 2000s that these networks, even when consisting of identical oscillators, can spontaneously flip out of sync and evolve into complex patterns. To better understand what is going on, Roukes and colleagues began to develop networks of oscillating nanomechanical devices. They started by just connecting two, and now, in the new study, have developed an interconnected system of eight. To the team’s surprise, the eight-node system spontaneously evolved into various exotic, complex states. “This is the first experimental demonstration that these many distinct, complex states can occur in the same simple system,” says co-author James Crutchfield, a visiting associate in physics at Caltech and a professor of physics at UC Davis.

Applying a network perspective to human physiology: Physicist describes 'network physiology,' which looks at different organ systems and how they relate to each other -- ScienceDaily

"We need to show how the different systems communicate with each other and adjust, coordinate and stay in sync," said Ivanov. The human body, according to this view, can be thought of as a network, with each organ serving as a node connected to other organs and other nodes. "The nodes are not just dots," he said. "They're dynamical systems, constantly changing in time, as are the connections between them." Today's best hospitals aren't equipped to monitor the inter-organ interactions. "Separate devices keep track of separate functions, but no single monitor can observe a multitude of functions," he said. To improve health monitoring techniques, Ivanov and his colleagues have spent the past decade developing the computational tools and biomedical devices needed to capture data streams from different organ systems and see how they relate to each other.






This debate was resolved in a seminal 1918 paper by R.A. Fisher, who showed that, if many genes affect a trait, then the random sampling of alleles at each gene produces a continuous, normally distributed phenotype in the population (Fisher, 1918). As the number of genes grows very large, the contribution of each gene becomes correspondingly smaller, leading in the limit to Fisher’s famous “infinitesimal model” (Barton et al., 2016).


“What we realized was that the signal for height was coming from almost the whole genome,” he said. If the genome were a long string of ornamental lights, and every DNA snippet linked to height were illuminated, more than 100,000 lights would be shining all the way down the string. That result contrasted starkly with the general expectation that GWAS findings would be clustered around the most important genes for a trait.

Everything big data claims to know about you could be wrong: To understand human health and behavior, researchers would do better to study individuals, not groups -- ScienceDaily

"If you want to know what individuals feel or how they become sick, you have to conduct research on individuals, not on groups," said study lead author Aaron Fisher, an assistant professor of psychology at UC Berkeley. "Diseases, mental disorders, emotions, and behaviors are expressed within individual people, over time. A snapshot of many people at one moment in time can't capture these phenomena." Moreover, the consequences of continuing to rely on group data in the medical, social and behavioral sciences include misdiagnoses, prescribing the wrong treatments and generally perpetuating scientific theory and experimentation that is not properly calibrated to the differences between individuals, Fisher said.

Timing is everything, to our genes -- ScienceDaily

Using RNA sequencing, the research team tracked gene expression in dozens of different non-human primate tissues every 2 hours for 24 hours. The team found that each tissue contained genes that were expressed at different levels based on the time of day. However, the number of these "rhythmic" genes varied by tissue type, from around 200 in pineal, mesenteric lymph nodes, bone marrow and other tissues to more than 3,000 in prefrontal cortex, thyroid, gluteal muscle and others. In addition, genes that were expressed most often tended to show more rhythmicity, or variability by time. Of the 25,000 genes in the primate genome, nearly 11,000 were expressed in all tissues. Of those (which mostly govern routine cellular functions, such as DNA repair and energy metabolism), 96.6 percent were particularly rhythmic in at least one tissue, varying drastically by when they were sampled.

Keeping up the pressure: New neural mechanism is found to regulate the chronic stress response -- ScienceDaily

The newly discovered nerve cells express a receptor, CRFR1, on their outer walls, which enables them to take in the message of the CRF neurotransmitter. The scientists' experiments showed that, in mice, the cortisol actually increases the number of CRFR1 receptors on these nerve cells, suggesting a positive feedback loop that could be self-renewing, rather than abating.

» The Collapse of Complex Business Models Clay Shirky


30 neurons act very differently, depending on chemical soup

Eve Marder, a prominent neuroscientist at Brandeis University, cautions against expecting too much from the connectome. She studies neurons that control the stomachs of crabs and lobsters. In these relatively simple systems of 30 or so neurons, she has shown that neuromodulators — signaling chemicals that wash across regions of the brain, omitted from Seung’s static map — can fundamentally change how a circuit functions. If this is true for the stomach of a crustacean, the mind reels to consider what may be happening in the brain of a mouse, not to mention a human.