Week 5 and 6

These two weeks I have been largely focusing on my research project, so I will combine them into one mega post. The basic goal for my project is to perform single cell RNA-seq on cells derived from the urine sediment from kidney transplant patients to explore the heterogeneity of cell types and potentially identify new candidate genes that are prognostic and diagnostic of allograft rejection or infection. Current studies have looked at bulk mRNA expression profiles from urine pellets with some success in predicting rejection before clinical confirmation via biopsy. We are interested in the potential new discoveries that can come with single-cell resolution of these urine pellets.

While the cost of single-cell RNA-seq has traditionally been on the order of tens to hundreds of dollars per cell, recent advances in microfluidic and molecular barcoding technologies such as Drop-seq and the 10X Genomics Chromium system have reduced these costs to the order of single dollars or cents. I have been working on setting up a Drop-seq system back in my lab in Ithaca and this has in part motivated the particular goals of my project here.

Many different types of cells can be found in the urine sediment, including erythrocytes, leukocytes, renal tubular epithelial cells, transitional epithelial cells, and squamous epithelial cells. Additionally, bacteria, crystals, and urinary casts can also be found and are indicative of different types of kidney injuries. I have been working on creating single cell suspensions from the urine pellets obtained from patients, which has proven a bit difficult. One major issue is the great variability in the amount of cells derived from a urine sample from patient to patient. In observing the serial sample collections from different patients for the current clinical study in the nephrology lab, I have noticed that some patients consistently produce smaller pellets while others with similar time frame post transplantation and clinical outcome have much larger ones. Obtaining a large sample of viable cells (>100,000) is important for the particular sequencing platform I will be using as less than 10% of sample cell input is actually captured for sequencing. Another issue is streamlining the process of obtaining a sample from a patient, spinning down the sample and producing a single cell suspension with known cell concentration and then transporting the sample to the genomics core for processing in a timely manner to maintain sufficient cell viability. Even obtaining samples in the first place is complicated by potential contamination with skin epithelial cells during collection by the patient. These are issues I have not encountered before when working with cells in culture, and this experience has really opened my eyes to the realities of working with clinical samples.

In addition to my ongoing research project, I was able to do a bit outreach activity over the weekend with a program that I was very involved with for the past three years. I participated in a college Q&A session at the New Jersey Governor’s School of Engineering and Technology in which I was able to talk about my undergraduate and graduate experiences as well as share some of my clinical immersion experiences with some of New Jersey’s most talented high school students. I would like to think it was beneficial to some of the students, especially those considering careers in medicine.

Music Selection of the Week (Fourth of July Edition): Yes (Originally Simon and Garfunkel) - America