Meet a microbiome researcher: Q&A with Dr. Erika Ganda
August 21, 2018
As a part of our Microbiome research interview series, we spoke with Dr. Erika Ganda from the department of Food Science, Cornell University, New York. Erika is a microbiome researcher with a background in veterinary medicine, epidemiology, microbiology, dairy extension and business. Her research interests focus on the application of innovative technologies to investigate animal health and food safety and the development of practices and approaches that can be applied to the agricultural industry. Erika is currently working on a project that uses Next Generation Sequencing and artificial intelligence to monitor dairy products throughout the processing chain for safety and quality. Erika has a degree in Veterinary Medicine from the Federal University of Goias in Brazil, and a Ph.D. in Animal Science with concentrations in Epidemiology and Microbiology from Cornell University. Erika is part of the Cornell Milk Quality Improvement Program and Food Safety Laboratory since May of 2017. We interviewed Erika to discuss her research, a typical day in the lab and her hobbies.
How did you first get interested in science and microbiome research?
Since I can remember I have been passionate about animals, particularly cows. This is funny, because none of my immediate family had any agricultural background. During high school I really enjoyed the biology courses and, taking my love for animals into account, the decision to pursue veterinary school was an easy one to make. I worked a lot with dairy extension throughout vet school in Brazil, helping dairy farmers improve their milk quality and herd health. Because I was interested in learning more about large dairy production systems, I went to the University of Florida as a visiting student during my last semester of vet school. There, I not only saw a 5,000-cow dairy for the first time, but also was introduced to research and first heard about the microbiome. This path led me to my Ph.D. studies at Cornell University, where I used next-generation sequencing to understand the microbial dynamics of bovine mastitis, a disease that affects 25% of US dairy cows each year and costs about 2 billion dollars to the US Agricultural industry. After I earned my Ph.D., I immediately moved on to a postdoc at the department of Food Science, where I am leveraging my expertise in the milk microbiome and using next generation sequencing and artificial intelligence to create an anomaly detection algorithm for milk samples.
Can you give a summary of your project?
Throughout my Ph.D. I investigated the bovine milk microbiome upon natural or experimental infection with Gram-negative pathogens, and the effect of treatment with third generation cephalosporins on healthy and mastitic milk microbiomes.
Currently, I am a postdoctoral associate in Dr. Martin Wiedmann’s lab at the Cornell University Department of Food Science, where I am working to innovate food safety management in partnership with the companies Mars and IBM.
This project takes a multidisciplinary perspective and aims to use artificial intelligence and modern molecular biology approaches (data mining techniques, metagenomics and meta-transcriptomics) to provide rapid and untargeted screening to assure the quality and safety of food products. We use milk as a model system, however the findings will be easily transferable to other food products and food systems (Cornel and IBM).
Are you working on any other new projects in the field of microbiome research? If so can you tell us a little about these?
In addition to my postdoctoral appointment, I have maintained collaborations with researchers I connected with during my Ph.D. As a result, I work with different investigators analyzing data on the microbiome of bovine rumen, companion animals’ mouth during periodontal disease, milk, salmon trout skin, and murine feces. In all these different species we investigate the microbiome in healthy and diseased states.
What will be a typical day for you in the lab?
I don’t believe there is such a thing as a typical day in the life of a scientist! It all depends on the stage of the project, and what is going on at the moment. I might spend the whole day extracting DNA, and a week later I will be dabbling in statistical analysis. This, of course, after hours reading the literature and designing all the experiments. In the end you get to sit down and have fun analyzing your data and reporting your findings!
What do you find most interesting about your project? What is the most interesting or surprising result you have found?
The most interesting point in my Ph.D. was that I was able to demonstrate that the milk microbiome is resilient and that it can return to a healthy state fairly quickly after a case of bovine mastitis caused by gram negative bacteria.
As part of my postdoc, I am really interested in applying artificial intelligence and machine learning techniques to the milk microbiome. It is exciting to explore the potential of microbiome-based anomaly detection for use in food safety and quality.
What kind of microbiome research do you perform and how does it impact health and disease? Where do you see this heading in the next five years?
Moving forward, I am interested in developing practical ways to modulate the microbiome to improve food animals’ production efficiency. We see a lot of associations between the microbiome, health, and productivity. It is imperative to improve the understanding of such mechanisms leading to positive outcomes, so we can then use that knowledge in our favor. I foresee my future projects spanning from food safety testing to microbial profiling and targeted treatment/nutrition of livestock, all the way to microbiome modulating approaches to impact animal health and productivity.
What are your hobbies?
I like to read while I have my morning coffee (usually a book about the microbiome, data analysis, or science in general). Additionally, I really love animals and water. Whenever I have the chance I try to be around cows, dogs, or a lake! So, I like paddle boarding, windsurfing, going on hikes with dogs, and just hanging out with cows and calves. I also love to travel, getting know new places and trying new foods.
What are the major challenges you face in your research with regards to sample collection, nucleic acid isolation and data analysis?
Milk is a really difficult sample to extract nucleic acids from! It has really low bacterial biomass and is loaded with DNA extraction and PCR inhibitors such as fats and proteins. Milk not only is really difficult to get DNA out of, but 99.99% of the DNA present in milk is bovine DNA. This is a particular challenge when you want to use untargeted sequencing to investigate the microbial content, making the studies quite expensive. This issue gave rise to another project I am carrying out during my postdoc in which we are evaluating several nucleic acid extraction techniques and host-DNA depletion methods for use with bovine milk.
In terms of data analysis, microbiome research is a rapidly evolving field. It is important to keep up to date with the most appropriate analysis methods, as there is still a lot of debate in terms of what the most appropriate data handling and analysis techniques are. We are gathering more data at a faster speed than ever before, and that comes with its inherent challenges. I believe that machine learning and artificial intelligence are going to be of great importance for microbiome research in the near future.
Which MO BIO or QIAGEN products do you use/have you used in the past and what did you like about the products?
Throughout my Ph.D. I performed over 3,000 DNA extractions with DNeasy PowerFood Microbial Kit. I have also used the DNeasy PowerSoil Kit, DNeasy PowerSoil Pro Kit, RNeasy PowerMicrobiome Kit, and QIAamp PowerFecal DNA Kit. I like the detailed protocols, particularly when they have an explanation on what is happening during each step. DNA extraction kits are definitely the workhorse of microbial population studies. Can you imagine having to extract all your samples with old school protocols?
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