Dr Suparna Mitra
- Position: University Academic Fellow
- Areas of expertise: Metagenomics; Metatranscriptomics; Bioinformatics; Biostatistics; Microbiome
- Email: S.Mitra@leeds.ac.uk
- Location: Microbiology, Old medical School
- Website: LinkedIn | Googlescholar | Researchgate
Currently I am a University Academic Fellow in Gastrointestinal Research including Bioinformatics at Faculty of Medicine and Health, University of Leeds and Honorary Research Fellow at Leeds Teaching Hospitals NHS Trust.
I am responsible for supervision, data handling and analyses of multiple medical projects involving Genomics, Statistics and Bioinformatics. For example few of the major projects among others are:
- Development of an invitro intestinal dysbiosis model (Co-Investigator, Bioinformatics lead). Funded by Centers for Disease Control and Prevention (CDC) (£327,740)
- Colorectal Cancer Cohort Study (COLO-COHORT) (Co-Investigator, Bioinformatics lead). Funded by Guts UK Charity (£269,284).
- Effects of trehalose on C. difficile infection (Co-Investigator). Funded by Hayashibara Co Ltd (£57,260).
- Analyses of patients’ gut microbiome during a clinical trial of ridinilazole (Summit Therapeutics), a narrow-spectrum antibiotic for C. difficile infection.
- Gut microbiome analyses of samples from a phase 3b clinical trial examining the effects of a novel extended fidaxomicin dosage regimen (Astellas Pharma), designed to prevent C. difficile germination, to reduce the rate of CDI recurrence.
Academic and professional background:
2003- BSc: Mathematics; University of Burdwan, India
2005- MSc: Statistics (with first class degree); University of Burdwan, India
2007-2010- PhD: Bioinformatics (Suma cum laude); Algorithms in Bioinformatics, University of Tuebingen, Germany
2012-2013- Experienced researcher Marie Curie fellowship
I came from Mathematics and Statistics background (BSc & MSc), then felt extremely interested in the applied side of Statistics and to the new genomics era. That motivated me to pursue my PhD in Bioinformatics in the group of Professor Daniel Huson (Tuebingen, Germany). My PhD thesis “Comparative Metagenome Analyses” was mainly related to the application of statistics and data analysis in next-generation sequencing: the newly evolved field of Metagenomis; for which I obtained summa cum laude grade from University of Tuebingen in 2010. During my PhD, I was also a teaching staff in the department and was responsible for different seminar courses and practicals. After completion of my PhD, I continued working as a postdoctoral researcher and teaching staff in University of Tuebingen for another year.
Following that, I worked as an experienced researcher with a prestigious Marie Curie fellowship (Initial Training Network: INT) in Wolfson Centre for Personalised Medicine, University of Liverpool, during 2012-2013. During this time I worked mainly on medical data analyses to investigate and correlate the effect of significantly expressed genes in patients’ drug-induced hypersensitivity conditions using Microarray, Exom sequencing.
After that, I worked as a Senior Research Scientist at cluster 2 (Meta-’omics and systems biology cluster), SCLESE, Nanyang Technological University, Singapore. There I was responsible for analyses of NGS data from multiple projects which involve environmental and medical metagenomics and metatranscriptomics data analyses.
I again moved to UK on 2014 as a Senior Research Scientist at Gut Health and Food Safety, Institute of Food Research & Norwich Medical School, University of East Anglia. There I was responsible for data handling and analyses for a number of large-scale NGS projects in the lab. One of the significant projects is the Baby Associated MicroBiota of the Intestine (BAMBI) Study, which is aiming to characterise the microbiota of preterm and term infants over time (from birth to 1 year of age) and to examine how external factors (including probiotic supplementation and antibiotics) modulate early life microbiota development. Another major project is Zoo Animal Microbiome, which is focusing on understanding the microbiome of captive animal population, including invertebrates, mammals, birds, reptiles. This may open up avenues for isolating new health-promoting bacterial strains for human and at the same time determine animal-specific microbial therapies in order to promote captive animal health.
The majority of my research involves applying metagenomics and metatranscriptomics to medical sciences, especially the complex gut microbiome which is a major potential reservoir for antimicrobial resistance genes that may be selected for and/or transferred to potential pathogens. In medical studies, longitudinal observations (time series data) are particularly important, but remain uncommon, rather than single or before/after treatment results. The former has much greater power to identify key, patho-physiologically/functionality relevant microbiome changes (taxonomy), as opposed to the consequences of such alterations.
With an interdisciplinary research background, I am inspired to apply my knowledge and experience in developing multivariate methods for ’omics data analyses that can identify potential applications in the real-world. During my research career, I have several years of experience in working both theoretical (statistics/bioinformatics) and applied (biostatistics/ medical/ biology/ infection control) research groups and various projects. I have productive collaborations with colleagues in the UK, Germany, USA, Denmark, Singapore, Malaysia and India.
See my recent bookchapter Multiple Data Analyses and Statistical Approaches for Analyzing Data from Metagenomic Studies and Clinical Trials
Omics in personalised therapeutics: The fast moving field of personalised medicine and therapeutics is showing positive impact on clinical care and deserves more attention. I have contributed significantly on bioinformatics method development and analyses for several clinical projects as listed below:
- Randomised trial of the effect of omega-3 polyunsaturated fatty acid supplements on the human intestinal microbiota (doi: 10.1136/gutjnl-2017-314968).
- Analyses of patients’ gut microbiome during a clinical trial of ridinilazole (Summit Therapeutics), a narrow-spectrum antibiotic for C. difficile infection (CDI). Recently, we presented these effects (vs. fidaxomicin treatment) (iCDS Abstract Book: http://www.icds.si/wp-content/uploads/2018/09/web-2018-09-ICDS-zbornik-prispevkov-170x235.pdf; page 42).
- Gut microbiome analyses of samples from a phase 3b clinical trial examining the effects of a novel extended fidaxomicin dosage regimen (Astellas), designed to prevent C. difficile germination, to reduce the rate of CDI recurrence .
- Exploring the gut microbiome and the effect of antibiotics and probiotics with regard to the prevention of severe gastrointestinal pathology in premature babies (necrotising enterocolitis)(doi: 10.1186/s12864-017-4229-x; ongoing project).
- Investigated the microbial community diversity between atherosclerosis patients vs. control subjects (doi: 10.1186/s40168-015-0100-y).
- Successfully analysed study subjects’ intestinal microbiome to assess the effect of laparoscopic sleeve gastrectomy versus very low calorie diet (doi: 10.1155/2015/806248).
Methods development and application of Statistics:?Microbiome analysis is heavily reliant on statistical and computational analysis developments. I am active within the academic community in addressing the need to develop the statistical and computational tools for ’omics studies. My research on development of visual and statistical techniques for pairwise (doi: 10.1093/bioinformatics/btp341) or multiple comparisons (doi: 10.1038/ismej.2010.51) and on different methods for comparative metagenomics are implemented in MEGAN (doi: 10.1101/gr.120618.111; 10.1007/978-1-61779-585-5_17). Our latest MEGAN publication own the the PLOS Computational Biology Research Prize 2017 in the category Exemplary Methods/Software (doi: 10.1371/journal.pcbi.1004957). Additionally, I have worked extensively to address data analysis techniques involving different kinds of sequencing such as amplicon (16S, doi: 10.1186/1471-2164-14-S5-S16), shotgun (mate-pairs, doi: 10.1186/1471-2105-11-S1-S12) and functional annotations (doi: 10.1186/1471-2105-12-S1-S21). Profiling of faecal samples using the 16S-rRNA gene is the most often deployed and cost-efficient method for large-scale clinical microbiome studies. However, the bacterial DNA extraction method and the region of the 16S-rRNA used can significantly affect the results and confound comparisons between studies. Thus, a recent project 16S-rRNA gene sequencing protocol is optimised to allow standardisation of methods for studying infant faecal samples (doi: 10.1186/s12864-017-4229-x).
- BSc Mathematics
- MSc Statistics (1st class)
- PhD Bioinformatics (Summa cum laude)
- European Society of Clinical Microbiology and Infectious Diseases (ESCMID).
- Microbiology Society (SGM)
- 2021: Lecture on "How have massively parallel sequencing technologies furthered our understanding of oncogenesis and cancer progression?" under module MSc Cancer biology and molecular oncology MEDM5221
- 2019-2020: RESS I Foundation II: Special Studies Project
- 2018-2019: RESS I Foundation II: Special Studies Project
- 2018-2019: Tutor for MBChB Year 1; Research Evolution and special studies (RESS) Human Biomarker Project
Research groups and institutes
- Leeds Institute of Medical Research at St James's