The second genome

Microbiome-based diagnostic markers

We carry more microbe cells than our own cells! We know that these microbes play a crucial role in our health and well-being. Although one can now obtain genome sequence data corresponding to these microbes using state-of-art sequencing machines, gaining meaningful insights from such complex and voluminous data is challenging.

TCS’ Life Sciences Research team has not only developed efficient algorithms for every step of analysis and management of the data, but has also carried out cutting edge research to understand the link between microbial community (called “microbiome”) and diseases. The team’s innovative microbiome-based solutions can be utilized for not only monitoring health status of an individual, but also for predicting at an early stage his/her risk for a number of asymptomatic diseases and disorders.

Can you believe that microbes resident inside us outnumber not only our own cells, but also contribute to close to billion microbial genes as against about 20,000 human genes!! Thus, apart from our own genome, we have our second genome (also called metagenome) contributed by DNA of all the inhabiting microbial community, collectively called the microbiome. In order to understand whether and how these tiny microbes residing within us influence our health, we need to study their genomes. As most of these microbes cannot be cultured in the laboratory, they cannot be studied using traditional genomics approaches. Thanks to the progress in science and technology and engineering, a new generation of DNA sequencing machines can now sequence the entire DNA of all the microbes that reside in any environment. This field which bypasses the culturing step is called metagenomics.

The field of Metagenomics has advanced rapidly in the last decade. Enormous amounts of DNA data has been/ is being generated and analyzed. However, there are some challenges in analyzing DNA sequencing data obtained from a microbial community:

• The sequencing data is voluminous and noisy

• Analysis requires complex algorithms, given the fact that we have no prior idea about the types and amount of bacteria to look for
• At each step of the analysis, specialized algorithms, visualization tools, and statistical methods are needed to obtain biologically meaningful insights from metagenomic data.

TCS’ Life Sciences R&D team has developed efficient algorithms for not only every step of the analysis, but also for management of metagenomic “BIG data”. These algorithms can be used for analyzing metagenomic data as well as for comparing multiple metagenomic datasets sampled across space and/or time. This is specifically important if one wants to compare datasets corresponding to healthy state and diseases. Our algorithms can be used for not only understanding microbial communities present in our body, but also for obtaining key insights into role of such communities which are present in other environments (soil, water, etc.).

Screening for Risk of Asymptomatic Diseases

When we talk about human health, the first question which comes to our mind is whether we can diagnose diseases at a very early stage so that preventive measures can be taken. A large number of diseases and disorders, like cancers, diabetes, cardiovascular diseases, do not show any symptoms in their early stages. In a healthy individual, there is a fine balance between various microbial groups residing in the body. This balance is lost in diseased individuals. Therefore, “variations” in the bacterial communities residing within us have the ability to serve as “diagnostic biomarkers” that can foretell the presence and/or stage of disease. Taking this as the clue, TCS’ Life Sciences Research team has captured these patterns of imbalances, i.e. “variations” in order to develop microbiome-based diagnostic markers.

Preterm Deliveries

To give an example, take the case of preterm births (PTB). Every year, about 15 million babies are born pre-term¹ . Out of them, more than a million die due to medical complications. Premature birth results in more neonatal deaths than any other disease. Every 30 seconds, a new born child dies. A preterm delivery is difficult to predict and at the moment, there are no diagnostic methods that can accurately raise an early alarm. Therefore, TCS’ microbiome research team looked beyond physical traits as well as biochemical tests and focused on studying the bacterial communities in pregnant women. We studied a lot of publicly available microbiome data from pregnant women and deciphered patterns that have the ability to act as biomarkers for preterm delivery. Unlike existing PTB diagnostic solutions, which are only applicable at later stages of pregnancy, our biomarker works in the first trimester with significantly high accuracy (>95%). Our biomarker relies on metagenomic sequencing and analysis of a single microbiome sample (either a vaginal swab or a saliva/ stool sample) collected from a pregnant woman. The method has been validated using publicly available microbiome data pertaining to pregnant women (on over 1100 clinically collected samples from diverse geographies and ethnicities). Since our microbiome-based diagnostic biomarker can accurately predict the risk of preterm birth as early as in the first trimester of pregnancy, clinicians will have enough time to act and prevent the preterm delivery.

Apart from predicting the risk of preterm delivery, TCS team has successfully developed microbiome-based biomarkers that can be used for accurate screening of colorectal cancer and breast cancer using microbiome sequence data obtained from an individual’s stool sample. The biggest advantage of using our biomarkers is that these are non-invasive (unlike traditional clinical diagnostics/screening methods) as well as low cost. They can also predict early the risk of a number of asymptomatic diseases/disorders. This gives doctors a chance to start timely therapeutic intervention and manage the patient and the disease in a much more effective manner.