Are uBiome’s Tests Reproducible? In a Word: Yes!

In our previous blog post –  which was also posted on Medium – we wrote about the use of 16S rRNA gene (“16S”) amplification and sequencing for the analysis of microbial communities, such as those found in our gut. One of the topics we wrote about was the reproducibility of 16S analysis. Reproducibility is how similar the outcome of a test is if you perform the same test multiple times. In order to consider a result reproducible,  you should be able to process the same sample multiple times, while maintaining consistent results.

We also recently wrote a scientific manuscript about the reproducibility of our sample collection and lab processes, which was posted as a preprint on bioRxiv. In this paper, which is ready for scientific peer review, we investigated how reproducible microbiome profiles generated in our laboratory are.

Here at uBiome, we obviously want our analysis to be as reproducible as possible, and we take many precautions to ensure this is the case. All our customers get the same sampling instructions and tubes with the same buffer to make sure that all samples are treated in the same way. In our laboratory, we process thousands of samples with the same protocol. Our laboratory staff works according to Standard Operating Procedures (SOPs), strict protocols they have to follow, and we have robotic liquid handlers and software that ensure that every sample gets the same treatment. Our lab is also CLIA-licensed and CAP-accredited, so all of our laboratory processes have been reviewed by rigorous external audits.

Still, we wanted to make sure that all these measures had the intended effect of reproducibility. In the manuscript we posted on bioRxiv, we wanted to address some very specific questions that we (and our customers) might have about how our sampling and laboratory processes affect reproducibility. To answer these questions, we did four experiments. We looked at how similar the profiles are of samples taken on adjacent days, how similar the profiles are of samples taken from different pieces of the same toilet paper, and what happens if you analyze the same sample three – or even three hundred – times.

Let’s take a look at the four questions we tried to answer in this paper:

Question 1.

Does it matter on which day I take a stool sample? I did not make any big changes in my diet lately, but I eat something different every day. Does my microbiome vary a lot from one day to another? Is there a best day to sample myself?

Experiment: To address this question, a volunteer literally pooped for science! “Volunteer A”, a healthy man in his 30s, took stool samples over a period of 20 days. Although he did not obtain a sample every day, he sampled his stool on 11 days within this 3-week period. As he was doing this, he followed his regular diet, with normal variation from day to day. All samples from this volunteer were extracted and analyzed in our laboratory.

Conclusion: All samples from volunteer A looked similar to each other (Figure 1A). It did not matter on which day he sampled or that there were small variations in his daily diet; his microbiome shows little variation from day to day. Using a common measure of similarity, the Lin’s correlation, we found an average correlation of 0.68 between samples from different days. However, when we compared volunteer A’s stool samples to that of 8 other subjects, each person had their own unique microbiome pattern (Figure 1B).

On average, the Lin’s correlation between samples from different subjects is only 0.28. This means that samples from volunteer A always looked much more similar to other samples of the same volunteer, than to samples from another person, even if taken on different days. So the answer to the question above is no, your microbiome does not very a lot from day to day.

From this experiment we concluded that there is little variation in a person’s microbiome, as long as large dietary changes aren’t made. Other studies, however, have shown that your microbiome will change if you make large dietary changes, if there are changes in your health or during international travel. So if you are struggling with your health and are taking action to change that by taking supplements or changing your diet, it would be beneficial to do multiple tests to see how your microbiome will change.

Figure 1: To answer questions 1 and 2, subject “A” sampled his stool on 11 days within a 20-day period. On each of these 11 days, he took 2 pieces from the same toilet paper. The microbiome profiles of all 22 samples looked very similar to each other (A, left). Samples from 8 other subjects (2 replicates per subject) looked all very different than those from subject A (A, right). The plot on the right (B) shows in a different way that all 22 samples from subject A (shown in pink) were very similar to each other, but very different from those of the 8 other subjects.

Question 2.

The uBiome Gut Explorer and SmartGut  kits require me to sample from toilet paper. Does it matter which fecal piece I get from that toilet paper? If I would take 2 samples from the same piece of toilet paper and send them in for a uBiome test, would the microbiome profiles of these 2 samples look the same?

Experiment: To answer this question, we asked volunteer A from experiment 1 above to not only sample his stool for 20 days, but to also take duplicate samples. On each day he sampled his stool, he took 2 different pieces of fecal material from the same toilet paper.

Conclusion: The results showed that these 2 duplicate toilet paper samples looked very similar to each other (Figure 1A). Using that same Lin’s correlation that we used to answer the previous question, we found that duplicate toilet paper samples had an average Lin’s correlation of 0.95, which is very high. In other words, samples from the same piece of toilet paper are almost identical, and significantly more similar than samples that this volunteer took on other days. So the answer is yes, two samples taken from the same toilet paper look almost the same.

Question 3. How stable is my sample after I took it and swirled it in the tube with the lysis buffer? Can I really ship it at room temperature? Will some bacteria start to grow? Will my microbiome profile change during the shipping process?

Experiment: We tested if microbiome profiles would change after keeping our samples at different temperatures for a week. We extracted samples immediately and also after keeping them in a freezer, at room temperature, or at higher temperatures (86 or 104 degrees F) for a week.

Conclusion: After processing, these samples looked very similar to each other (Figure 2). So the answer is: yes, your microbiome profile will remain stable, regardless of shipping temperature. Our sampling buffer, the liquid in the tube that you swirl your sample in, will immediately lyse (kill) all microbes, ensuring that your results reflect your microbiome exactly how it was when you sampled it.

Figure 2: Stool samples from 8 different persons were immediately extracted or extracted after storage for a week at different temperatures (freezer, room temperature, 87F or 104F; all in duplicate). Panel A on the left shows that all 10 samples from the same person had nearly identical microbiome profiles, no matter what temperature they were stored at. On the other hand, samples from each individual were very different from one another. Panel B on the right shows the same data in a different way, and confirms that samples cluster per subject, with no apparent effect of temperature treatment.

Question 4. How reproducible is the uBiome process? If you process the same sample multiple times, how similar are those microbiome profiles going to look? What would happen if you process the same sample, say, three times? Do you get the same results, or do these three replicates look very different every time you process them?

Experiment: We extracted the DNA from 44 stool samples, all derived from different people. We then performed the same microbiome analysis test three times, using different reagents and equipment and performed by different technicians in the laboratory.

Conclusion: All three replicate samples from the same person looked very similar to each other, independent of reagents or equipment used, and technician performing the assay in the laboratory. Of the 44 samples, the 3 replicates clustered tightly together in 39 cases. We could also clearly tell these samples apart, as every person has their own unique microbiome.

Figure 3: Extracted DNA from 44 stool samples, all from different people, were used to generate microbiome profiles, on three independent times. While samples from each individual were very different from one another, the three replicates looked very similar to each other.

Question 5. Sure, but what would happen if you processed the same sample hundreds of times? Would the results still all look the same?

Experiment: After testing each sample 3 times, we wanted to know what would happen if you tested the same sample hundreds of times. We took one complete poop sample (the whole sausage!), mixed it in a blender with buffer, divided that into smaller portions, and stored these in the freezer. From there, we prepared 363 even smaller portions, each of which was processed independently. The runs were done by different laboratory personnel and on different machines in our laboratory. Then, we compared all the 363 microbiome profiles.

Conclusion: The result? They still looked very similar to each other, even when processed over 300 times (Figure 4). In our paper, we also show that which technician or machine the run was performed with introduced very little variance.  

Figure 4. The top part of the figure shows the 363 replicates generated from the same homogenized stool (HS) sample – these look all very similar. The bottom part shows the microbial genera in samples from 400 other persons – these all look very different from each other.


In summary, our study shows that several aspects of microbiome analysis are reproducible. In a healthy person, there is little day-to-day variation of the microbes found in stool, and it does not matter which piece you take from toilet paper. In addition samples stored in our tubes have been experimentally verified at a wide range of temperatures for at least a week, and extracting the same sample over and over again, will give very similar results.

questions you shouldn't be afraid to ask your gynecologist

Ten Questions You Might Be Afraid to Ask Your Gynecologist (But Shouldn’t Be)

There’s nothing like a trip to the gynecologist to make you feel glamorous, right? There’s the expertly tailored paper gown and the equally fashionable paper throw to drape over our knees. And who needs high heels when we can slip our dainty feet into cold, metal stirrups?

Okay, so maybe the thought of visiting the gynecologist ranks somewhere between getting a root canal and being audited by the IRS, but it’s an important part of your overall health. Anyone who’s had a yeast infection can attest to the importance of keeping one’s vagina healthy, but there’s much more to women’s health than care for down there.

In honor of National Women’s Health Week, we reached out to Dina Bastawros, M.D., Female Pelvic Medicine and Reconstructive Surgery Fellow at Carolinas Medical Center in Charlotte, North Carolina, with ten questions we shouldn’t be afraid to ask our gynecologists. So wear those paper gowns proudly, and go to your next appointment armed with the bravery to broach burning questions such as: Continue reading “Ten Questions You Might Be Afraid to Ask Your Gynecologist (But Shouldn’t Be)”


Meet Lactobacillus: The Vagina’s Beneficial Bacteria

From yeast infections to STIs, there’s a lot of info out there about how certain microbes can hurt our vaginal health. Growing up, some of us were taught that vaginas are inherently “dirty” and that we need to “clean” our vaginas with harsh soaps or douches.

But the truth is just the opposite! Rather than harsh vaginal washes or flower-scented tampons—which can actually cause far more harm than good—we get protection against infection from the millions of bacteria that make up our vaginal microbiomes. That’s right: bacteria are one of the keys to vaginal health. Continue reading “Meet Lactobacillus: The Vagina’s Beneficial Bacteria”

Mothers' Day

You got it from your momma. Your eyes, your nose… and your microbes.

On this special day meant for celebrating the mother in your life, there are countless things you can thank her for. On a biological level, however, there might be more to thank her for than you think! While she obviously passed her genes to you and gave you life, she also passed on diverse bacteria that contribute to your health. Continue reading “You got it from your momma. Your eyes, your nose… and your microbes.”


What to expect (from your vaginal microbiome) when you’re expecting

There’s one gift your mother has given you that may stay with you your whole life: the millions of microorganisms she passed to you during birth and through her breastmilk, your microbiome. While your own unique microbiome begins developing during your first year, this inherited microbiome plays a huge role in protecting you from disease during this vital period.

But what about the other side of coin? A pregnant mother’s vaginal microbiome doesn’t just affect her unborn child—it also affects her own health. Research has found that the vaginal microbiome changes during pregnancy and the postpartum period. These changes can have a huge effect on pregnancy outcomes, with some kinds of bacteria leading to increased risk of preterm delivery. Continue reading “What to expect (from your vaginal microbiome) when you’re expecting”

Scientific Facts About 16S rRNA Gene Sequencing

As the leader in microbial genomics, we know a lot about microbiome sequencing. We use a range of different sequencing approaches, including 16S rRNA gene sequencing, full metagenomics, and our patented precision sequencing™.

One of our earliest advisors was Dr. Joe DeRisi, Professor at UCSF, MacArthur Genius award winner, sequencing pioneer, and inventor of numerous sequencing techniques. uBiome has filed patents on over 15 new sequencing methods, including precision sequencing™, CRISPR-based library preparation, combinations of RNA and DNA, as well as optimizing current methods for the microbiome.

We have a team of over 60 scientists working with molecular as well as computational techniques for understanding the human microbiome. And each month, we generate terabytes of sequencing data. Our dataset, which is over 250,000 samples and projected to be over 1 million by the end of next year, is the largest human microbiome dataset in the world.

Even though 16S sequencing is just part of what we do, it is an important tool in the toolbox of anyone trying to understand the microbiome. It is one of the best techniques for high-throughput analysis of thousands of samples. The 16S gene is present in every bacterium and archaeon. Because so many labs all over the world have been and are using this approach, 16S sequence databases are unparalleled in size. So almost every 16S sequence read can tell you which bacteria and archaea are present in a sample.

There was a recent interesting discussion on Medium and Twitter about the usefulness of 16S sequencing. Eran Segal and Jonathan Eisen, two scientists and pioneers in the microbiome research world, both agreed that 16S sequencing is a great approach for microbial community analysis.



We wanted to take a closer look at some of these recent claims made about 16S sequencing and see if we could help shed some light. What is true about 16S sequencing, and what is just “fake news”?

Fake News:

“16S sequencing is useless. It is a complete waste of your money.”


Since the birth of microbiome research, the 16S rRNA gene (“16S”) has been recognized as a powerful tool with which to classify microorganisms. 16S is a gene that is present in all bacteria and archaea (another type of microorganism). 16S sequencing can be used to identify these microorganisms and determine how many of them are present in a biological sample, such as your gut.

16S sequencing was the technique of choice for the National Institutes of Health’s Human Microbiome Project, in addition to thousands of laboratories worldwide. Each year, hundreds of scientific studies based on the 16S gene are published. Focusing on the same gene has allowed researchers all over the world to compare results with each other and build databases that contain millions of 16S sequences. The Ribosomal Database Project, for example, has over 3 million different 16S rRNA sequences, and the SILVA Database has over 2 million.

These extensive databases are an advantage of using 16S instead of whole genome DNA or transcriptomic (RNA) sequencing. The number of bacterial and archaeal genomes that have been sequenced to (near) completion is much smaller; NCBI’s Genome Database contains only 135,000 different genomes so far. Other widely utilized databases, such as KEGG, only contain information for around 5,300 organisms.

Simply put: if you use 16S sequencing, there is a large chance that your sequence will be present in the 16S database, making it easy to identify to which bacteria or archaea the gene belongs. If you use metagenomic or metatranscriptomic analysis, on the other hand, your chance of finding a sequence in the genomic databases is much smaller and could simply be reported as an “unknown gene from an unknown bacteria”. Not so useful.

At uBiome, we have developed our own curated 16S database from our dataset of human microbiomes, which is the largest in the world. For our products, we use a version of this 16S database that we use to report genus or species-level taxa. In addition, our team of bioinformaticians and engineers have developed automated pipelines in which every read is compared to this database.


Fake News:

“16S can only identify bacteria.”


This is misleading, at best; over 99% of the genes in our gut are bacterial, so focusing on bacteria is not a bad thing. Moreover, the method we use at uBiome to amplify and sequence the 16S gene can identify both bacteria and archaea, a group of microorganisms discovered in 1977 by Carl Woese using – you guessed it! – 16S rRNA gene sequencing. So whoever said this may not have heard of archaea, which also happens to be the third domain of life. It is true that fungi and yeasts cannot be identified with this method. However, they can be identified with some of the other methods we use in our products — full metagenomic and precision sequencing™.


Fake News:

“16S is just one gene. Metagenomics or metatranscriptomics will identify all living organisms”


Let’s say that your sample contains 1,000 different bacterial species, and each species contains, in general, between 2,000 to 5,000 different genes. That is between two and five million different genes!

Put differently, imagine you have thousands of different puzzles, each with a different design, and all the puzzle pieces are mixed together in one big box. Undoubtedly, there are many fewer corner pieces than center puzzle pieces, and it would be much easier to match 100 corner pieces to the different designs than 100 middle pieces. Similarly, it is much easier to match 10,000 16S reads to the species that they belong to than 10,000 random gene reads. Because 16S analysis focuses on just one gene, all 10,000 or more sequencing reads are of the 16S gene. The extensive databases we mentioned earlier allow us to easily tell which bacteria are present in your sample. It is also very likely that we will be able to find 16S reads from all of these 1,000 species.

With a minimum of 10,000 sequencing reads, each bacterium will be, on average, covered 10 times.

With metagenomic or metatranscriptomic analysis, the same 10,000 sequencing reads will not be enough to cover all 1 million different genes in the sample. Many of these cannot be matched to a known organism because the genomic databases are not large enough. If you want to go really deep into the analysis of your sample, you will need to sequence millions of reads, which will cost you easily 100 times as much as a 16S analysis.

That is why we also developed our patented precision sequencing™ platform, a technique that combines 16S sequencing with enhanced features. We are very excited about this, and we hope to tell you more about that in a future blog.


Partially Fake News:

“In some recent scientific publications, the 16S technology has been shown to produce lots of false results. A peer-reviewed study by Edgar determined that 16S sequencing of known bacterial communities resulted in a 56% to 88% false positive rate of predicted genus names.”


This is partially correct, but it’s not applicable to uBiome data. The study mentioned above (Edgar) was investigating a very specific bioinformatics analysis pipeline (QIIME) and a very specific 16S rRNA gene reference database (Greengenes). One of the problems identified in this study was that, in the Greengenes database, certain genera were placed under multiple families, thus creating unreliable taxonomic lineages.

As we wrote above, at uBiome we use a proprietary bioinformatics pipeline and a different manually curated sequence database that does not have these taxonomic overlaps. We have made sure that there are no genera that fall under different taxonomic lineages. So the problem described above does not apply to our bioinformatics analysis. If we label a 16S sequence with a name, you can rest assured that we got the taxonomy right.


Partially fake news:

“Both 16S and metagenomic methods have another drawback: they analyze DNA, not live microorganisms. DNA is very stable, so even DNA from the food we consume and from dead microorganisms finds its way into stool samples, thus wasting sequencing data and confounding the analyses”


This is partially true. DNA is indeed very stable, but the DNA from the food we eat is already chemically or enzymatically degraded in the stomach and in the intestines. About 99% of the genes in our stool come from bacteria, not from our food, so in metagenomic sequencing hardly any data is wasted at all. In addition, RNA is more unstable than DNA, so the inverse problem could be true for samples for metatranscriptomics: since RNA has a very short life-span, the estimation of microbial activity from metatranscriptomics will always underestimate the actual activity of the microbes from a sample.


Fake News:

“16S sequencing is unreproducible and unreliable. If you sequence the same sample twice, you will get very different results”


This is false.

The source of this claim is likely a post on the website Science News, where the same sample was analyzed by 2 different groups: uBiome and American Gut (a nonprofit university project). uBiome’s sampling method contains a proprietary stabilization buffer, which preserves your sample immediately after sampling. American Gut does not provide a stabilization buffer so some bacteria can keep on growing as the sample gets shipped to the laboratory.

Since these 2 assays use very different shipping conditions and DNA extraction methods, it is not surprising that the same sample sent to 2 different companies can give different results. We responded officially to this in 2014 on the uBiome Blog.

Sequencing of the same sample using uBiome’s technologies is extremely reproducible. In fact, in the graph below you can see that analyzing the same sample 50 times leads to remarkably similar results! (In fact, we are submitting an article for peer-review on this very subject.)

Genus-level uBiome Explorer data of the same stool sample that was extracted, amplified, and sequenced 50 times, gives highly reproducible microbial profile results. Samples were all analyzed in different, independent runs. Source: uBiome.


Fake News:

“16S sequencing will only provide you with genus-level data. On genus level, our microbiomes are 95% identical.”


This simply isn’t true.

Each person has their own unique microbiome. Thanks to our microbiomes, we look as different from each other on the inside as we do on the outside!

Still not convinced? Below you’ll find a graph of genus-level gut microbiome data from 50 different people, analyzed using uBiome’s testing kits. As you can see, we’re all very different!

Genus-level uBiome Explorer data from 50 different stool samples, each from a different person. The plot shows the 50 most abundant genera in this data set. All other genera are grouped together and shown as “Other genera”. Each person’s stool has a unique microbial fingerprint that changes over time. Source: uBiome.


Fake News:

“Genus level is not accurate enough. The resolution is too low. Humans, dogs, and rats all belong to the same genus. At the genus level, we are all mammals – so genus level analysis is useless.”


This is completely wrong! Whoever said this perhaps didn’t pay attention during science class.

Mammals are a class, not a genus. Humans are Homo sapiens – belonging to the genus Homo. Even our closest relative, chimpanzees, belong to a different genus, Pan. Genus level analysis is pretty good in telling all of us mammals apart, and, for bacteria and archaea, genus-level analysis has equally good resolution.

uBiome’s analysis often goes even deeper than genus-level analysis. For example, the probiotics panel on our Explorer product reports to the species level. Our clinical products, SmartGut and SmartJane, use precision sequencing to identify a panel of gut microbes on the species level, with high specificity and sensitivity. SmartGut identifies 13 species and 13 genera, while SmartJane identifies 17 species and 15 genera. The science behind the selection of each of these targets, and the validation of the methods to make sure that we can detect them with high precision is available online, so you can read more about that if you like. For SmartGut, that information has been published in a peer-reviewed scientific paper in PLOS ONE, while a preprint of the development of the SmartJane assay is available as well.

Two of our current products offer species-level precision sequencing, but even the resolution of our Explorer product, where genus level is used, is high enough to distinguish all of us from each other.

Figure: Scheme showing classification on different taxonomic levels. All living organisms, from mammals, to plants, to bacteria, are classified using this scheme. For example, at the Class level all mammals are grouped together. Foxes, wolves, and coyotes belong to the same family-level group, but each belong to a different genus. Genus-level analysis can clearly tell humans, dogs, and rats apart. Source: Wikimedia Commons (Author: Annina Breen).


A chimpanzee and a human – genus level analysis can clearly tell them apart. Source: Wikimedia Commons; author: “user:snowyowls”.



Further reading:

microbiome space bacteria

May the Fourth Be With You… and With Your Microbiome

May 4th has long been an unofficial Star Wars holiday, thanks to a somewhat silly pun. (“May the fourth be with you!”) This year, fans have even more reason to celebrate: the newest movie in the franchise, Solo, comes out in just a few weeks.

Solo traces the origin story of space smuggler Han Solo, whose love of blasters and Princess Leia was made famous by the original trilogy. Other theater-goers may be transfixed by the film’s dramatic space battles and depictions of exotic alien species. For us, however, watching the Millennium Falcon hyperjump across the big screen will bring only one question to mind: how would all of this interplanetary space travel affect human gut flora?  Continue reading “May the Fourth Be With You… and With Your Microbiome”

Crohn's disease

What is Crohn’s Disease?

Extreme fatigue all day, stabbing abdominal pain, cramping, and constant diarrhea. You may wince at the thought of these symptoms, especially in conjunction with one another, but that is the daily reality of the many experiencing a flare up of Crohn’s disease.

Crohn’s disease, a chronic inflammation of the gastrointestinal tract, is a type of inflammatory bowel disease (IBD)—a category of autoimmune diseases that also includes ulcerative colitis. In cases of IBD, the immune system incorrectly mistakes beneficial gut bacteria for dangerous bacteria. Continue reading “What is Crohn’s Disease?”

nature vs nurture

Nature? Nurture? Or something completely random?

In 1995, the European Journal of Physics published a paper apparently proving that when a slice of buttered toast falls from table height, it will land butter-side down 62% of the time.

We humans love good, solid, logical explanations, and in this case the researchers explained that when toast falls from a table, it only has time to perform half a somersault during its fall to the floor.

And since it starts butter-side up, it’s more likely to end up the other way round at the conclusion of this brief journey. Continue reading “Nature? Nurture? Or something completely random?”


Mycoplasma genitalium – the common STI you’ve never heard of

Mycoplasma genitalium – the common STI you’ve never heard of

Mycoplasma genitalium: it’s the sexually transmitted infection (STI)  you’ve never heard of. Even though Mycoplasma genitalium is more common than the bacterium that causes gonorrhea in young adults aged 18-27, it’s not always part of standard STI screenings. So what the heck is Mycoplasma genitalium? And should you be worrying about it?

Mycoplasma genitalium has flown under the radar in part because it’s relatively hard to detect. Just like other STIs, people who are infected may not have any  symptoms, and if they do, their physicians may not always test for Mycoplasma genitalium–partly because it’s difficult to test for using traditional methods. However, thanks to increasingly accessible DNA-based STI screening—and increasing awareness—doctors are now more able than ever to diagnose and treat a Mycoplasma genitalium infection.


What the heck is Mycoplasma genitalium anyway ?

Mycoplasma genitalium is a bacterium that infects both male and female genitalia and is passed through sexual intercourse and genital contact. While you may not have heard of Mycoplasma genitalium, that’s not because it’s particularly rare: researchers have found that an estimated 1.3% of adults in developed countries ages 16-44 are infected.

Mycoplasma genitalium is responsible for 20-35% of cases of male urethritis (inflammation of the urethra) not caused by chlamydia or gonorrhea. In women, it is also associated with cervicitis (inflammation of the cervix), pelvic inflammatory disease (PID), and even infertility.


How do I know if I have Mycoplasma genitalium ?

Mycoplasma genitalium was first identified as a sexually transmitted infection in the 1980s. Why, then, do so many articles from the past few years call it a “new” or “emerging” STI?

It partly has to do with the nature of the bacterium itself. Mycoplasma genitalium is often symptomless or has symptoms that can be caused by several other infections. In one 2015 study, for example, over 94.4% of men and 56.7% of women who tested positive for Mycoplasma genitalium had not experienced any symptoms in the previous month. If symptoms do appear, men may experience penile discharge and irritation while urinating, while women may experience unusual vaginal discharge, painful sex, and spotting. These are similar to the symptoms of gonorrhea and chlamydia, so it can be tricky to identify Mycoplasma genitalium. Because of this, Mycoplasma genitalium was rarely discussed… simply because few people realized they had it.

Until recently, Mycoplasma genitalium has also been hard to test for. It’s a slow-growing organism, so traditional testing methods (which require isolating and culturing bacteria from a sample) don’t work for Mycoplasma genitalium. Instead, doctors rely on nucleic acid amplification testing (NAAT), which detects the bacterium’s DNA—and that process is often still possible only at big research labs.

That’s why uBiome’s sequencing-based SmartJane test can detect the presence of Mycoplasma genitalium where traditional STI screening might not, and makes testing easier and more accessible to boot. Your doctor can catch a potential Mycoplasma genitalium infection in a preventative SmartJane screening or even order a SmartJane test to check out whether any symptoms present could be Mycoplasma genitalium or another STI.

The same advances in genetics which allow researchers to perform NAAT tests have led to other exciting scientific developments. In 2008 Mycoplasma genitalium became the first bacterium to have its complete genome artificially synthesized by scientists, when a team of researchers from the Venter Institute managed to piece together its entire DNA sequence. In its own way, Mycoplasma genitalium has contributed to scientific progress, too.


What about treatment?

Difficulty in diagnosis isn’t the only difficult thing about Mycoplasma genitalium—it can also be tricky to treat.

Since Mycoplasma genitalium has no cell wall, many antibiotics, which target the cell wall, are ineffective. The current go-to treatment, the antibiotic azithromycin, has an 85% cure rate, but researchers have reported a rise in Mycoplasma genitalium’s resistance to azithromycin. Several other drugs are currently being tested, but they’re not on the market yet. If you do have Mycoplasma genitalium, your doctor can find the treatment that works for you.


Don’t panic—be proactive!

A sometimes symptomless, rarely screened for STI which is increasingly resistant to antibiotics? We know, we know: Mycoplasma genitalium doesn’t sound like a walk in the park.

But, as always, when it comes to STIs—and hey, your health in general—worrying won’t protect you. Instead, you can be proactive by following common-sense sexual health practices. As with all STIs, communicating with your partner about sexual health is key. Regular condom use especially during intercourse may help protect you from Mycoplasma genitalium, and regular sexual health checkups can enable you to identify and deal with STIs before they become a problem. The more you know, the more power you have.


April is STI Awareness Month! Talk to your healthcare provider about your vaginal health. uBiome’s SmartJane test identifies HPV, four common STIs including Mycoplasma genitalium, and 23 bacteria that can be vaginal risk factors for bacterial vaginosis and other conditions.

NOTE: SmartJane is not a replacement for Pap smears or well woman visits and does not detect cancer directly.