In brief (April 2013) – Microbiome, gender and diabetes; stealth nanoparticles and anticancer drug; (not quite) dream reading

Three picks from what I’ve read over the past two months:
microbiome, gender and diabetes, or how gut bacteria influence susceptibility to disease in females versus males in a mouse model of type 1 diabetes,
stealth nanoparticles and drug delivery, or how a short chain of amino acids can get anticancer drug-carrying nanoparticles past the defenses of the immune system,
(not quite) dream reading, or how researchers can approximately tell what kind of images are going trough your mind in the stage 1 of sleep.

  • Microbiome, gender and diabetes

Many autoimmune diseases are more frequent in women than in men (a typical example being lupus), however the reasons for this gender bias are not well understood. In the past few years, researchers interested in microbiota (the bacteria living in/on another organism) and how it interacts with its host have started to discover how our microbiota participates in shaping our immune system. A study published in Science in March now shows that sex differences in the composition of the microbiota contribute to gender bias in susceptibility to type 1 diabetes in a mouse model.

The Canadian research team who performed the study used a mouse strain called NOD (for non-obese diabetic) that is genetically highly susceptible to type 1 diabetes. When housed in normal conditions, about twice as many female mice spontaneously develop diabetes compared to male mice. However, the researchers found that this difference disappeared when the mice were bred and raised in germ-free conditions. They also observed changes in testosterone levels in germ-free mice compared to “regular” ones, indicating that the microbiota influences sex hormone levels in the host. Conversely, researchers also found that sex hormones modulate the composition of gut microbiota: while there were no differences in the bacteria strains that made up the gut microbiota in male and female mice at 3 weeks of age (weaning age), some differences were visible at 6 weeks of age (puberty) and were even more pronounced in adults. To directly study the influence of male versus female microbiota on disease susceptibility, researchers transferred gut bacteria from adult male mice to female ones before they reached puberty (and before disease onset). A few weeks later, the resulting microbiota in these females was not fully “male”, but it was no longer fully “female” either. Importantly, the change was enough to reduce the incidence of type 1 diabetes in these female mice compared to normal females, and researchers additionally found that this effect was dependent on testosterone activity.

On the whole, this study shows that changes in the gut microbiota early in life can modulate disease susceptibility in mice that have a strong genetic predisposition to develop the disease, and it identifies a direct interaction between commensal bacteria, sex hormones and disease susceptibility.

(Markle et al., Science 1 March 2013, doi: 10.1126/science.1233521)

  • Stealth nanoparticles and drug delivery

The immune system protects the body against foreign invaders, such as bacteria or viruses. Macrophages are immune cells that are part of the first line of defense, and whose function is to recognize, ingest and destroy foreign particles in a process called phagocytosis. Although this is all well and good when we need to fight infections, it poses a major challenge for therapeutic applications that are based on microscopic particles carrying a drug, for example, an anticancer molecule. Indeed, these nanoparticles are recognized as foreign by the immune system and are quickly disposed of, greatly diminishing their efficacy. In a study published in February in Science, US researchers present a new approach to stop macrophages from destroying drug-carrying nanoparticles.

The team exploited a characteristic of the immune system, which is that it is able to distinguish between foreign invaders (non-self) and the body’s own cells (self). Macrophages recognize a specific “don’t eat me” signal on the surface of the body’s cells, a protein called CD47. Binding of CD47 to the corresponding receptor (called SIRPa) on the macrophage identifies the CD47 carrier as “self” and prevents it from being destroyed by the macrophage. In the study, researchers coated nanobeads with a short chain of amino acids (CD47 peptide) that corresponds to the part of CD47 that interacts with SIRPa. They then injected these beads in mice, along with nanobeads that did not carry the CD47 peptide. After 35 minutes, they observed that there remained 4 times as many CD47 peptide-coated beads as non-coated beads in the mice’s blood. In another experiment, the researchers loaded nanobeads with the anticancer drug paclitaxel and injected them in mice that had tumors. They observed that beads that had also been coated with the CD47 peptide shrank tumors more than ones that had not been coated with the CD47 peptide.

This new approach to getting nanoparticles past the immune system has now to be tried in humans, but if it proves safe and does its job well, it could make nanomedicines currently in clinical trials even more effective.

(Rodriguez et al., Science 22 February 2013, doi: 10.1126/science.1229568)

  • (Not quite) dream reading

Reading someone’s mind, whether that someone is awake or asleep, sounds like science fiction. However, a study recently published online in Science reveals that a team of researchers in Japan has taken one step further towards identifying what a (lightly) sleeping person is “seeing”.

Dreaming is usually associated with a certain sleep stage, called rapid eye movement (REM) sleep. However, as it takes one hour or more to reach this phase after falling asleep, the researchers chose to study the hallucinations that often occur in the stage 1 of sleep, when people start to doze off. They used fMRI (functional magnetic resonance imaging) to record brain activity in three volunteers as they were falling asleep. After being allowed to slip into sleep stage 1, the study subjects were awoken and asked about what they had “seen”. This process was repeated several times during 3-hr sessions over ten days until about 200 fMRI scans and corresponding verbal reports were available for each volunteer. Next the researchers analyzed the words present in the reports, grouping them in broad semantic categories. They then took new fMRI recordings from the same volunteers, this time while they were awake and looking at images corresponding to the different semantic categories. These recordings were used to train a computer program to associate fMRI brain activity patterns with categories of images for each individual. When the researchers finally tested this program on the initial fMRI recordings taken when the volunteers were asleep (stage 1), they found that it could detect the presence/absence of a semantic category in the dream-like hallucinations with above-chance levels. When using a program that had been trained on two specific categories, for example “food” and “furniture”, and testing it on fMRI records that corresponded to sleep periods in which the volunteer had reported seeing one of these categories, for example “food”, but not the other, they found that the mean accuracy of the decoding program (tried for many pairs of categories) was 60%, higher than what it would be by chance (which is 50%).

On the whole, although it is not quite yet the level of “dream-reading” of science fiction stories, this study shows that the visual experiences during sleep share some brain activity patterns with visual experiences when awake, and that a machine can be trained to associate blood flow changes in the brain with groups of images. And at the very least, it provides evidence that we don’t just make up our dreams when we wake up.

(Horikawa et al., Science online 4 April 2013, doi: 10.1126/science.1234330)


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