Publications – Irina

Papers from Irina either from her work outside of the sluglab.

What is forgetting? Slug lab provides some new insights!

- rcalinjageman

Today, the SlugLab can share an exciting new paper, with contributions from Tania Rosiles, Melissa Nguyen, Monica Duron, Annette Garcia, George Garcia, Hannah Gordon, and Lorena Juarez ​(Rosiles et al., 2020)​.

Where to even start?

  • Contributions from 7 student co-authors! It’s been such a long haul; we’re proud of each of you for sticking with it and for all your contributions to this paper.
  • This paper is a registered report: We first proposed the idea and the methods, even writing a complete analysis script. This was then sent to peer review (you know, when you can still do something if the reviewers turn up an issue or problem to consider!) and after some back and forth received an ‘in principle’ acceptance. Then we completed the work and the analysis and submitted it for one more round of review focused solely on the interpretation of the data. This approach to publication lets peer reviewers have a more meaningful impact on the project and it also helps combat publication bias. People tend to think of this model for replication research, but in our case we used a registered report because we wanted to establish a fair and valid test between two competing theories and to ensure that the approach and analysis were pre-specified.
  • This paper is exciting! We were able to test two very different theories of forgetting:
    • decay theory, which says that memories are forgotten because they physically degrade
    • retrieval failure, which says that memories don’t degrade at all, but simply become more difficult to retrieve due to interference

We found clear support for the retrieval failure theory of forgetting, something I (Bob) was completely not expecting.

So, what was the study actually about?

Even memories stored via wiring changes in the brain can be forgotten. In fact, the majority of long-term memories are probably forgotten. What does this really mean? Is the information gone, or just inaccessible?

One clue is from savings memory, the fact you can very quickly re-learn seemingly-forgotten information. Savings memory is sometimes taken to mean the original memory trace persists, but it could also be that it had decayed, and the remnants prime re-learning.

We noticed a testable prediction:

  • If forgetting is decay, savings re-encodes the memory and must involve the transcriptional and wiring changes used to store new information.
  • If forgetting is inaccessibility, savings shouldn’t involve transcriptional/wiring changes

To test this prediction, we tracked transcriptional changes associated with memory storage as a memory was first formed, then forgotten, then re-activated. We did this in the sea slug, Aplysia calinfornica as a registered report (with pre-registered design and analyses).

The memory was for a painful shock—this is expressed as an increase in reflexes (day 1, red line way above baseline). Sensitization is forgotten in about a week (day 7, reflexes back to normal), but then a weak shock produces savings (day 8, reflexes jump back up)

What’s happening in the nervous system? Our key figure shows expression of ~100 transcripts that are sharply up- or down-regulated when the memory is new. At forgetting, these are deactivated (all lines dive towards 0). At savings? No re-activation! (lines stay near 0)

Our results show that savings re-activates a forgotten memory without invoking *any* of the transcriptional changes associated with memory formation. This strongly suggests the memory is not rebuilt, but just re-activated—the information must have been there all along?!

Lots of caveats (see paper), but the results seem compelling (though surprising) to us. In particular, we used an archival data set to show we would have observed re-activation of transcription had it occurred. Transcriptional changes with savings are clearly negligible.

  1. Rosiles, T., Nguyen, M., Duron, M., Garcia, A., Garcia, G., Gordon, H., … Calin-Jageman, R. J. (2020). Registered Report: Transcriptional Analysis of Savings Memory Suggests Forgetting is Due to Retrieval Failure. Society for Neuroscience. doi: 10.1523/eneuro.0313-19.2020

The remarkably long-lasting fragments of memory

- rcalinjageman

It was a whirlwind 2018. Irina and I are just now catching our breath and finding some time to update the lab website.

One awesome piece of news we forgot to publicize is that our latest paper came out in the August issue of Neurobiology of Learning and Memory (Patel et al., 2018).   This paper continues our work of tracking the molecular fragments of a memory as it is forgotten.  Specifically, we tracked 11 genes we suspected of being regulated *after* forgetting (Perez, Patel, Rivota, Calin-Jageman, & Calin-Jageman, 2017).  Things didn’t work out quite as well as we had expected: of our 11 candidate genes 4 didn’t show much regulation, meaning that our previous results with these genes were probably over-estimating their importance (curse you, sampling error!).  On the other hand, we replicated the results with the other genes and found that some of them are actually regulated for up to 2 weeks after the memory is induced, long after it seems forgotten.

Here are two key figures.  The first is the memory curve for sensitization in our Aplysia -it shows that after memory induction there is strong sensitization recall that decays within a week back to baseline.  Even though the memory seems gone, giving a reminder 2 weeks after learning rekindles a weak re-expression of the memory. That’s a classic “savings” effect.  

The next figure traces the time-course of memory-induced gene expression (levels of mRNA) for 6 specific genes, measured in the pleural ganglia that contains neurons known to be important for storing sensitization memory.  You can see that each of these transcripts is up- or down-regulated within 24 hours of learning, and that in each case this regulation lasts at least a week and sometimes out to 2 weeks.  So, just as the behavioral level of the memory fades but isn’t really completely gone, the some of the transcriptional events that accompany learning also seem to persist for quite some time. 

Why would this occur?  Perhaps these transcripts are part of savings…maybe they set the stage for re-expressing the memory?  Or maybe they are actually part of forgetting, working to remove the memory?  Or maybe both?  For example, one of the transcripts is encodes an inhibitory transmitter named FMRFamide.  It is really up-regulated by learning, which would normally work against the expression of sensitization memory.  So perhaps this helps suppress the memory (forgetting), but in a way that can be easily overcome with sufficient excitation (savings)… that’s an exciting maybe, and it’s the thing we’ll be working this summer to test.

As usual, we’re so proud that this paper was made possible through exceptional hard work from some outstanding DU student researchers: Ushma Patel, Leticia Perez, Steven Farrell, Derek Steck, Athira Jacob, Tania Rosiles, and Melissa Nguyen.  Go slug squad!

Patel, U., Perez, L., Farrell, S., Steck, D., Jacob, A., Rosiles, T., … Calin-Jageman, I. E. (2018). Transcriptional changes before and after forgetting of a long-term sensitization memory in Aplysia californica. Neurobiology of Learning and Memory, 155, 474–485. doi:10.1016/j.nlm.2018.09.007
Perez, L., Patel, U., Rivota, M., Calin-Jageman, I. E., & Calin-Jageman, R. J. (2017). Savings memory is accompanied by transcriptional changes that persist beyond the decay of recall. Learning & Memory, 25(1), 45–48. doi:10.1101/lm.046250.117

New preprint on the very long-lasting transcriptional response to learning

- rcalinjageman

The sluglab has a new preprint out, currently under review at the Neurobiology of Learning and Memory.  We shows that both transcription and savings can persist for as long as 2 weeks after the induction of long-term sensitization, way beyond the decay of recall.  Interestingly, all the long-lasting transcriptional changes start within 1 day of training.  Lots of student co-authors on this one; it was a *lot* of work.  Looking forward to the reviews.

Slug Lab – Distinguished Service Awards from the Faculty for Undergraduate Neuroscience

- rcalinjageman

At this year’s Society for Neuroscience meeting, Irina and I were honored for our contributions to the Faculty for Undergraduate Neuroscience (FUN).  Specifically, we were both given the annual Distinguished Service Award.  The honors were bestowed for our work organizing the FUN conference this past summer and for other work supporting the mission of undergraduate neuroscience education.

We’re so fortunate to be a part of FUN–it’s our favorite people all working towards a mission that is so very important.  Thanks for the great honor, and we’re looking forward to staying very involved with FUN.

Here’s a photo of Irina’s award.

 

 

Maintaining Memories, Changing Transcription

- rcalinjageman

Under the right circumstances, a memory can last a lifetime.  Yet at the molecular level the brain is constantly in flux: the typical protein has a half-life of only a few hours to days; for mRNA a half-life of 2 days is considered extraordinarily long.   If the important biological molecules in the brain are constantly undergoing decay and renewal, how can memories persist?

The Slug Lab has a bit of new light to shed on this issue today.  We’ve just published the next in our series of studies elucidating the transcriptional changes that accompany long-term memory for sensitization in Aplysia.  In a previous paper, we looked at transcription 1 hour after a memory was induced, a point at which the nervous system is first encoding the memory.  We found that there is rapid up-regulation of about 80 transcripts, many of which function as transcription factors (Herdegen, Holmes, Cyriac, Calin-Jageman, & Calin-Jageman, 2014).

For the latest paper (Conte et al., 2017), we examined changes 1 day after training, a point when the memory is now being maintained (and will last for another 5 days or so).  What we found is pretty amazing.  We found that the transcriptional response during maintenance is very complex, involving up-regulation of >700 transcripts and down-regulation of <400 transcripts.  Given that there are currently 21,000 gene models in the draft of the Aplysia genome, this means more than 5% of all genes are affected (probably more due to the likelihood of some false negatives and the fact that our microarray doesn’t cover the entire Aplysia genome).   That’s a lot of upheaval… what exactly is changing?  It was daunting to make sense of such a long list of transcripts, but we noticed some very clear patterns.  First, there is regulation influencing growth: an overall up-regulation of transcripts related to producing, packaging, and transporting proteins and a down-regulation of transcripts related to catabolism.  Second, we observed lots of changes which could be related to meta-plasticity.  Specifically, we observed down regulation in isoforms of PKA, in some serotonin receptors, and in a phosphodiesterase.  All of these changes might be expected to limit the ability to induce sensitization, which would be consistent with the BCM rule (once synapses are facilitated, raise the threshold for further facilitation).  (Bienenstock, Cooper, & Munro, 1982).

One of the very intriguing findings to come out of this study is that the transcriptional changes occuring during encoding are very distinct from those occuring during maintenance.  We found only about 20 transcripts regulated during both time points.  We think those transcripts might be especially important, as they could play a key regulatory/organizing role that spans from induction through maintenance.  One of these transcripts encoded a peptide transmitter called FMRF-amide.  This is an inhibitory transmitter, which raises the possibility that as the memory is encoded, inhibitory processes are simultaneously working to limit or even erode the expression of the memory (a form of active forgetting).

There are lots of exciting pathways for us to explore from this intriguing data set.  We feel confident heading down these paths because a) we used a reasonable sample size for the microarray, and b) we found incredibly strong convergent validity in an independent set of samples using qPCR.

This is a big day for the Slug Lab, and a wonderful moment of celebration for the many students who helped bring this project to fruition: Catherine Conte (applying to PT schools), Samantha Herdegen (in pharmacy school), Saman Kamal (in medical school), Jency Patel (about to graduate), Ushma Patel (about to graduate), Leticia Perez (about to graduate), and Marissa Rivota (just graduated).  We’re so proud of these students and so fortunate to work with such a talented and fun group.

Bienenstock, E., Cooper, L., & Munro, P. (1982). Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 2(1), 32–48. [PubMed]
Conte, C., Herdegen, S., Kamal, S., Patel, J., Patel, U., Perez, L., … Calin-Jageman, I. E. (2017). Transcriptional correlates of memory maintenance following long-term sensitization of Aplysia californica. Learning and Memory, 24, 502–515. doi: 10.1101/lm.045450117 [Source]
Herdegen, S., Holmes, G., Cyriac, A., Calin-Jageman, I. E., & Calin-Jageman, R. J. (2014). Characterization of the rapid transcriptional response to long-term sensitization training in Aplysia californica. Neurobiology of Learning and Memory, 116, 27–35. doi: 10.1016/j.nlm.2014.07009

2014×3 – Transcriptional correlates of long-term habituation

- rcalinjageman

Third paper of the year for the lab (gasp!) is now out in Learning and Memory [cite source=’doi’]10.1101/lm.036970.114[/cite].

The focus of the project is habituation, considered the simplest and most ancient form of memory. Long-term habituation requires changes in gene expression, but to date there is almost nothing known about what specific changes are required to encode and store a long-term habituation memory.

We’re not the first to try to tackle this issue, but it turns out to be a very difficult topic for study. Habituation is typically very site specific, occurring only at the site of training. This implies a relatively discrete set of neurons encode the memory, and that presents a real problem for qPCR and microarray analysis, because the signal from memory-encoding neurons could easily be washed out from signal from non-encoding neurons, glia, etc.

Our strategy was to develop a new, automated protocol for inducing long-term habituation over the entire body of an Aplysia. With the help of a tinker-toy set, a windshield-wiper motor, a relay box, an old computer with a parallel port, and some qBASIC programming (blast from the bast), we developed a slug car wash–an apparatus we could place over the tanks to repeatedly (though gently) brush Aplysia without any need for human intervention during training. We made a video to show off the system, which you can see here.

The slug car wash turns out to work great. We tracked the development of habituation over repeated rounds of training and saw a classic pattern of behavior–robust decreases in behavior at the end of each round of training, substantial overnight recovery (forgetting), but a progressive development of a persistently decreased response within 3 days of training. Importantly, we could observe habituated responding when stimulating the animal at the head, the siphon, or the tail. Moreover, the effect sizes were huge. So it was pretty clear that the slug car wash was producing the high impact we were looking for. In addition, we found that pattern of training really does matter–when training has breaks between sessions and is spaced out over 3 days it is extremely effective; massing all the same stimulation together into a single one-day session (at a slightly higher rate to squeeze it all in) produced neither long-term nor short-term habituation. This is a useful finding because it gave us an additional no-memory control, one which could ensure any molecular correlates identified are specific to memory formation, not just to the activity induced by brushing.

So what’s changing transcriptionally? We decided to focus on the pleural ganglia containing the VC nociceptors. These are relatively high-threshold neurons, and are probably not carrying the bulk of the activity induced by the brush. Unfortunately, though, no one yet knows *where* in the Aplysia nervous system to find the cell bodies of the low-threshold neurons that mediate light touch (probably in the periphery). Not to worry, though–we did record from the VCs in reduced preps and found that they do actually get some activation from the brush: about 1/4 fired APs, and most of the rest got lots of IPSPs from off-center stimulation.

To track transcriptional changes, we used the custom-designed microarray we recently developed in the lab [cite source=’pubmed’]25117657[/cite]. Some quick words about methods: We again used a large-ish sample size (n=8/group; can you believe that n=3/group is still common in microarray!?). We also used very high statistical standards by adopting the ‘treat’ function in limma which allows you to specify a reasonable null hypothesis (e.g. at least 10% regulation in either direction, rather than the standard practice of testing against a null of no regulation). Adopting a more reasonable null enables you to test for statistical and practical significance at the same time, and we’ve found that transcripts which pass such a rigorous test generalize very well to new samples. We’ve been finding R and limma surprisingly easy to use, which is pretty fantastic for free software.

Anyways, back to the data. The microarray results were a bit of a bummer. Out of over 20,000 transcripts tested, only *one* came up as strongly regulated. Bummer. Another 20 transcripts came up as regulated if you use a standard null hypothesis, but, as expected, none of these validated.

Although the microarray results were not what we hoped, we did further explore the one regulated transcript, and it turns out to be quite interesting. From sequence alignment, it seems to be an Aplysia homolog of cornichon, an auxiliary subunit for AMPA receptors. In invertebrates, cornichon seems to limit trafficking to AMPA receptors to the membrane and therefore reduces glugatmate-induced currents[cite source=’pubmed’]24094107[/cite]. Note that this is precisely the type of effect that could produce behavioral habituation. Moreover, one of the few known molecular correlates of long-term habituation is a decrease in surface expression of glutamate receptors [cite source=’pubmed’]14573539[/cite]. Fits perfectly!

To ensure that cornichon is truly regulated in our paradigm, we did some additional follow-ups. First, we used qPCR to check cornichon levels not only in the microarray samples but in an additional, independent set of samples. Sure enough, we confirmed up-regulation of cornichon in the pleural ganglia 1 day after training. In addition, we checked levels in massed animals, who display no memory after training. In this case, cornichon was actually slightly down, and was significantly different than in the regularly trained animals. So, cornichon is quite specifically and consistently up-regulated after long-term habituation training. As far as we know, this is the first specific transcriptional correlate of long-term habituation to be identified.

Needless to say, we’re quite proud of this work. It wouldn’t have been possible without two of the most talented undergrads we’ve had in the lab: Geraldine Holmes and Samantha (Sami) Herdegen. Geraldine was the most diligent slug trainer in the history of the lab. For this paper alone she ran over 48 animals, testing each 8 times a day for 3-5 days–that’s a whole lot of behavior to monitor! Sami, of course, has been the qPCR wizard in the lab, testing lots and lots and lots and lots of transcripts for regulation. It’s no surprise that both are on to bigger and better things, Geraldine is now in a PhD program in Canada and Sami is soon to start pharmacy school. We also had contributions from John Schuon (when he could fight his way in for some qPCR; now off to medical school), Ashly Cyriac (who helped start the project before heading off to pharmacy school), Jamie Lass and Catherine Conte. Congrats!

As has now become the norm for the lab, all the raw data from this study been posted online at the Open Science Framework: https://osf.io/6ew4i/.

Sluglab Strikes Again – New paper tracing dynamics of learning-induced changes in transcription

- rcalinjageman

A nice way to wrap up 2014–we have a new paper out [cite source=’pubmed’]25486125[/cite] where we trace learning-induced changes in transcription over time and over different location in the CNS. We think it’s a nice follow-up to the microarray paper, because:

  • We show that some transcriptional changes are likely occuring in interneurons and motor neurons, not just in the VC nociceptive sensory neurons.
  • We found some transcripts which, like Egr, are rapidly *and* persistently up-regulated by sensitization training (GlyT2, VPS36, and an uncharacterized protein known for now as LOC101862095). We’re interested in such transcripts because they could be related to memory maintenance
  • We were able to better test the notion that CREB supports memory maintenance. So far, our evidence continues to go against this hypothesis, with no long-lasting changes detected in the VC sensory neurons nor in the pedal ganglia.
  • As a methodological point, we found that microdissecting out the VC cluster really really improves signal:noise for identifying transcriptional changes induced by learning. This is exciting–most work on the molecular mechanisms of memory uses tissue samples representing homogenous cell types. Zooming in on a single cell type of known relevance for storing the memory really enhances the power of the analysis.
  • We re-rested the four novel transcripts identified in our microarray paper from earlier this year [cite source=’pubmed’]25117657[/cite]. All four validated again! Moreover, all 4 were specifically up-regulated in the VC nociceptors (and some elsewhere as well). Another good indication that we’re on the right track with our microarray approach.
  • Another 3 student co-authors on this paper! We’re especially proud of Sami, Catherine, and Saman.

    • The paper is free on PLOSE ONE: http://dx.plos.org/10.1371/journal.pone.0114481. Also, you can download our raw data to examine for yourself at the Open Science Framework: https://osf.io/ts9ea/.

    New Publication – Microarray analysis of sensitization

    - rcalinjageman

    We’ve got a new paper out [cite source=’pubmed’]25117657[/cite] with the first of what we hope will be a series of studies using microarray to track the transcriptional changes following long-term sensitization training. This paper looks at the changes that occur immediately (1 hour) after training. It provides lots of details and data to validate the microarray design we developed, but also identifies a set of 81 transcripts that are strongly regulated after learning. Best of all, for a microarray paper, we use a large sample size (n = 8) and show using a subset of transcripts that most generalize to a completely independent sample. Among the changes we fully validated are up-regulation of a c/ebp-gamma (what the what!?), a glycine transporter, and a subunit of ESCRTII. The rest of the gene list that we’re working on has some exciting possibilities, too.

    Another thing to be proud of, is our three student co-authors on the paper.

    The paper is free for the next 50 days via this link, then it goes behind a paywall for 305 days, then it will be in PubMedCentral for free again (strange, right?). All the raw data is available on the Open Science Framework: https://osf.io/8pgfh/.

    Harmonin enhances voltage-dependent facilitation of Cav1.3 channels and synchronous exocytosis in mouse inner hair cells

    - rcalinjageman

    Gregory FD, Pangrsic T, Calin-Jageman IE, Moser T, Lee A

    J. Physiol. (Lond.) 2013 Jul;591(Pt 13):3253-69

    PMID: 23613530

    Abstract

    Cav1.3 channels mediate Ca(2+) influx that triggers exocytosis of glutamate at cochlear inner hair cell (IHC) synapses. Harmonin is a PDZ-domain-containing protein that interacts with the C-terminus of the Cav1.3 α1 subunit (α11.3) and controls cell surface Cav1.3 levels by promoting ubiquitin-dependent proteosomal degradation. However, PDZ-domain-containing proteins have diverse functions and regulate other Cav1.3 properties, which could collectively influence presynaptic transmitter release. Here, we report that harmonin binding to the α11.3 distal C-terminus (dCT) enhances voltage-dependent facilitation (VDF) of Cav1.3 currents both in transfected HEK293T cells and in mouse inner hair cells. In HEK293T cells, this effect of harmonin was greater for Cav1.3 channels containing the auxiliary Cav β1 than with the β2 auxiliary subunit. Cav1.3 channels lacking the α11.3 dCT were insensitive to harmonin modulation. Moreover, the ‘deaf-circler’ dfcr mutant form of harmonin, which does not interact with the α11.3 dCT, did not promote VDF. In mature IHCs from mice expressing the dfcr harmonin mutant, Cav1.3 VDF was less than in control IHCs. This difference was not observed between control and dfcr IHCs prior to hearing onset. Membrane capacitance recordings from dfcr IHCs revealed a role for harmonin in synchronous exocytosis and in increasing the efficiency of Ca(2+) influx for triggering exocytosis. Collectively, our results indicate a multifaceted presynaptic role of harmonin in IHCs in regulating Cav1.3 Ca(2+) channels and exocytosis.

    Glutamate transporters EAAT4 and EAAT5 are expressed in vestibular hair cells and calyx endings

    - rcalinjageman

    Dalet A, Bonsacquet J, Gaboyard-Niay S, Calin-Jageman I, Chidavaenzi RL, Venteo S, Desmadryl G, Goldberg JM, Lysakowski A, Chabbert C

    PLoS ONE 2012;7(9):e46261

    PMID: 23049999

    Abstract

    Glutamate is the neurotransmitter released from hair cells. Its clearance from the synaptic cleft can shape neurotransmission and prevent excitotoxicity. This may be particularly important in the inner ear and in other sensory organs where there is a continually high rate of neurotransmitter release. In the case of most cochlear and type II vestibular hair cells, clearance involves the diffusion of glutamate to supporting cells, where it is taken up by EAAT1 (GLAST), a glutamate transporter. A similar mechanism cannot work in vestibular type I hair cells as the presence of calyx endings separates supporting cells from hair-cell synapses. Because of this arrangement, it has been conjectured that a glutamate transporter must be present in the type I hair cell, the calyx ending, or both. Using whole-cell patch-clamp recordings, we demonstrate that a glutamate-activated anion current, attributable to a high-affinity glutamate transporter and blocked by DL-TBOA, is expressed in type I, but not in type II hair cells. Molecular investigations reveal that EAAT4 and EAAT5, two glutamate transporters that could underlie the anion current, are expressed in both type I and type II hair cells and in calyx endings. EAAT4 has been thought to be expressed almost exclusively in the cerebellum and EAAT5 in the retina. Our results show that these two transporters have a wider distribution in mice. This is the first demonstration of the presence of transporters in hair cells and provides one of the few examples of EAATs in presynaptic elements.