Can The Microbes You Leave Behind Be Used to Identify You? – Phenomena

 

When you touch a surface, you leave behind fingerprints—distinctive swirling patterns of oils that reveal your identity. You might also deposit traces of DNA, which can also be used to identify you. And you leave microbes. You are constantly bleeding microbes into your surroundings, and whenever you touch something, bacteria hop across from your skin. It’s increasingly clear that everyone has a unique community of microbes—or microbiome—living on their bodies. We share species and strains but the exact roll call varies from person to person. “If you take a collection of people, their microbes will look very different but their genomes will look mostly the same,” says Curtis Huttenhower from the Harvard School of Public Health. So, could the DNA of these tiny variable residents also reveal our identity, just like fingerprints or our own DNA? A few studies have suggested so. In 2010, Noah Fierer from the University of Colorado found that bacteria swabbed from keyboards and mice matched those on their owners’ skins more closely than those from other people. (The match wasn’t quite accurate enough for forensic use, although that didn’t stop CSI Miami from running with it.) And last year, Simon Lax and Jack Gilbert from the University of Chicago managed to identify people, from a pool of 18 volunteers, based on the microbes they left behind in their homes. More recently, Lax and fellow student Sean Gibbons spent two days swabbing their mobile phones, the soles of their shoes, and the floor around them, on an hourly basis, to many strange looks. They found that the shoes and phones retained traces of their owners, so that an algorithm could accurately identify whose items any given sample came from. The objects were also heavily influenced by their environment; the shoes, in particular, quickly picked up microbes from the floors they walked over, suggesting that it might be possible to track a person’s movements from the microbes on their belongings. But what would happen if you scaled these studies up to larger populations? Could you still accurately pinpoint a person using their microbes, without false alarms? Would the results be consistent? And while fingerprints and genomes are largely constant, microbiomes change a lot—so will a person’s abandoned microbes still identify them weeks or months later? To answer these questions, Eric Franzosa and other members of Huttenhower’s team worked with data from the Human Microbiome Project, which collected microbes from the guts, skin, and other body sites of 120 people, at several points in time. They used an algorithm that took data from each volunteer’s first visit, extracted features like the presence of certain species, strains, or genes, and combined the most distinctive ones into a “code” that was unique to each individual, but also consistent over time. They then compared these codes to samples collected several months later to see if they could still identify the right owners. They only managed to recognise a third of their volunteers in this way. That’s nothing to sniff at, but it certainly doesn’t match the forensic utility of the human genome, or even fingerprints. The results were more promising when the team focused on gut microbes, which proved to be exceptionally stable; gut-based codes identified 86 percent of the volunteers. “That’s a floor. The accuracy can only go up if we have more sequencing data and better algorithms,” says Huttenhower. He also notes that “since the microbiome changes over time, we wanted to get as few things wrong as possible, so we biased the algorithm in favour of false negatives.” That is, the program might fail to identify people based on their microbes, but it will almost never identify the wrong person. Their results reflect our growing understanding of the human microbiome. Our bodies—and our guts, in particular—are colonised by a surprisingly stable set of bacterial strains. Their levels might fluctuate, but the same coterie persists for decades. Perhaps our genes or our immune systems determine who gets to stay. Perhaps there’s a “first-mover advantage”, where the first strains to set up shop then dictate which others get to immigrate. Either way, as Huttenhower says, “Not only are we robots for microbes, but each of us is a robot for a specific set of clones or strains that ride around with us for a long period of time.” He doubts that these results are important for forensic science. “If you deposit your microbes, you’re probably depositing your DNA too and DNA forensics is so well developed,” he says. But he adds that microbiome researchers need to be wary of these issues to protect the privacy of study volunteers. The data from such studies is always anonymised, but if people have unique and consistent signatures, there’s a risk that information from different data sets could be compared in ways that break anonymity. Consider what happened with Netflix. In 2007, the online media company released movie rankings from 500,000 of its customers, so that others could help to improve its recommendation algorithms. Even though the data were anonymised, researchers still managed to identify some of the individuals by comparing their rankings to non-anonymous profiles from IMDB, another movie site. And unlike movie rankings, our microbiome could reveal potentially sensitive information about what we eat, and whether we suffer from health problems. “This isn’t an issue now and it’s not a high-risk issue, but it’s still important for us to consider,” says Huttenhower. “No one study has any danger of releasing private information but due to uniqueness, the ability to link across studies becomes a possibility.” Reference: Franzosa, Huang, Meadow, Gevers, Lemon, Bohannan & Huttenhower. 2015. Identifying personal microbiomes using metagenomic codes. PNAS http://dx.doi.org/10.1073/pnas.1423854112 Lax, Hampton-Marcell, Gibbons, Colares, Smith, Eisen & Gilbert. 2015. Forensic analysis of the microbiome of phones and shoes. http://dx.doi.org/10.1186/s40168-015-0082-9

Microbiome linked to type 1 diabetes: Shift in microbiome species diversity prior to disease onset

 

The human microbiome, which consists of the trillions of microorganisms (bacteria, viruses, and other assorted "bugs") that reside in our bodies, has become an area of growing interest to the medical community as researchers have begun to probe the role it plays in human health and disease. While most bugs in our microbiome are harmless, and even beneficial, changes in the microbiome (and in the interactions microbial species share with their human hosts) have been linked to various disease states, including diabetes and Inflammatory Bowel Disease (IBD). To explore the possible connection between changes in the microbiome and type 1 diabetes, a team led by Ramnik Xavier, an Institute Member of the Broad and Chief of Gastroenterology at MGH, followed 33 infants (out of a much larger cohort of Finnish and Estonian children) who were genetically predisposed to T1D. From birth to age 3, the team regularly analyzed the subjects' stool samples, collecting data on the composition of their gut microbiome. In the handful that developed T1D during this period, the team observed a 25% drop in community diversity (in other words, in the number of distinct species present in the microbiome) one year prior to the onset of the disease. They also noted that this population shift included a decrease in bacteria known to help regulate health in the gut, along with an increase in potentially harmful bacteria that are known to promote inflammation. The findings are further evidence of a previously identified link between inflammation of the gut and type 1 diabetes. "We know from previous human studies that changes in gut bacterial composition correlate with the early development of type 1 diabetes, and that the interactions between bacterial networks may be a contributing factor in why some people at risk for the disease develop type 1 diabetes and others don't," said Jessica Dunne, Director of Discovery Research at JDRF, which funded the study. "This is the first study to show how specific changes in the microbiome are affecting the progression to symptomatic T1D." Previous studies have shown that transferring microbiota from mice that were predisposed to autoimmune diabetes (the mouse equivalent of T1D) to mice that were not predisposed increased the prevalence of autoimmune diabetes in mice that were otherwise unlikely to develop the disease. Studies in humans have also shown an association between T1D and the bacterial composition of the gut. However, those studies were retrospective, meaning they were conducted after the patients developed the disease, making causality difficult to prove. "This study is unique because we have taken a cohort of children at high risk of developing type 1 diabetes and then followed what changes in the microbiome tip the balance toward progression to the disease," Xavier said. Aleksandar Kostic, a postdoctoral fellow in Xavier's lab and first author of the study, agreed, calling the study "a compelling piece of evidence pointing toward a direct role of the microbiome in type 1 diabetes." Since the study also followed infants who did not ultimately develop type 1 diabetes, the researchers were also able to gain insights into the normal development of the microbiome during infancy. They found that, while the species of bacteria present in the gut microbiome vary greatly between individuals, the composition of the microbiome is generally stable within the individual over time. Moreover, using metabolomic analysis (looking at the metabolites -- the tiny molecules produced during metabolism -- in subject stool samples), the researchers were also able to see that, while bacterial species varied between individuals, the biological functions served by the various species in the microbiome remained consistent over time, and from person to person. "Whether the bacterial community is very small, as it is in early infancy, or if it's larger as it is later in life, the community is always serving the same major functions regardless of its composition. No matter which species are present, they encode the same major metabolic pathways, indicating that they're doing the same jobs," Kostic said. By revealing patterns in the development of the microbiome in healthy individuals, and in those progressing toward T1D onset, the findings may ultimately have diagnostic or therapeutic implications. In terms of diagnostics, understanding how the microbiome shifts prior to the onset of disease could ultimately help clinicians spot early microbial features of T1D. As for therapeutics, Xavier, who is also the Kurt Isselbacher Chair in Medicine at Harvard Medical School and Co-Director of the Center for Microbiome Informatics and Therapeutics at MIT, says that knowing which species are absent and which are flourishing in the gastrointestinal tract of children with T1D may help make it possible to slow progression of the disease after onset by revealing ways to manipulate the microbiome and, in turn, microbiome-induced immunoregulation. The next step, he says, is to broaden the sample pool to determine what factors in the environment and in the microbiome might be making Finns -- who are at exceptionally high risk of T1D -- more predisposed to the disease than other populations. That includes revisiting the hygiene hypothesis, which holds that a lack of childhood exposure to microbiota and other potentially infectious agents may hinder the development of the immune system and increase susceptibility to immunological disorders. The researchers are also examining the metagenomic data gathered in the study to determine what biological pathways the microbiota are acting upon -- or what metabolites they may be producing -- that could be contributing to disease. The study was funded by JDRF and supported by the European Union Seventh Framework Programme and The Academy of Finland Centre of Excellence in Molecular Systems Immunology and Physiology Research. Other researchers who worked on the study include: Dirk Gevers, Heli Siljander, Tommi Vatanen, Tuulia Hyötyläinen, Anu-Maaria Hämäläinen, Aleksandr Peet, Vallo Tillmann, Päivi Pöhö, Ismo Mattila, Harri Lähdesmäki, Eric A. Franzosa, Outi Vaarala, Marcus de Goffau, Hermie Harmsen, Jorma Ilonen, Suvi M. Virtanen, Clary Clish, Matej Orešič, Curtis Huttenhower, and the DIABIMMUNE Study Group under the leadership of Mikael Knip.