Summer projects in the Liggins Institute

Search for Summer Research Scholarships projects in the Liggins Institute.

Gene expression changes induced by local injury in human endometrium


Project code:  MHS091

Department

Liggins Institute

Supervisor

Anna Ponnampalam

Endometrial scratching performed by pipelle biopsy is currently being proposed as a technique to improve the probability of pregnancy in subfertile women and couples. The process of obtaining an endometrial sample is believed to create an injury or disturbance to the lining of the womb, making it more receptive to the implantation of an embryo.

The mechanism underlying the suggested reproductive effect are thought to involve inflammation process, specifically the recruitment of immune cells that produce cytokines such as interleukin-6, which characterise early implantation.

This summer studentship will investigate the potential biological pathways underlying the improved pregnancy outcomes following endometrial scratch. The student will participate in patient recruitment and sample collection. He/she will then analyse repeat biopsies from the same women taken during two consecutive cycles directly prior to her IVF cycle. The samples will be analysed in a “before and after” type comparison to determine if there are any gene expression changes in favour of successful embryo implantation associated with endometrial scratching prior to IVF cycle commencement.

Skills

RNA Extraction
Real-time PCR
Data analysis

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New statistical methods for detection of biomarkers of premature birth in the maternal metabolome


Project code:  MHS106

Department

Liggins Institute

Metabolomics seeks to obtain a profile of as many metabolites (amino acids, fatty acids, sugars) as possible, in any given biosample. The metabolite composition of some biosamples is highly variable depending on what the subject has been eating or doing just before the sample was taken.  This can obscure differences in the average levels of metabolites between healthy and diseased individuals. 

We will examine whether looking for differences in the covariance model, which describes how sets of metabolites tend to increase and decrease together, can  detect  dysregulation  that is not obvious from differences in mean metabolite levels.  Our approach will be to model the differences in inverse covariance for several large cohort metabolomic datasets from New Zealand, Ireland, and Singapore in order to infer differences in the metabolic network.  The metabolite profiles will be compared with data on pregnancy complications, including gestational diabetes, pre-eclampsia, preterm birth, small for gestational age infants, and macrosomia.  Other statistical strategies will also be investigated.

Skills

Skills that will be taught:

  • Advanced use of R and/or Matlab
  • Fundamentals of  (inverse) covariance modelling
  • Techniques for preserving data integrity while handling large datasets
  • Publication-standard data plots using R
  • Library databases and literature review skills

This project would suit a second or third year undergraduate student with an interest and some background in statistics.  The ideal candidate would have experience using R, or Matlab, or other computer programming languages.  Candidate preferences:

  • An interest in statistics
  • Computer skills, statistics or programming skills
  • Self-motivated
  • Creative thinker
  • Attention to detail
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Discovery lipidomics: biomarkers for prediction of pregnancy complications


Project code:  MHS151

Department

Liggins Institute

Lipidomics is the study of all of the lipids present in any given biosample.  Suitable methods for lipidomics profile of a wide range of lipids, including triglycerides, phospholipids, sphingolipids, ceramides, gangliosides, fatty acids, cholesteryl esters, glycerolipids, and sterols.

Project Aims

Lipid profiles will be obtained from the plasma of 1000 pregnant women from Singapore for correlation with their pregnancy outcomes.  The successful applicant will be carrying out extraction of lipids from maternal plasma for liquid chromatography - mass spectrometry (LC-MS) analysis.  Techniques from analytical chemistry and mass spectrometry will be used to extract and measure as many lipids as possible.  If time permits, we will also use a typical LC-MS dataset to compare the performance of open-source software with commercial LC-MS data extraction software.

Skills

Skills that will be taught:

  • Lab hygiene and handling of human samples
  • Storage and handling of temperature sensitive samples
  • Calibration and use of pipettes
  • Cold solvent extraction of plasma
  • Use of centrifugal vacuum concentrators for lypholisation
  • Mass spectrometry data extraction and identification software

Candidate preferences:

  • Hepatitis B immunisation preferred, but can be arranged
  • Science or Biomedical major, laboratory experience preferred
  • Creative thinker
  • Self-motivated
  • Attention to detail
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