The Role of Dopamine Receptors in Motivated Behavior

Christoph’s Kellendonk’s lab at Columbia University is interested in understanding the biology that underlies behavior changes associated with Schizophrenia. By using optogenetics, chemo genetics, viral methods and electrophysiology in mouse models they seek to understand how circuit function regulates behavior and ultimately translate their findings to guide further studies in patients with Schizophrenia and identify new treatment targets for enhancing cognition and motivation in this patient population.

In a recent study they explored the cellular and electrophysiological mechanisms through which dopamine D2 receptors (D2R’s) in the nucleus accumbens regulate motivation. Using AAV’s and a transgenic mouse line, they selectively overexpressed D2R’s in the striatal output pathway of the nucleus accumbens that endogenously express D2R’s, the indirect pathway. They then assessed the willingness of mice to work for food using a progressive ratio task, where the number of lever presses needed to receive a reward increased with each successive reward. They found that selective upregulation of D2R’s in the indirect pathway of the nucleus accumbens enhances the willingness to work for food (Figure 1).

Figure 1


Furthermore, using slice electrophysiology, they found that the increase in motivation was associated with decreased inhibitory transmission from dopamine 2 medium spiny neurons (D2 MSN) and in blunted output from the indirect pathway of the nucleus accumbens to the ventral pallidum. Their finding suggest that upregulation of D2R’s in medium spiny neurons of the nucleus accumbens disinhibit the ventral pallidum to regulate motivated behavior.

The complete study can be read here:

Kellendonk lab website:

To learn more about Christoph Kellendonk’s work join us at 4:00pm, Tuesday 01/21/2019 at Marilyn G. Farquhar Seminar Room.

Maribel Patiño is a first year PhD student in Dr. Ed Callway’s lab.



What makes a mouse vulnerable to cocaine?

Veronica Alvarez’s lab at NIAAA studies the cellular mechanisms that control drug seeking behavior. VAlvarezIn one study recently published in Neuropsychopharmacology, Dobbs, Alvarez and colleagues investigate the role of dopamine type 2 receptors (D2R) in striatum.

Cocaine use has significant costs on society. While it has previously been established that cocaine is a dopamine transporter blocker, what makes some people more vulnerable to cocaine abuse is still unknown.

Vulnerability for cocaine abuse in humans is associated with low D2 receptor availability but the mechanisms driving this vulnerability are unknown. Previously the Alvarez lab found that reduction of D2R on indirect pathway medium spiny neurons made mice acquire preference for a location where they were administered cocaine, and accelerated the expression of locomotor sensitization from repeated cocaine exposure.  

In this study, Alvarez and colleagues knocked down D2 receptors in the striatum which subsequently caused changes to the mechanism of D1 receptors and the structure of striatopallidal projections. Ultimately, they found that downregulation of D2R lead to D1R hypersensitivity that controlled the cocaine locomotor sensitization. But, when they tested out the likelihood of seeking and taking cocaine in D2R- knockout mice, there were no differences in acquisition, seeking, or taking (Figure 1).

alvarez figure

You can read the full paper here

To learn more about Dr. Alvarez’s exciting work on dopamine in the striatum, please join us this Tuesday, 1/15/18, at 4pm in the Marilyn G. Farquhar Seminar room in the Center for Neural Circuits and Behavior. The title of her talk is “Mechanisms for dopamine release in the striatum and the actions of drugs of abuse”.


Emily Baltz is a first-year PhD student interested in how internal states control behavior. She is currently rotating in Jing Wang‘s lab. You can find her on Twitter, LinkedIn, and Google Scholar.


What facilitates the extreme maternal behaviors in octopuses?

The octopus, a highly intelligent invertebrate with a uniquely complex central nervous system, has caught the attention of Dr. Clifton Ragsdale for investigation of cephalopod genomics. As a professor under the Department of Neurobiology at The University of Chicago, Dr. Ragsdale and his lab are applying modern cellular and molecular techniques to studying octopus neurobiology. In 2015, they published findings with collaborators from Rokhsar’s group at UC Berkeley on the genome of the California two-spot octopus, Octopus bimaculoides. Since then, the Ragsdale lab has been investigating comparative cephalopod genomics, octopus arm regeneration, octopus embryogenesis, and neocortex development.

A recent paper published in August of 2018 in the Journal of Experimental Biology revealed multiple signaling pathways in the octopus optic gland that facilitate maternal behaviors and death. A female octopus that has mated will undergo extreme maternal care behavior of starvation and death after a single reproductive cycle. The optic gland is analogous to the vertebrate pituitary gland, and when removed, the octopus reverses the brooding behavior and abandons her clutch to resume feeding and mating. The molecular features underlying this optic gland signaling were explored by Ragsdale with transcriptome and behavioral analyses.

They examined four behavioral stages in the adult life of the sexually mature female octopus. The first being non-mated females that are active predators outside their dens. Next were mated females that actively guarded their dens and egg clutches but exhibited reduced predatory behavior. Following that is the fasting stage, and then the final stage of rapid physiological and behavioral decline with excessive self-grooming and self-cannibalization resulting in death.

Ragsdale used RSEM and edgeR analysis methods to identify nearly 1200 transcripts that were differentially expressed. 25 subclusters were determined, of which 22 were excluded due to sample scarcity or lack of monotonicity (either entirely increasing or decreasing trends). The remaining three subclusters contained 343 genes of interest with differential expression across the four behavioral stages. The first cluster included transcripts for neural signaling and neurotransmitter receptors that increased after mating and remained elevated through brooding stages (Fig. 5A-C). The transition from feeding to fasting stages revealed increased expression of insulin signaling genes (Fig. 5D), which promote cell survival under starvation conditions. Genes related to feeding circuit-related neuropeptides in the third cluster decreased expression between unmated and mated stages (Fig. 5E), which may regulate energy expenditure or the drive to hunt for food. To assess whether these gene expression changes were localized in the optic gland or globally present in other tissues, Ragsdale compared the transcriptomes of the optic gland to those of tissues from different parts of the octopus arm using BLASTP and TBLASTN. They found these molecular markers of senescence are only present in the optic glands and not in other tissues.


Figure 5. Expression profiles of genes relevant to optic gland signaling.

The Ragsdale lab has uncovered multiple signaling systems in the octopus optic glands. Upregulations and downregulations of catecholamine, steroid, insulin, and feeding peptide pathways tightly regulate maternal behavioral feeding behaviors. These functions parallel those of the anterior pituitary gland and adrenal glands in vertebrates, thus prompting further investigation of optic gland targets. Ragsdale and his team have demonstrated the significant organization and function of the optic gland in octopus physiology for maternal behavior.

To hear more about the work being done in Dr. Ragsdale’s lab, please join us at 4 PM, Tuesday 1/8/2019 at the Marilyn G. Farquhar Seminar room in CNCB.

To read the paper, visit:

To learn more about the octopus genome research project in the Ragsdale lab, check out and for their 2015 Nature paper.

Vivian Ko is a first-year PhD student.  


Understanding the Biophysics of Spatial Navigation and Memory


Dr. Lisa Giocomo is an Assistant Professor of Neurobiology at Stanford University. Her lab is primarily interested in understanding how ion channels control neural coding and behavior. The system her lab uses to investigate this question is studying spatial coding by non-sensory medial entorhinal cortex neurons, and the discovery of an ion channel that directly maps to specific features of functionally-defined medial entorhinal neurons. Her previous work demonstrated that spatially selective medial entorhinal neurons use ion channel kinetics for spatial scaling, giving her lab unprecedented access to a system ideal for studying the connections between ion channels, coding and behavior. In particular, the Giocomo lab uses electrophysiology, behavior, imaging, gene manipulations, optogenetics, and computational modeling to study how single-cell biophysics and network dynamics interact to mediate spatial memory and navigation.

In August of this year, her lab published a paper in Nature Neuroscience showing a theoretical framework for understanding how landmark and self-motion cues combine during navigation to create spatial representations and guide behavior. The neurons that contribute to encoding position in space in the medial entorhinal cortex (MEC) include grid cells, head direction cells, border cells, and speed cells. However, the principles by which these MEC cells integrate self-motion versus landmark cues are not well understood. Giocomo examined how mouse behavior and MEC cell classes integrate self-motion with landmark cues by analyzing the neural activity and behavior of mice while they explored virtual reality environments.

Giocomo found principled regimes under which behaviorally measured position estimates and MEC codes differentially weight the influence of visual landmark and self-motion cues. Gain was manipulated by altering the transformation between the rotation of the running ball and translation of the VR track, with gain decreasing or increasing the visual scene translation. These manipulations placed visual and locomotor cues in conflict, depicted in Fig 2. Through structural analysis of gain change responses, she found that conflicts between locomotion and visual cues caused grid cells to remap in an asymmetric manner, with gain increases causing phase shifts and gain decreases causing grid scale changes. This finding that grid cells responded differently to gain increases and decreases, with an occasional loss of fields, and remapping and rescaling in gain decreases, led them to wonder about the mechanism driving this.

Screen Shot 2018-12-02 at 6.51.22 PM.png

Figure 2

She then developed a coupled-oscillator attractor model that explained how grid responses to gain manipulations could come from competition between conflicting self-motion and landmark cues. The model successfully predicted grid responses to an intermediate gain change. Finally, she used a path integration task to demonstrate behavioral asymmetry in the weighting of visual versus locomotor cues that matched grid and speed responses. These findings provide an important framework for understanding the dynamics of cue combination in MEC neural codes and navigational behavior.

You can read the complete paper here:

To learn more about Dr. Giocomo’s exciting work, please join us this Tuesday, 12/4/18, at 4pm in the Marilyn G. Farquhar Seminar room in CNCB.

Desi Chu is a first-year Neuroscience PhD student currently working in Dr. Sung Han’s lab.

Theoretical Approaches in Nervous System Processing

a081460-1-e1429226047518 (1)Adrienne Fairhall PhD., is a Professor in the Department of Physiology and Biophysics at the University of Washington. The Fairhall lab develops theoretical approaches to understanding processing in nervous systems, from single neurons to foraging mosquitos to navigating primates. Using mathematics and statistical methods, the Fairhall lab studies the relationship between neuronal circuitry and functional algorithms of computation.

One of the challenges the Fairhall lab is undertaking is understanding adaptive coding in context sensitive neural systems. As the encoding of a stimulus depends on the temporal, spatial, and semantic context in which it is embedded, many typical features of a system are adjusted according to the signal-to-noise ratio, with this coding range typically adapting to the range of stimuli. Adding to the complexity is the fact that different processes encode information at different timescales. Fast adaptive processes can normalize the response functions to the scale of the stimulus, but there are also slower processes that depend on the history of temporal changes in stimulus statistics.

Recently, the Fairhall lab has come out with a study that advances our understanding of both of these topics. Published in PLOS computational biology this year, they studied the history dependence in insect flight decisions during odor tracking. As many important behaviors require animals to make extended sequences of decisions in response to complex stimuli, they sought to model these sequences in fruit flies and mosquitos by tracking their response to odor plumes. By examining videos and tracking the 3D trajectory of these insects flying in a wind tunnel containing an attractive odor, they were able to ask what features of the encounters with an odor plume could influence flight decisions. Interestingly, although the average response was a reflexive upwind turn towards the stimulus, they found that the strength of the response was modulated by the history of prior plume encounters.


Fig 3. History dependence of crossing-triggered turns in data and models


This history dependence was captured in a model where a simulated tracking agent maximizes information about the position of the plume source. These results suggest that real odor tracking could involve short-term memory processes that occur over multi-encounter timescales that accumulate information about the source location. They did not report, unfortunately, on how to prevent those pesky mosquitos from learning which part of your arm to land on for a bite!

To hear more about the work being done in Dr. Fairhall’s lab be sure to join us at 4 PM, Tuesday 11/27/2018 at the Marilyn G. Farquhar Seminar room in CNCB.

To read the paper, visit:

To learn more about the projects ongoing in the Fairhall lab, swing by:


Joseph Herdy is a first-year PhD student working in Dr. Saket Navlakha laboratory.







Feedback Circuits Regulate Skilled Reaching

jc2Despite the powerful computations our brains can perform and the vivid abstractions of reality it allows us to produce in our minds, our only way of affecting any change in the world around us is through our motor system: the contracting and relaxing of our muscles. One of the most impressive evolutionary accomplishments of humans and other mammals is our ability to very precisely control these movements to achieve fine motor tasks. For example, reaching out a hand, grasping a glass of water, and bringing it to one’s mouth for a drink. While this may require almost no conscious effort, it is a nontrivial feat, requiring the brain to coordinate the movement of many muscles in the hand and arm, and integrate this with tactile and visual information from other bodily systems.

One major theory of how the nervous system accomplishes this smooth and precise pattern of movement is by utilizing internal copy pathways, which was an interest of Dr. Eiman Azim’s while at Columbia University. In this model, descending motor neurons send projections to the cerebellum and provide it with the same set of motor information that is being sent to muscles. This allows the cerebellum to predict whether or not a given set of motor commands will be successful before the action is carried out, and provide immediate corrective feedback to ensure successful movement. If the brain instead were to react solely on sensory feedback provided by vision and touch, information would have to travel all the way from the extremities back to the brain, producing a significant time delay, and forcing the cerebellum to compensate using information that is no longer current.

One good candidate neuronal population for providing an internal copy the cerebellum is the cervical propriospinal neurons (PNs). These neurons have bifurcated axons that extend one branch to the lateral reticular nucleus (LRN), a pre-cerebellar relay, and another branch to the cervical motor neurons that control forelimb movement. In his study, published in Nature in 2014, Dr. Azim identified a major population of the PNs that belong to the V2a interneuron class, which are known to be highly involved in motor control.

To determine what role PNs play in skilled movement, Dr. Azim created a behavioral assay in which mice are presented with a food pellet and tasked with reaching their paw through a small window to retrieve it. Paw position is recorded throughout the test, and is divided into three distinct phases: reaching through the window, the anticipatory phase immediately before grasping, and the grasping phase. Statistics such as the paw position in 3D space, distance to the pellet, and paw velocity are recorded by two nearby cameras.

jcpic1 Figure 2: Reaching kinematics

Dr. Azim first used this assay to determine that specific ablation of PNs by diphtheria toxin resulted in mice moving their paws more slowly, and more frequently changing direction, but only when the animal was reaching out its paw to retrieve the pellet, rather than in the grasping or anticipatory phase. This established an initial role for these neurons in regulating fine motor control. To tease apart what role specifically the PN projection to the cerebellum might play, Dr. Azim optogenetically stimulated PN axons present in the LRN, so that all downstream cerebellar targets would be activated but the direct connections to the motor neurons would be unaffected. Stimulating this region during the pellet retrieval task resulted in a similar perturbation of the movement, with a large increase in the number of reversals in paw direction. This indicates that information sent by PNs through the cerebellar pathway plays a role in regulating forelimb movement, in addition to the connections made directly with motor neurons. Finally, Dr. Azim performed a complementary experiment and severed the connections between the LRN and the cerebellum, and saw that this increased the response latency of motor neurons by 1 to 3 ms as measured by motor neuron field potential response, demonstrating that the cerebellar circuit plays a role in producing rapid compensatory changes in motor output using information from PNs.

Overall, Dr. Azim’s study provided evidence for an internal copy provided by PNs to the cerebellum via the LRN, which in turn provides rapid adjustments to ensure the success of the movement. The finding that ablation of these neurons affects only the reaching phase of pellet retrieval and does not affect grasping supports an emerging idea that different sets of interneurons are responsible for specific sets of movements like reaching or grasping, and that these sets of neurons are recruited modularly in order to perform highly complex motor tasks.

To hear more about the work being done in Dr. Eiman Azim’s lab, please join us at 4:00pm, Tuesday 11/20/2018 at Marilyn G. Farquhar Seminar Room.

To read the paper, visit:

To learn more about the Azim lab, visit:

Understanding Stress Granules in Neurodegenerative Disease

YeoGene-400x400Dr. Gene Yeo, Ph.D., MBA, is an expert in the areas of RNA, genomics, computational biology, and neurodegenerative diseases. Dr. Yeo was the first Junior Fellow at the Crick-Jacobs Center for Theoretical and Computational Biology at the Salk Institute in 2005 and was soon appointed assistant professor of Cellular and Molecular Medicine at UCSD. Dr. Yeo, now a full professor, has been very successful during his time in academia. Of note, his lab was the first to demonstrate the targeting of RNA using CRISPR/Cas9 and furthermore, Dr. Yeo has received the inaugural Early Career Award by the international RNA Society. In addition, Dr. Yeo serves on the Scientific Advisory boards of several biotech companies, is a bioinformatics and business consultant for biotech and pharmaceutical companies, and has co-founded several start-ups.

A primary interest of the Yeo lab is to understand how RNA expression is regulated post-transcriptionally in relation to maintaining cellular homeostasis during development, aging, and disease. To study this, the Yeo lab employs computational and experiment techniques, including genomic data analysis, molecular biology, biochemistry, high-throughput sequencing, and imaging. In their recent study published in Cell, titled “Context-Dependent and Disease-Specific Diversity in Protein Interactions within Stress Granules”, the Yeo lab elucidates the composition and behavior of stress granules during normal and disease states.

Stress granules (SGs) are ribonucleoprotein (RNP) aggregates that transiently assemble in the cytosol upon cellular stress and have been implicated in neurodegenerative diseases as represented in figure 1 below.


Figure 1: Schematic of stress granule formation

To understand the proteome of SGs, the Yeo lab first identified known and previously unknown SG proteins using ascorbate peroxidase (APEX) proximity labeling in combination with mass spectrometry and immunofluorescence. Using these methods, the Yeo lab discovered about 150 previously unknown human SG-related proteins. They next compared the composition of SGs in different cell types and under different cellular stressors and found cell-type specific and context-dependent SG proteins. The Yeo lab then wanted to compare healthy and amyotrophic lateral sclerosis (ALS) SG composition and location in patient specific iPSC-derived motor neurons, the cell type most affected in ALS, and saw altered composition and altered distribution of ALS SGs. Furthermore, they were able to show that when altering these SG proteins, they can modify protein toxicity in Drosophila ALS disease models. A summary schematic of their findings is below in figure 2. These results show that SG homeostasis is altered in ALS and that targeting the proteins involved in SG function may be a therapeutic option for treating ALS. This implicates the importance of understanding SG formation and function in neurodegenerative diseases, especially in diseases where protein aggregation is prominent.


Figure 2: Schematic summary of findings from studying SGs

Please join us Tuesday October 30th at 4pm in the Marilyn G. Farquhar Seminar Room in CNCB to hear Dr. Gene Yeo talk more about his research!


To learn more about stress granules, here is a nice review:

To learn more about the Yeo lab, here is the lab website: 

Figure 1 

Figure 2


Sammi Sison is a first-year neuroscience graduate student, currently working in Dr. Kristin Baldwin’s lab.

Constructing the transcriptomic definition of CNS cell-types


The human central nervous system is a complex entity composed of over 170 billion cells. Deconstructing its complexity requires methods to define and characterize specific cellular populations. Michael Oldham, PhD, neuroscientist and Assistant Professor of Neurological Surgery at UCSF, believes gene expression lies at the root of cellular identity. His team dives into the transcriptome of the central nervous system to find distinct, reproducible signatures of cell types in silico.

The lab’s most recent publication 2018 in Nature Neuroscience, “Variation among intact tissue samples reveals the core transcriptional features of human CNS cell classes,” takes a top-down approach to identifying core signatures of cellular identity in an astonishing 7,221 human CNS samples!

To illustrate their rationale (Fig 1a-b), they first created “synthetic tissue samples.” These samples were composed from single-cell RNA seq data and designed to mimic the cellular heterogeneity found in human CNS samples. The data from each synthetic tissue sample was run through an unsupervised gene coexpression analysis. From this analysis, Oldham’s group (1) identified gene coexpression modules ( and (2) identified modules with the highest abundance of previously published markers of astrocytes, oligodendrocytes, microglia, or neurons (“cell-class modules”).

Fig 1

Fig. 1: Rationale and workflow.

They performed this same unsupervised gene coexpression analysis on data from 62 publicly-available human CNS gene expression data sets representing thousands of tissue samples and billions of cells. Their goal was to identify cell-class modules and use them to define a cell-type specific consensus transcriptomic profile (Fig 1c-g).

In addition to being used as part of a categorizing definition, cell-class modules were also used to retrace cellular composition of the original, intact tissue sample. This is very exciting as in the experimental process of extracting RNA from bulk postmortem CNS tissue, no information about cellular identity is retained. There is no trace to show which transcripts belonged to which cells.

The solution to this problem, the Oldham group posited, is a simple idea: “variation in cellular composition among intact tissue samples will drive covariation of transcripts that are uniquely or predominantly expressed in specific kinds of cells.” Then mathematically, the first principal component (‘module eigengen’ in Fig 1)  of a cell-class module is the relative proportion of the cell class in the sample.

Let’s break down this idea. Cell-class modules should contain transcripts that are (1) highly specific–unique to a specific cell type and (2) highly sensitive–expressed consistently throughout those cells. These genes have a high “expression fidelity.” Mathematically, this is quantified as KME (the cell-class module membership in Fig 1). As they mark cellular identity, expression patterns for these cell-class modules should be predictable and consistent for a given cell-type. Therefore, the majority of variability in the expression of cell-type specific, high fidelity genes across samples should be due to the proportion of cell-type specific cells within a given sample. A sample with 80% neurons will show increased expression of high-fidelity neuronal genes versus a sample with 40% neurons.

They tested this hypothesis using their synthetic tissue samples (as they have known cellular compositions). They found that their module produced accurate predictions of cellular abundance (Supp Fig 1). Truly an exciting finding, as they show a means to define cell-specific transcriptomic signatures WITHOUT the need for physically isolating cellular subpopulations.

And all that just in Figure 1!

Using this workflow, Oldham’s group:

  1. Validated many canonical markers as high fidelity genes for their predicted cell class (Fig 2)
  2. Examined in detail the top 50 expression fidelity genes for each major CNS cell class including expression levels/fidelity, loss-of-function intolerance, PubMed citations, cellular localization, and protein-protein interactions (See Fig 3 below)
  3. Examined less abundant (or more specific) cell classes (such as cholinergic neurons, midbrain dopaminergic neurons, endothelial, ependymal, choroid plexus, and more) and validated many canonical cell markers (Fig 4)
  4. Found differential expression of genes associated with neural disease in different cell populations (e.g., genes associated with most neurodegenerative disorders are enriched in microglia and astrocytes) (Fig 6)
  5. Identified differences in expression fidelity for cell classes in different CNS regions (regional differences greatest for neurons > microglia and astrocytes > oligodendrocytes) (Fig 7)
  6. Identified species-specific transcriptional differences in cell classes (including identifying a putative candidate gene driving astrocyte size differences in human vs. mouse CNS) (Fig 8).

Fig 3

Fig. 3a-d: The core transcriptional identities of human astrocytes, oligodendrocytes, microglia, and neurons include known and novel biomarkers.

Quite a feat!

To learn more about the work from Dr. Michael Oldham’s lab, please join us at 4:00pm, Tuesday 10/22/2018 at Marilyn G. Farquhar Seminar Room.

To read the paper:

To read more about the Oldman group:

Isabel Costantino is a first-year PhD student working in Dr. Jerold Chun’s laboratory.


Piezos: Mechanotransduction in health and disease

I don’t suppose you have given pause recently to ponder the biophysical marvel that is the red blood cell (RBC). And, well, who can blame you really? But then I am, however, confronted with the unhappy task of arguing that you should. This is because the RBC has that annoying habit of surfacing in the unlikeliest of places and then, once noticed, is weirdly found to have been hiding some impressive and seemingly outsized role. Orchestrated, as things forever seem to be, by a cytoskeletal scaffold, the biconcavity of the RBC is, structurally, perhaps its most prominent feature and, functionally, features prominently. It is the RBC’s biconcavity that enables it to maneuver through — or rather be propulsed through — the birth canal-like passages of the vasculature, and it is the RBC’s biconcavity that grants flexibility to volumetrically respond to the osmotic changes happening outside its walls. Much of this volumetric regulation, as it happens, is tuned by something called a piezo.

It is Ardem Patapoutian’s crew at Scripps Research that have been the primary movers pushing the field of piezos. Piezos (which, if you care, our good friend Webster claims is etymologically derived from the Greek piezein, “to press”) are non-selective, mechanosensitive cation channels, meaning they transform the mechanical forces of the outside sensory world into actionable biological signals. Two of them, helpfully christened Piezo1 and Piezo2, have been identified so far, but likelihood suggests more of them remain to be discovered. While Piezo1 enjoys greater expression in non-neuronal tissues (e.g., endothelial, smooth muscle, and red blood cells), Piezo2 is more prominently expressed in sensory neurons and facilitates, for example, proprioception and the detection of light touch. In addition to sensory neural structures, Piezo2 is also expressed in other sites dependent upon mechanosensation (e.g., respiratory structures).

Figure 1

Taking the latter first, Piezo2 has been identified as a structure critical for the mechanotransduction of light touch and proprioceptive information and localizes to nerve terminals, those sites where one could perhaps reasonably expect mechanotransduction to occur. Using green fluorescent Piezo2-GFP mice, fluorescence in skin was observed to concentrate in lanceolate endings and around hair follicles, in Merkel cells, and in Meissner’s corpuscles, all of which are sites and cells involved with touch sensation. Subsequent employment of an ablation-at-will methodology utilized AvCreERT2 mice, mice that are embedded, if you will, with tamoxifen-inducible Cre recombinase in sensory neurons and epidermal Merkel cells that have an Advillin promoter. Mating these AvCreERT2 mice with the Ai9 tdTomato reporter line revealed tdTomato expression in 87% of dorsal root ganglion neurons (DRGs) and 82% co-expression of Piezo2 and tdTomato positivity (Figure 1). Because it has previously been argued elsewhere that silencing Piezo2 in DRGs yields decreased mechanically activated current, Patapoutian’s crew poked cultured DRGs from Piezo2 knockout mice with glass probes to confirm that Piezo2 knockout DRGs do indeed feature fewer rapidly adapting mechanically activated currents. In fact, the DRGs do not even appear to respond more slowly but rather appear to become altogether unresponsive (Figure 2). Upon finding deficient mechanically activated current in DRGs, one might reasonably propose a concordant deficiency in skin sensory fibers, a proposal the group then assessed using an ex vivo skin nerve preparation — using samples drawn, again, from wild-type and Piezo2 knockout mice — and observed, in the knockouts, loss of

Figure 2

mechanosensitivity in 50% of the Aβ-fibers without significant loss in either Aδ-fibers or C-fibers. It is, to say the least, an unfortunate era in which to be a mouse.

The finale of at least this assessment of Piezo2 was a series of behavioral tests, conducted in our by now quite tired and savaged Piezo2 knockout mice. Application of von Frey filaments with varying force to the hind paws of these mice indicated severe deficiency at detecting forces of lower magnitude. Interestingly, however, the ability to detect forces of greater magnitude was retained, suggesting Piezo2 may function within a constricted range of mechanical stimulation. In a separate assay, the so-called cotton swab assay, a cotton swab was gingerly drawn under the mouse’s paws; apparently the Piezo2 knockouts, in contrast to wild-type, couldn’t be bothered to withdraw their paws from its softness. Anyway, to ensure these findings were not merely the byproduct of globally useless sensory reception, application to the Piezo2 knockouts of various forms of thermal stimuli and particularly irritating mechanical forces revealed no differences in response from controls. To thus finish our discussion of Piezo2 perhaps overly briefly, while the argument Patapoutian’s lab has assembled fairly robustly supports the role of Piezo2 for at least light touch mechanotransduction, the equivalency of response observed upon mechanostimulation at higher magnitude would appear to offer an interesting opportunity for one to further define the spectrum of mechanosensation.

Figure 3

To then consider the former second, we turn to Piezo1, the recent structural and functional analyses of which represent impressive steps forward in the study of mechanically activated channels. Using methodology that can perhaps only be described as the very cutting-edge of structural biology, the full structure of the Piezo1 channel was defined in whole rather recently using high-resolution single particle cryo-EM. While the pictorial depiction of Piezo1’s structure is, quite simply, a beauty, we are best served by considering Piezo1’s activation, a feat that involves finely tuned movements of an inner helix, outer helix, C-terminal domain, anchor domain, and latch and beam domains. I know, I know, but stay with me here. The anchor domain in particular is thought to factor prominently in channel gating, most likely via an electrostatic interaction between the E2133 residue and the R2482 residue of the inner helix; these things apparently are somewhat in the vicinity of one another (Figure 3). While this precision tuning may represent nature at its finest, any disruption in the force, so to speak, melts down the whole mechanism. Indeed, the R2482H mutation in human Piezo1 has not just slower inactivation but also has been associated with something called dehydrated hereditary stomatocytosis, a disease of — you didn’t think I forgot about them, did you? — RBCs.

Let us then return, you and I, to the RBC. And while up to this point we have considered piezos in health, here let us consider them, or at least Piezo1, in disease. Also known as hereditary xerocytosis, dehydrated hereditary stomatocytosis is a blood disorder in which RBCs are said to be dehydrated and feature decreased osmotic fragility — a disruption in that critical biconcavity. Many of the mutations in Piezo1, including R2482H, result in slower inactivation and thus increased passage of ions. Consequently considered gain-of-function mutations, these are the mutations that cause dehydrated RBCs. Dehydrated RBCs are in some fashion associated with diminished infectivity by Plasmodium, the agent that causes malaria. Plasmodium is additionally understood to effect a selectivity pressure on the genome. Patapoutian’s group thus assessed the relationship between Piezo1, dehydrated RBCs, and Plasmodium susceptibility first by infecting gain-of-function Piezo1 mice with a GFP-expressing line of a rodent Plasmodium species notably notorious for causing cerebral malaria. In these gain-of-function Piezo1 mutant mice, evaluation of GFP-positive RBCs by flow cytometry showed decreased parasitemia and increased survival. To evaluate for the blood-brain barrier breakdown commonplace in cerebral malaria, they injected Evans blue dye into both wild-type and Piezo1 gain-of-function mice infected with Plasmodium. Here it is the wild-type mice for whom we’re to become soppy-eyed for they all exhibited the blue dye leakage consistent with blood-brain barrier dysfunction. But the Piezo1 mutated mice, on the other hand, exhibited no dye leakage: they were protected from cerebral malaria! The question, of course, is whether any of this has any meaning for humans.

Figure 4

Echinocytes and stomatocytes are denoted by white and yellow arrowheads, respectively.

Figure 5

In pursuit of an answer, Patapoutian’s group assessed whether African populations (whose individuals are expected to more frequently be from areas with endemic malaria) have an increased frequency of gain-of-function Piezo1 mutations. Indeed, one mutation, E756del, was found to have an allelic frequency of 18% and functionally observed to have the slower inactivation time similar to R2456H, the allelic equivalent of which was used to generate the gain-of-function Piezo1 mutant mice. Further characterization suggested this allele was derived (i.e., not ancestral) and under positive selection, almost certainly a selection pressure resulting from its protective effects against Plasmodium. To confirm RBC morphological and infectivity results that had heretofore only been observed in mice, the group lastly evaluated RBC dehydration and infectivity by Plasmodium falciparum in African American E756del carriers. (It is perhaps of value here to recall that P. falciparum is the most grievous and hideous of the whole Plasmodium scourge.) At any rate, scanning electron microscopy of RBCs showed the echinocytes and stomatocytes expected of hereditary xerocytosis (Figure 4), and osmotic fragility testing showed the RBCs of E756del donors to be dehydrated. In vitro infection of RBCs from controls and E756del carriers with P. falciparum revealed decreased parasitemia for carriers (Figure 5). Although a precise mechanism for such a chain of events may yet remain to be elucidated, what we see is that gain-of-function genetic alteration of the Piezo1 mechanosensitive channel confers protection for the most at-risk populations against the most severe malarial parasite, Plasmodium falciparum, by dehydrating the RBC. Seeing as I have by now probably exhausted your attention supply, allow me to rather abruptly conclude by saying that I think some commendation is in order for these individuals — these populations — that have been able to so successfully mooch off that selfish gene.

In order of appearance:

  • Murthy, S. E. et al., Nature Reviews Molecular Cell Biology (2017).
  • Ranade, S. S. et al. Nature (2014).
  • Saotome, K. et al. Nature (2018).
  • Ma, S. et al. Cell (2018).

Jason Adams is a first-year Ph.D. student in the lab of Alysson Muotri.

Understanding Neuronal Cell-Type Diversification From the Perspective of a Worm

From the outside looking in, the brain looks rather homogenous. It has folds and creases, some protruding lobes, but really only a handful of features that make it unique upon gross inspection. Taking a closer look (depending on the species) reveals hundreds to thousands, or even one hundred billion neurons that help make up the brain. Taking an even deeper dive, unfolds a richness of cell types that gives the brain an immense amount of diversity. The mechanisms governing cell-type diversity in the brain is poorly understood, but incredibly important. Understanding the genetic programs that make neurons different may help elucidate what went wrong when neurons (and brain structures) become pathologic.

Spearheading the research that investigates the molecular mechanisms governing neuronal cell-type diversity is Oliver Hobert. Professor Hobert has appointments in biological sciences and molecular biophysics at Columbia University, and has the privilege of being a Howard Hughes Medical Institute investigator. Dr. Hobert’s lab uses Caenorhabditis elegans (C. elegans) to take a “bottom-up” approach to elucidate the genetic programs responsible for cell type diversification in the brain. The “Bottom-up” approach is an attempt to define sequences of DNA (AKA the “gene battery”) that specify anatomical and functional properties of cells, and then dissects the regulatory elements governing the transcription of neighboring genes (AKA “cis-regulatory elements”).  Ultimately, C. elegans provides a genetically tractable model with well described neuroanatomy to test hypotheses regarding the development of different neuronal cell types. Hopefully, the molecular and analytical tools used in C. elegans, can be used to investigate these developmental mechanisms in other species.

Recently, the Hobert lab published a paper in Neuron titled: “Diversification of C. elegans Motor Neuron Identity via Selective Effector Gene Repressor”, which elucidates the mechanisms governing C. elegans motor neuron diversification. In the paper, they point out that C. elegans motor neurons are cholinergic and GABAergic, but can be further subdivided. For example, the cholinergic neurons can be divided into six classes based on their features (Fig 1a). In the end, they sought to uncover the mechanisms governing cholinergic motor neurons (MNs) diversification in the ventral nerve cord (VNC) of C. elegans.

Previous studies showed that 5/6 classes of MNs in the VNC shared the unc-3 transcription factor (Fig 1b). Additional studies showed that the loss of or misexpression of unc-3 lead to the loss of specific MN subtypes. Therefore, the unc-3 transcription factor was not only shared among 5/6 MNs, but also specified MN subtypes, which is a little paradoxical. How can a shared transcription factor also specify MN subtype? The Hobert lab sought to answer this question by testing two models. They hypothesized that either the unc-3 transcription factor requires class specific co-factors to activate class-specific features (co-activator model upper panels of Fig 1d) or unc-3 is capable of activating all features, including class-specific features, but is prevented from doing so via class-specific repressor proteins (repressor model lower panels of Fig 1d). If the activator model were true, loss of unc-3 would lead to loss of class-specific features. If the repressor model were true, loss of unc-3 would lead to ectopic expression of class-specific features.

To test the two models, they screened C. elegans mutants to identify alleles in which MN class-specific effector genes are either misexpressed (supporting repressor model) or lost in specific MN classes (supporting the co-activator model). An example of how the data was collected and analyzed is shown in figure 2. Using the genetic screen, the ot721 allele was found and unc-129 (an effector gene) was ectopically expressed. Figure 2a shows the expression pattern of unc-129 with GFP in both the wild-type and mutant ot721 C. elegans. In the mutant ot721 phenotype there is green protein found in VA and VB MNs, which indicates ectopic expression. Expression patterns for the mutants are shown in fig 2b. Further analysis showed that the mutant ot721 allele corresponded to a previously undescribed zinc finger transcription factor encoding gene bnc-1 (fig 2c). When bnc-1 is expressed in the mutant ot721 C. elegans, the phenotype was rescued.

In the end, they found that MN diversification was a result of class-specific repressor proteins that prevents unc-3 from activating subsets of class-specific effector genes. Furthermore, all the reported repressors are phylogenetically conserved. Therefore, the proposed mechanism for MN diversification in C. elegans may constitute a broadly applicable principle of neuronal identity diversification across species.

To learn more about the tools used to investigate the genetic programs that lead to neuronal diversification join Dr. Hobert and the rest of UCSD neurograduate program at 4pm Tuesday (05/29/18) at the CNCB Seminar Room at UCSD.


figure 1


figure 2_finalElischa Sanders is a first-year Neuroscience Ph.D. student, currently working in Eiman Azim’s lab