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.

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…

LP publications

For my own curiosity (as well as for some data in case I want to show to granting agencies that I’m not hoarding the research tools / materials that I make), I keep track of the papers that have used the landing pad cells / materials in their work. Here’s a chart of publications using some version of the LP cells over time.

The first few papers were mine, but from there, there have been roughly 10 or more papers per year. It’s seemingly been a little higher in the most recent couple of years, although the 2023 date has a dotted line projection for the end of year number (in the instance of my originally writing this paragraph, it was early June).

Manuscript acceptance timing

I’ve now been an author on enough papers to have a reasonable sampling of what the experiences can be like. In short, it minimally takes 2 months to go from initial submission to eventual manuscript acceptance. These experiences typically are those that require little to no experiments for revision. The process, especially when requiring hefty experiments or multiple rounds of revision, can easily stretch to half a year. In some cases it can take *much* longer (in one experience I’ve seen, a journal did the “rejected but amenable to resubmission if sufficient additional impact is added”, which resulted in an informal span of ~ 800 days!!! ). Anyway, at least for the manuscript submissions I was involved with where I had access to an author portal (or received emails when things happened), I noted when the reviews were returned and revisions submitted, to also keep track of how much of that time was technically under one’s control (manuscript with authors; red) or completely out of one’s control (manuscript with journal; blue). See below:

Also, part of the reason it makes sense to post manuscripts to bioRxiv; why have a completed manuscript that is essentially publication-worthy sit in the dark for half a year?

Note: Obviously this data is for manuscripts that eventually got accepted. Rather pleasantly, I’ve never been first or corresponding author for a paper that got rejected, so I don’t have nearly as good a sampling of that experience. But sitting on the sideline as a middle-author for a handful of such occasions, it would seem to take anywhere between a week (eg. immediate desk rejection) to a couple of months (eg. rejected upon peer review) per submission; when sequentially shopping across multiple journals to find a taker, this would seem to add up.

Network drive for file storage

I’m so tired of being jerked around by various cloud storage services. Institutional Google Drive was unlimited storage, but now the University has capped it at 100GB (how uselessly small…). I believe the institutional Box account was also unlimited, but apparently it is now 1 TB. Which, I mean, is better than 100GB, but also the Box interface is painfully awful and IMO is not useful for anything other than “cold storage” of files, where 1 TB isn’t going to cut it. Regardless, I solved this problem for actively used shared file storage for my lab by purchasing 2TB of GoogleDrive cloud storage for $100 a year (out of my personal bank account). Still doesn’t solve the “cold storage” problem for microscopy data, which can easily run much more than a terabyte.

Well, I have an iMac at work that is hooked up to a landline, and I have plenty of external hard drives, so I’m going to try to allow one of those external hard drives be discoverable on the network, and see if that works as a way to store our microscopy data. To access this network (on a mac, at least), follow these instructions:

  1. If you’re not directly hooked up to the landline on campus, you’ll need to VPN in. This is done through FortiClient. This will require DUO authentication (so check your phone to accept).
  2. If you’re now connected to the VPN, you can now try to load that external network drive. to do this, hit Command + K while in the MacOS Finder (or go to the top menu and hit Go > Connect to Server…) and then enter the following:
    smb://[See the IP address the Matreyeklab_Overview_Googledoc]/MLab_5TB
  3. You might have to put in a username and password. This will be the standard lab username and password (refer to the Matreyeklab_Overview_Googledoc if you’ve forgotten, but you must have memorized this by now…)
  4. Voila! You should now have a Finder window for the external hard drive, which will (at the least) have a folder called “Microscopy”.
  5. Now what if you want to do things on the Terminal, since you’re a power user (perhaps aspiring power user?). In that case, load up a new Terminal instance, back out of your own account directory into one of the root directories of your computer (ie. do “cd ../..) and then go into the “Volumes” directory, and if you’ve accessed the network drive like described above, you should now be able to go into the external hard drive directory off the network (ie. do “cd MLab_5TB), and start doing what you need to do there.

Yay, problem solved. Obviously the above instructions are only for lab members. If you run into problems, LMK, and I’ll try to help troubleshoot.

Various links / references, mostly for my own use:
https://support.apple.com/guide/mac-help/set-up-file-sharing-on-mac-mh17131/13.0/mac/13.0
https://support.apple.com/guide/mac-help/servers-shared-computers-connect-mac-mchlp3015/13.0/mac/13.0
https://support.apple.com/guide/mac-help/connect-mac-shared-computers-servers-mchlp1140/mac
https://www.makeuseof.com/how-to-set-up-access-network-drive-mac/

NIH grant expenditures

At least in my SOM-based department, one’s general status is supposedly correlated with the amount of indirect costs they bring in. It looks like I’m currently capped at 4 desks for my personnel, and it’s not clear if it’s worth trying to expand here. Regardless, this is apparently the directs / indirects space I’m operating in with my current setup.

What does this come out to in terms of indirect costs generated per month? Here’s the plot based on my budget reports, below:

So, essentially at my steady state (which I’ll probably be at for at least the next 2.5 years), the lab is generating ~ $20k a month in indirects for the department, amounting to about ~ $5k per desk per month.

Ah, the business of SOM-based academic research. Well, I’m nothing if not transparent.

Submitted DNA amounts and reads returned

In this previous post, I showed how many reads we’ve gotten from our Plasmidsaurus and AMP-EZ submissions. Well, now’s also time to see whether the amount of DNA that we gave correlated with the number of reads we got back.

Submissions to Plasmidsaurus. Red vertical line denotes the minimum value asked for submission (>= 10uL at 30 ng/uL). Blue line is a linear model based on the datapoints.

As you can see above, since this is miniprepped DNA, it’s usually quite easy to reach the 300 ng needed for submission. One time, when we submitted closer to 200ng, it worked perfectly fine. One other time, when we submitted ~ 100ng, it did not, albeit this was not plasmid DNA and instead was a PCR product, so it’s an outlier for that reason as well.

Submissions to Genewiz / Azenta AMP-EZ. Red vertical line is the minimum amount of DNA asked for, while the horizontal red line is the number of reads they “guarantee” returned. Blue line is a linear model based on the data.

This is the more important graph though, since all of our AMP-EZ submissions are from gel extracted PCR amplifications, and it can be quite difficult to do it in such a way that we have the 500 ng of total qubitted DNA available for submission. Well, turns out that it’s probably not all that important for us to hit 500 ng of DNA, since it’s worked perfectly fine in our attempts between 200 and 500 ng. I imagine people in my lab will simultaneously be happy (knowing they don’t have to hit 500 ng) and sad (knowing they had spent a bunch of extra effort in the past unnecessarily trying to reach that number) seeing the above data, but hey, it’s good to finally know this and better late than never!

Workday accounting

Rather facetiously got a suggestion to keep track of how my workdays are spent, but that did prompt me to start keeping track since I have gotten into the phase of my job where I’m feeling somewhat burdened by non-research responsibilities and I like having data in hand. As I’ve noted on my other website, my workdays are now largely constrained by daycare hours. Thus, I do have pretty limited hours in a day to get everything done, requiring a fair amount prioritization; doing one things often means not doing something else.

I’ll sporadically hit “run” on my analysis script and the below plot will update. The n values are currently pretty small, but I plan to keep doing this indefinitely.

Keys for the above plot:
Red dashes are mean values across all days. Gray dots are values for individual days.
Research_internal” denotes activities that directly impact my research group (eg. meetings with personnel, data analysis, benchwork).
Research_external” denotes research activities that don’t have to do with my group (eg. Science-centric meetings with other faculty, emails to people requesting reagents).
Administrative_internal” denotes general paperwork (eg. Filling out my annual performance reviews)
Seminar_director” denotes work related to running the immunology portion of the Dept seminar series (eg. More emails…)
Postdoc_affairs” denotes work related to trying to manage postdoc affairs for the dept (and in some ways, by extension, the SOM).
Other_service” denotes other service activities for the school (eg. Corresponding with CWRU undergrads not in my group).

But I can break down some of these activities further. For example, for the the “Research_internal” section where I’m handling things directly related to my research lab, it can be further broken down as follows:

Most of the categories here are self explanatory. “DNA_construct_stuff” is planning out primers or checking plasmid associated sequencing reads. “Labwork” is mostly tissue culture, since I think that’s where my direct efforts are most valuable (in contrast to using a DNA extraction kit, for example). “Literature” is either doing literature searches or reading papers.

And, well, since so much time seems to be spent writing emails nowadays, this how much time I spend writing emails each day (note: I do all internal communication with lab members via Slack, so this is mostly administrative matters):