NSF? Not so fast.

When I was an early PhD student, I barely knew about the NSF GRFP, and it wouldn’t matter if I did since I felt too overwhelmed / behind on everything to consider applying. Fast forward to my postdoc, where I was in a lab that expected you to write for postdoc fellowships (it’s a good policy, btw), in a department where half the grad students seemed to *win* an NSF GRFP any given year; this experience made me realize just how useful of a training opportunity writing fellowship applications can be, as well as helping me to realize that there can be a bit of a feed-forward effect for success, where being awarded a competitive fellowship early on opens up a small number of additional possibilities, which can compound over time until the final result ends up being a large effect.

Well, simply bringing this ethos with me when starting my own lab seemingly isn’t enough; there are apparently entire institutional administrative systems that can get in the way. I’ve already talked about a previous experience, where the school grants offices wouldn’t allow a student’s application to be sent since they weren’t in the internal grants management system yet, despite the fact that NSF GRFP applications are supposed to be sent in by the student. At least that application got saved at the 11th hour, and was actually successfully submitted and reviewed, even though it went unfunded.

This year, we had two students put together well-prepared, complete applications, only to be disqualified on the same technicality. Turns out, sometime within the last two years, the school started putting a summer class on the transcripts of incoming biomedical PhD students; in short, instead of the first entry of their transcript being the fall quarter, there is a summer quarter listed on the transcript preceding it. In actuality, the only thing that is happening during this time is rotations, which typically start in July or August here. There may be a handful of workshop type things, but nothing that counts as an academic course that is a requisite for eventually graduating. It’s effectively the same situation as most other PhD programs in terms of timing of official instruction.

Well, in the case of 2nd year grad students, NSF considers that summer transcript entry as indication that they have completed 1 year of graduate coursework prior to submission, disqualifying them. Each of the two students got an email from NSF saying so, and each student tried to get a statement from the university administration clarifying the situation. In neither case was the school willing to deviate from whatever legal wording they already had, so the disqualification appeal filed by the student was denied by NSF.

So two applications (and probably more) where, in retrospect, the student was writing the application documents, as well as corralling letter writers, with a 0% chance of success. You’d think the school would want to change their transcript policies to not unnecessarily disqualify their biomedical PhD students from the NSF GRFP, but there was seemingly little indications that the contacted administrators will do anything about it. So essentially, no CWRU School of Medicine PhD student in their second year should submit an NSF GRFP application, unless something changes. Maybe (hopefully), this isn’t the case with other CWRU schools, like those overseeing biology or bioengineering.

Well, the biomedical PhD students can still apply in their first year, right? I suppose so, although if they’re new to the campus, they probably aren’t writing their application based on a 4 to 6 week rotation (the expected rotation duration in our school). Only those that were in the know and had strong, supportive research environments prior to grad school would be in the running, and I suspect that isn’t a large fraction of our incoming student populations.

So a school that simultaneously bemoans a lack of student fellowships, yet through lack of experience and rigid / misguided administration, manifests the same situations it bemoans, with little indication that this will ever change even when notified of the problem. Institutions, man.

Open Research Assistant Position

Our lab space issues were recently resolved, so I’m now able to spend some of my remaining start-up funds to hire more personnel. I also have a bunch of starts to various research directions, and nobody aside from me to push parts of them forward in various aspects (eg. tissue culture, data analysis, experimental planning). I’m curious to see if I can find a relatively recent college graduate that is interested in pursuing a PhD program, but wants to take a year or two beforehand to gain more hands-on research experience. Well, if so, here’s an open position on the CWRU hiring website that can be applied to (if you’re like me and already a CWRU employee, you may need to open that link in an incognito window since existing cookies can get in the way otherwise).

HEK cell small molecule toxicities

I’ve now done a *bunch* of kill curves with HEK cells in various forms (WT HEK cells, single or double landing pad cells). Here’s a compendium of observed toxicity of serial dilutions of various small molecules in HEK cells not engineered to be resistant in any way. (This is mostly for my own reference, when I’m in the TC room and need to check on some optimal concentrations).

Old Lab Photos

As the lab finishes its 4th year of existence, I’m realizing that the older lab photos are going to eventually overwhelm the “personnel” page, but I still want to save them for posterity. Thus, I’ll start only keeping the most recent lab photos on the personnel page, while transferring older photos to this blog post.

Here’s the history of lab photos for the Matreyek and Bruchez labs, from (almost the) most recent to oldest:

September 2022: Matreyek and Bruchez lab picnic! From left to right: Sarah, Michelle, Nisha, Kenny, Alex, John*, Avery, Anna, Lane*, Nidhi, Olivia, Vidusha*. *[rotation student]
June 2021: Celebrating Drew’s last day, and Vini starting grad school at CWRU.
^ Geeks who (mostly do not) drink at Boss Dog Brewery, July 13, 2021.
“The Cloneheads” got 10th place out of 20 teams; a full 10 places higher than we expected to be!

Landing pad kill curves

I previously did some recombined cell enrichment curves using flow cytometry of mixed cells populations (containing both recombined and unrecombined cells) upon treatment with various selections (Blast, Puro, Hygro, Zeo), but my recent experience testing out the various plate readers got me in the mode of doing serial dilutions with various cell viability / (relative) cell counting assays, so I did that for our mostly commonly used Single Landing Pad HEK cells (LLP-Int-BFP-IRES-iCasp9-Blast) as well as our still unpublished Double Landing Pad HEK cells. Here are what those curves generally look like.

Note: The Double Landing Pad cells encode hygromycin resistance within the second landing pad, so the difference in hygromycin IC90’s in the SLP and DLP cells is expected. Once we have the plate reader purchased and back in the lab, I’ll probably do some other conditions (eg. unmodified 293Ts, recombined SLP cells, recombined DLP cells) for some of those common cell culture antibiotics.

Note 2: Also, now that I know the general effective concentrations of some of these chemotherapeutics (eg. cyclophosphamide, gemcitibine, vincristine; although I did completely overshoot the concentrations for gemcitibine), I’m somewhat set up to see how the IC90 changes when I overexpress various transgenes that should increase resistance to those drugs.

A personal clingen vignette

Back in 2017, when I was a postdoc and still first learning the human genetics field, I encountered a clinically relevant situation in my own family’s genetics. In short, my bloodline seemed to harbor a quite rare recessive allele in a gene encoding the “battery pack” for a set of critical hormone (and other small molecule) modifying / metabolizing enzymes. When two dysfunctional copies are harbored in the same individual, there are devastating consequences on the developing child.

Figuring this out ended up being an interesting academic exercise, since it was a case where I could synthesize a lot of the knowledge I had built up, from more recently acquired knowledge in human genetics, clinical genetics, genomic technologies, and genomic databases, to somewhat older knowledge I had on literature searches, molecular biology, cell biology, and protein structure-function. Here’s a report I had provided a family member upon embarking on my quest to understand the situation. Aside from my family, I had directly shared it with various friends / colleagues / trainees over the years, but a recent conversation with people in the lab made me realize that I may as well share it more broadly at this point (any lingering minor concerns about publicly sharing “private” health-related information – for both me and at least some of my family members – is offset by what I think is a nice case-study of the importance of science and genetics on understanding human disease.

Note: In the process of having Avery, we did get Anna tested, and she was not a carrier for any variants in POR thus making Avery’s risk of ABS essentially zero (rather than the number I had calculated at the end of the above document). That said, I remember that getting Anna tested was somewhat of a struggle, between it not being fully covered under insurance and there being some miscommunication between our hospital system and the external genetic testing lab, such that the test results were pretty delayed. Such is the US health care system…

Quantitating DNA via the plate reader

As another installment of the “demoing the plate reader” series, we’re also trying to see how well it quantitates DNA. Probably good that I’m actively involved in this process, as it’s making me learn some details about some of the existing and potential assays regularly used by the lab. Well, today, we’re going to look a bit at DNA binding dyes for quantitating DNA.

We have a qubit in the lab, which is like a super-simplified plate reader, in that it only reads a single sample at a time, it only does two fluorescent colors, and the interface is made very streamlined / foolproof, but in that way loses a bunch of customizability. But anyway, we started there, running a serial dilution of a DNA of known high concentration and running it on the qubit (200uL recommended volume). We then took that same sample and ran it on the plate reader. This is what the data looked like:

So pretty decent linearity of fluorescence between 1ug to 1ng. Both the qubit and plate reader gave very comparable results. Qubit readings missing on the upper range of things for the qubit since it said it was over the threshold upper limit of the assay (and thus would not return a value). This is reasonable, as you can see by the plate reader values that it is above the linear response of the assay.

So what if you instead run the same sample as 2uL on a microvolume plate instead of 200uL in a standard 96-well plate? Well, you get the above result in purple. The data is a bit more variable, which probably makes sense with the 100-fold difference in volume used. Also seems the sensitivity of the assay decreased some, in that the results became unreliable around 10ng instead of the 1ng for the full volume in plate format, although again, I think that makes sense with there being less sample to take up and give out light.

7/3/23 update:

Just tried AccuGreen from Biotium. Worked like a charm. They suggest mixing in ~200uL of DNA dye reagent (in this case, to 1uL of DNA already pipetted in), but I tried 100uL and 50uL as well, and if anything, 100uL arguably even looked the best.

Also, I just used the same plate as Olivia had run the samples on Friday. So in running these new samples, I ended up re-measuring those same samples 3 days later. And, well, it looked quite similar. So the samples for reading are quite stable, even after sitting on the bench for 3 days.

Oh, and lastly, this is what it looked like doing absorbance on 2uL samples on the Take3 plate. Looks perfectly fine, although as expected, sensitivity isn’t nearly as much as Accugreen. That said, you do get more linearity at really high concentrations (4000 ng/uL), so that’s kind of nice.

Kenny gets an R21 to study Sarbecovirus receptor interactions

The Matreyek lab is awarded a 2-year R21 grant to study how various Sarbecovirus (ie. SARS-like coronavirus) receptor binding domain sequences correspond to binding and infection with various ACE2 receptor sequences (eg. variants of human ACE2, or sequences of diverse ACE2 orthologs across mammals) to find the rules governing molecular compatibilities between these viruses and their potential hosts. More information here.

Quantitating cells via the plate reader

In moving down the floor and having some more space, we’ll be purchasing a plate reader. Based on previous experience / history, I’ve started by testing the BioTek Synergy H1. We’re going to put it through a number of the more traditional paces (such as DNA and protein quantitation), but we clearly have a bunch of cell-based experiments and potential assays that are worth testing on it. Since I’m curious about some of the possibilities / limitations here, I’ve taken a pretty active role in testing things out.

For these tests, I essentially did a serial dilution of various fluorescent protein expressing cells, to assess what the dynamic range of detection could be. Here, I did half log dilutions of the cells in a 96-well plate, starting with 75,000 cells (in 150uL) for the “highest” sample, and doing 6 serial dilution from there down to 75 cells per well, with a final row with media only to tell us background fluorescence. Everything was plated in triplicate, with analyses done on the average.

For the purposes of not having a ton of graphs, I’m only going to show the background subtracted graphs, where I’ve created a linear model based on the perceived area of dynamic range, and denote black dots showing datapoints that linear model predicts, to see how well it corresponds to the actual data (in color).

The above shows serial dilutions high UnaG expressing landing pad cells. Seems like a decent linear range of cell number -dependent fluorescence there, where we can see perhaps a little more than two orders of magnitude in predictable range. Of course, this is one of the least relevant (but easiest to measure) cases, so not super relevant to most of our experiments.

On the other hand, this is a situation that is far more relevant to most of our engineered cell lines. Here, it’s the same serial dilutions of cells, except we’re looking for histone 2A -fused mCherry. The signal here is going to be lower for three reasons: it’s behind an IRES instead of cap-dependent translation, red fluors are typically less bright than green fluors, and the histone fusion limits the amount of fluorescence to the nuclei, so the per-cell amount of fluorescence is decreased. Here, it was roughly a 20-fold range of the assay down from a confluent well. Maybe useful for some experiments quantitating effects of some pertubation on cell growth / survival (without exogenous indicators!) but obviously can’t expect to reliably quantitate more than that 20-fold effect.

Those are direct cell counting assays (or, well, relative counts based on total fluorescence), but what about enzymatic assays, such as common cell counting / titering assays based on dye conversion. I could certainly see these assays potentially having more sensitivity due to a “multiplier” effect through that enzymatic activity. Well, this is what it looks like for Resazurin / Alamar Blue / Cell Titer Blue.

The above is based on Resazurin fluorescence, where we have a pretty decent 2-log range, although even with these conditions, the confluent wells already saturated dye conversion and lost linearity.

Here, I’m testing a different cell titering dye, CCK-8 / WST-2, which only uses absorbance at A460 as its readout. Here, the linear range of the assay seemed to be a lot less; roughly 1 order of magnitude. I’m not showing resazurin conversion absorbance (A570, A600) here, but it looked pretty similar in overall range as CCK-8.

How about timing for the Resazurin and CCK8 assays? Well, here is what it looks like…. Note, I didn’t do the same linear modeling things, b/c I got lazy, but you can still tell what may be informative by eye:

So clearly, we lose accuracy at the top end but gain sensitivity at the bottom end by having the reaction run over night. This is looking at fluorescence. How about absorbance? That’s below:

Same shift toward increased sensitivity for looking at fewer cells, but same dynamic range window, so we lose accuracy in the more confluent wells as it shifts.

Here, the overnight incubation really didn’t do anything. Same linear range, really.