Frequently Asked Questions
A complex ecosystem that simultaneously exists as bacteria, viruses, fungi and bacteriophages, which interact with each other and their environment (e.g. air, water, soil, different sites of the human body). The collective microbial genes from this community of microorganisms is referred to as the “microbiome”.
Genes are the basic unit of heredity in biology (i.e. a single gene is a “code”). The central dogma of biology describes the blueprint of genes being DNA (deoxyribose nucleic acid), which is transcribed to an intermediate called RNA (ribose nucleic acid), and is finally translated into protein. Proteins include essential compounds and are required for the structure, function, and regulation of the body’s cells, tissues, and organs. The gut microbiome is composed of millions of various microbial organisms made up of trillions of genes (i.e. numerous codes) that are translated into different proteins. These proteins interact with the human host and ultimately have differing essential roles in human biology.
The gut microbiome contains almost 100-fold more unique microbial genes than the human genome. The significance of this has led to a trend in research to describe the gut microbiota as a whole human “organ”. The gut microbiome composition is unique to an individual, established in early life and – due to their interaction with the host – plays a role in disease susceptibility throughout life.
The early colonization of the gut to form a “core” microbiome profile is influenced by several factors including genetics, the mode of delivery, diet, gestational age, environment and antibiotic administration. These factors influence the functioning of the gut microbiome, especially bacteria and its role in several protective mechanisms against harmful pathogens as a process for maintaining control over the resident microbes. As well as various functions involved in nutrition, modulating host immune responses, maintaining health and metabolic homeostasis.
Research has shown that a more diverse gut microbiome is associated with healthy or improved health outcomes. In contrast, the loss of diversity is associated with the susceptibility or the onset of specific disease, dependent on the microbial species affected by the decrease in abundance. The environment has arguably the most significant impact on the gut microbiome and drives the overall diversity profile. Environmental impacts include things humans are exposed to, such as what they eat, how physically active they are, or how long they are exposed to car fumes in traffic etc. These factors all contribute to an individual’s unique microbiome profile.
Large sets of microbial sequencing data will be generated from the samples collected, along with a vast amount of anthropological and environmental data. The big data generated will be used to characterize what the baseline microbiome profile looks like, and how it is affected by differences in the information collected about the individual’s lifestyle and environment. Ultimately, statistical models will be applied to identify associated features between the collected datasets and be used to train an artificial neural network. This will serve as the basis of a predictive model for disease risk linked to particular lifestyle practices or exposure to harmful environmental pollutants by using the microbiome as the input layer. The role of this data collection will subsequently assist in the development of the platform.
Environmental modelling will be undertaken by the CSIR Air Quality group at Smart Places. Geolocation data supplied for “work” and “home” will be utilized to associate a participant’s profile (through postal codes provided) with specific water quality, air quality and meteorological data collected. This group will contribute to the project by providing climate models, which will be used to generate Air quality (AQ) metrics. Importantly, AQ measurements of ambient air pollutants known to modulate the human microbiome, such as particulate matter, ozone, sulphur dioxide, nitric oxide and nitric dioxide will be collected. Accompanying this will be meteorological measurements such as ambient temperature, rainfall, wind speed and wind direction, which are all factors that can affect the distribution of these air pollutants.
Machine learning and AI development will enable the application of mathematical modelling to real-world applications including health based AI development. Since the project will produce large datasets, it is important to be able to pry out what information is relevant in terms of the microbiome and health, and collaboration with IBM will bring about a multidisciplinary approach in making sense of these datasets and the development of the platform.
The development of a precision medicine based platform with an early detection strategy has the enormous potential to revolutionise healthcare in South Africa. This would shift the emphasis in medicine from reaction to prevention, predict susceptibility to disease and improve disease detection. It would enable the customization of disease-prevention strategies to a region or an individual, depending on the resources available. The ideal of pre-empting disease progression could be realized, with the prescription of more effective drugs whilst avoiding prescribing drugs with predictable side effects. This would inevitably reduce the time, cost, and failure rate of treatment regimens by eliminating the trial-and-error inefficiencies that increase health care costs and undermine patient care.
We will be rolling out a recruitment drive by creating online awareness for the project through collaboration with the CSIR communications team. This will involve written information about the CMMI and visual recruitment presentations. Individuals above 18 years old of all genders and ethnic groups employed by the CSIR will be invited to join. Interested individuals will be invited to sign up via email and provide informed consent through an electronic database, and will then be redirected fill out and submit an anthropological survey (available in English, isiZulu and Afrikaans). This survey will serve to explain why a microbiome profile is unique to the participant. They will then be provided with a sample collection kit from the Knowledge Commons building for an easy collection of stool at a single time point in the privacy of their homes. These kits come with an instruction manual and a link to online support. These samples will be anonymised by assigning an identifier then processed. Microbial DNA will be extracted and sequenced, which will tell us all the different types of bacteria present within the individuals gut and at what ratios. This sequencing data will be analysed in conjunction with the anthropological and environmental data, and associations will be identified to assist in explaining what drives the changes in the gut microbiome.
The conclusions that individuals are more susceptible to certain diseases and respond differently to treatment depending on their environment is accurate. A study found that within six to nine months, immigrants to the United States from Thailand experienced a striking westernization of their gut microbiome accompanied by increased risk of obesity, attributed in part to adopting a US diet. Their relocation lead to a myriad of short-term gut microbiome responses, including disruption to the gut microbiome immediately after arrival, expansion of opportunistic pathogens, gut disruption several months after arrival, and stability of microbiome diversity. Genetically unrelated individuals residing in close proximity (i.e. in the same household) are more likely to exhibit similar microbiome profiles than genetically related individuals residing in different locations (i.e. in different households and as far as different continents), highlighting that microbiome diversity has very little to do with ethnicity.
Research has shown that the gut microbiome is established and seeded in utero, and the subsequent mode of delivery and early infant feeding practices continue the diversification of the microbial profile. As the infant diet is changed to more solid foods and environmental exposures increase, the dynamic nature of the diversifying gut microbiome becomes more stable, and a “core” microbiome is formed after approximately three years of life. This core gut microbiome profile generally remains stable throughout life, however it also features a variable profile, which can be affected and changed by acute environmental exposures such as a temporary change in diet or location. This variable gut microbiome profile can see an increase/decrease in microbial diversity, but the core microbiome remains constant. However, a long term change in these factors (e.g. adopting a vegetarian diet) can cause a more drastic change in the variable and the core microbiome, which can have subsequent effects on overall health over time. The use of antibiotics also causes drastic changes in the gut microbiome by essentially causing a reset of the profile, which can then be stably reformed into the profile the individual previously had if their lifestyle remains consistent.
South Africa is composed of a variety of individuals of culturally diverse and demographic groups, each with lifestyles, diets and social practices that would inevitably influence their gut microbial profiles. In 2019 South Africa was named the world’s unhealthiest country according to the Indigo Wellness Index, which tracks several criteria including blood glucose, obesity, depression and exercise. This may reflect the epidemiological transition to a more urbanized society which has major implications in the development of various pathologies such as diabetes, cardiovascular disease and cancer, due to simultaneous increases in sedentary lifestyles and changes in dietary habits. Microbiome variations and perturbations (i.e. dysbiosis) have been shown to influence therapeutic outcomes. A study on cancer treatment using cyclophosphamide – one of the most prescribed medications at public hospitals in South Africa which is used as a chemotherapy and to suppress the immune system – has shown that its efficacy is significantly dependent on the individuals gut health. The susceptibility to infectious disease largely affecting SA such as HIV and TB is also impacted by gut microbiome profiles and health. Further investigation would aid in understanding how these changes in healthy gut microbiome profiles in the SA population affects health and reveal future significant implications in personalized medicine.
A digital platform would serve as a novel health metric that would assist in the work towards the reduction and eradication of the rise of non-communicable diseases. This platform would answer questions such as those pertaining to the general health of the South African population, and ideally be used as an early warning system for the onset of disease. Due to the dynamic and malleable nature of the microbiome, it can respond early to the potential susceptibility to disease as opposed to late outcomes of diagnosis. Therefore, this platform would be used as an early intervention system to prevent disease before it becomes too serious.
The CSIR Microbiome Mapping Initiative (CMMI) is essentially a pilot project that has been set up within the Next Generation Health Cluster. The endpoint aim of this project is to set up the infrastructure and technical information necessary for establishing a national microbiome profiling platform. This project will involve capturing a snapshot of the microbial diversity to enable us to understand what the baseline profile looks like in the average South African community at the CSIR. We also aim to seek out how this baseline relates to various different factors previously mentioned e.g. diet, environment and lifestyle practices, and how this compares to international studies (Human Microbiome Project, American Gut Project). The information from the CMMI would set up the foundation for the generation of this knowledge and a digital platform.
In order to be in line with the international standards of microbiome research, we will collect stool as a proxy for the human gut microbiome. Faecal collection is a convenient method to examine the gut microbiome because it is relatively non-invasive and ensures easy rapid collection by the participants at home and preservation of faecal sample microbial profiles.
Once the study analyses is concluded, participants will receive a report detailing their microbiome composition and how their sample relates to other individuals on the CSIR campus e.g. an individual with a vegetarian diet will see where their sample composition lies in comparison to an individual that consumes meat.
The data from this project is relevant to the respiratory virus infection because perturbations in the gut microbiota relate to the lung-gut axis. Although, corona virus primarily causes lung infection through binding of ACE2 receptors present on the alveolar epithelial cells, it was recently reported that coronavirus RNA was found in the stool of infected patients. The intestinal epithelial cells, particularly the enterocytes of the small intestine, also express ACE2 receptors and thus the gut microbiota plays a role in influencing lung diseases and a normal microbiome profile may be altered. Numerous individuals diagnosed with COVID-19 have also been shown to experience gastrointestinal issues related to the interaction of this virus with the ACE2 receptors in the gut. Exposure to COVID-19 and diagnosis will be addressed in the study, and this may enable an additional investigation of COVID-19 severity of susceptibility and vaccine treatment response.