Humans Are Superorganisms

colonist writes "You are not completely human. You are a superorganism made up of human cells, fungi, bacteria and viruses. That's the view of scientists from Imperial College London and Astra Zeneca, published in Nature Biotechnology. Microbes in the gut can weigh up to one kilogram, forming the second largest metabolic 'organ'. Human cells and genes are outnumbered by microbial cells and genes. 'Understanding the man-microbe interaction is likely to be crucial in realising personalised medicine and healthcare in the future,' says the lead researcher."

Comments

What's new?

[Finuvir]

What's new here? We've known for a long time that eukaryotic cells contain bacteria that do most of the interesting chemical work for us. Chloroplasts in plants are seperate organisms that photosynthesise. Mytochondria, which are so useful in tracing animal lineages, are bacteria inside animal cells that extract energy from sugars and oxygen (they metabolise for us). Termites in Darwin, Australia (known as Darwins termites) don't digest their own food. That's done by prokaryotes in their gut, which themselves are crowded with other tiny critters that do most of their work (propulsion is done by one set of bacteria which are powered by another group).

For an accessible introduction to this kind of symbiosis, see The Ancestor's Tale: A Pilgrimage to the Dawn of Life by Richard Dawkins.

Re:Huh?

[anthony_dipierro]

Not exactly. A "superorganism is an organism consisting of organisms."

Re:Well

[reverseengineer]

I think the mitochondria argument is in reference to the idea of "endosymbiosis," which suggests that mitochondria (and chloroplasts) were originally independent prokaryotic organisms that were at some stage incorporated into eukaryotic cells, the primary evidence for this being that these organelles have their own DNA. They then became highly specialized at a certain task (aerobic respiration, photosynthesis) and discarded the machinery required for independent survival. The eukaryotic cell benefited by gaining sets of powerful new energy pathways in nice self-contained packages, and the organelles benefited by being passed on whenever eukaryotic organisms reproduced (you have your mother to thank for your mitochondria, as yours descend from the mitochondria of her egg cell). As to whether mitochondria are alive, well, biology has a way of making airtight definitions very difficult- after all, there are plenty of complex species which are completely dependent on other species in order to live and reproduce; we call them parasites.

Now, despite that, I'm personally in the "not an organism" boat, as mitochondria are really not much different from other "opportunistic" pieces of DNA like viruses and plasmids. It just happens that the bag the DNA comes in is extraordinarily useful to the host cell. Indeed, while mitochondria are completely dependent on host cells to reproduce, life on earth would be far different- there'd be no way an ATP-guzzler like the human brain could have evolved without the benefit of aerobic respiration, for instance.

In reference to the whole "humans are superorganisms" idea, one of the things I got from a microbiology course I took in college was the ubiquity of microorganisms on and in the human body- and how their relationship to the host organism can be anything from beneficial to deadly. I think that considering the other billion residents of the body when examining avenues of treatment is a wise move.

Re:Lynn Margulis' Research

[reverseengineer]

Yeah, good point, I was somewhat surprised too. I should have mentioned her in my post, actually- endosymbiosis, which I did mention, is her idea, and along with James Lovelock, so is the Gaia Hypothesis (which admittedly I'm less hot on). The idea of complex organisms as "superorganisms" in symbiosis with their own ecosystem of microbes fits nicely in scale between her two major ideas, one of which is about the relationship between a cell and some of its organelles and the other of which is about the relationship of the entire biosphere to all of its inhabitants.

Re:No surprise for some of us....

[Anonymous Coward]

Just a correction - our digestive system is damn good for what it does. Most of the work of digestion is performed by our digestive system, not our commensal organisms.

Bacteria are great at providing certain things for us - B vitamins is one that springs to mind; but make no mistake - we can digest and absorb most things (carbohydrate, fatty acids, protein, minerals, vitamins) just fine without them.

Nature Biochemistry Article Text

[Anonymous Coward]

Nature Biotechnology 22, 1268 - 1274 (2004)
Published online: 06 October 2004; | doi:10.1038/nbt1015
The challenges of modeling mammalian biocomplexity
Jeremy K Nicholson1, Elaine Holmes1, John C Lindon1 & Ian D Wilson2
1 Biological Chemistry, Biomedical Sciences Division, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, UK.

2 Dept. of Drug Metabolism and Pharmacokinetics, AstraZeneca Pharmaceuticals, Mereside, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK.

Correspondence should be addressed to Jeremy K Nicholson j.nicholson@imperial.ac.uk

Understanding the relationships between human genetic factors, the risks of developing major diseases and the molecular basis of drug efficacy and toxicity is a fundamental problem in modern biology. Predicting biological outcomes on the basis of genomic data is a major challenge because of the interactions of specific genetic profiles with numerous environmental factors that may conditionally influence disease risks in a nonlinear fashion. 'Global' systems biology attempts to integrate multivariate biological information to better understand the interaction of genes with the environment. The measurement and modeling of such diverse information sets is difficult at the analytical and bioinformatic modeling levels. Highly complex animals such as humans can be considered 'superorganisms' with an internal ecosystem of diverse symbiotic microbiota and parasites that have interactive metabolic processes. We now need novel approaches to measure and model metabolic compartments in interacting cell types and genomes that are connected by cometabolic processes in symbiotic mammalian systems.

Human populations face many diverse and aggressive biological challenges, including new infectious agents, antibiotic resistance, the increased incidence of cancer and age-related neurodegenerative conditions and the rapid and insidious rise in insulin resistance. All these problems involve interactions of multiple gene loci, environmental factors and, in many cases, interacting nonhuman genomes. In the quest to improve our understanding of disease processes, researchers have applied advanced analytical platforms to generate new physiological information to complement data supplied by modern genomics1, 2. The hope is that judicious use of genomic knowledge within a framework of physiology and metabolism will yield improvements in the health of whole populations and in the health of individuals by personalized healthcare solutions1, 2, 3, 4.

The growth of a wide range of 'omics' sciences enables the measurement of multiple features of complex systems at various levels of biomolecular organization from the cell to the whole organism3, 4. However, these technologies generate massive amounts of data and it is a major task to model these robustly in a way that allows predictive disease modeling. This is a particular challenge because of the level of complexity of the mammalian system in its entirety, with its many spatially heterogeneous arrays of disparate cell types. Thus, the question is what needs to be measured and modeled to describe the integrated function of the system in a way that can be used to predict modes of failure accurately.

In this review, we consider some aspects of mammalian biocomplexity that are currently poorly understood, but may be of great importance in understanding certain aspects of human disease development and drug action or drug toxicity. We first examine temporal and spatial variation in data, then describe the hierarchy of different systems that can be modeled, including multiple genome interactions, and then conclude by discussing trends in the modeling of systems of increasing levels of complexity.

Timescales of 'omics' events
To measure a system, even at the single-cell level, one must first understand the time-displacement that exists between gene, protein, metabolic and physiological events and their end points3. This is one of the confounding issues to