Faculty Bibliography

Regulation of mRNA translation is a major modulator of gene expression, allowing cells to fine tune protein levels during growth and differentiation and in response to physiological signals and environmental changes. Mass-spectrometry and RNA-sequencing methods now enable global profiling of the translatome, but these still involve significant analytical and economical limitations. We developed a novel system-wide proteomic approach for direct monitoring of translation, termed PUromycin-associated Nascent CHain Proteomics (PUNCH-P), which is based on the recovery of ribosome-nascent chain complexes from cells or tissues followed by incorporation of biotinylated puromycin into newly-synthesized proteins. Biotinylated proteins are then purified by streptavidin and analyzed by mass-spectrometry. Here we present an overview of PUNCH-P, describe other methodologies for global translatome profiling (pSILAC, BONCAT, TRAP/Ribo-tag, Ribo-seq) and provide conceptual comparisons between these methods. We also show how PUNCH-P data can be combined with mRNA measurements to determine relative translation efficiency for specific mRNAs.

How is the cerebellum capable of efficient motor learning and control despite very low firing of the inferior olive (IO) inputs, which are postulated to carry errors needed for learning and contribute to on-line motor control? IO neurons form the largest electrically coupled network in the adult human brain. Here, we discuss how intermediate coupling strengths can lead to chaotic resonance and increase information transmission of the error signal despite the very low IO firing rate. This increased information transmission can then lead to more efficient learning than with weak or strong coupling. In addition, we argue that a dynamic modulation of IO electrical coupling via the Purkinje cell-deep cerebellar neurons - IO triangle could speed up learning and improve on-line control. Initially strong coupling would allow transmission of large errors to multiple functionally related Purkinje cells, resulting in fast but coarse learning as well as significant effects on deep cerebellar nucleus and on-line motor control. In the late phase of learning decreased coupling would allow desynchronized IO firing, allowing high-fidelity transmission of error, resulting in slower but fine learning, and little on-line motor control effects.

How epilepsy affects brain functional networks remains poorly understood. Here we investigated resting state functional connectivity of the temporal region in temporal lobe epilepsy. Thirty-two patients with unilateral temporal lobe epilepsy underwent resting state blood-oxygenation level dependent functional magnetic resonance imaging. We defined regions of interest a priori focusing on structures involved, either structurally or metabolically, in temporal lobe epilepsy. These structures were identified in each patient based on their individual anatomy. Our principal findings are decreased local and inter-hemispheric functional connectivity and increased intra-hemispheric functional connectivity ipsilateral to the seizure focus compared to normal controls. Specifically, several regions in the affected temporal lobe showed increased functional coupling with the ipsilateral insula and immediately neighboring subcortical regions. Additionally there was significantly decreased functional connectivity between regions in the affected temporal lobe and their contralateral homologous counterparts. Intriguingly, decreased local and inter-hemispheric connectivity was not limited or even maximal for the hippocampus or medial temporal region, which is the typical seizure onset region. Rather it also involved several regions in temporal neo-cortex, while also retaining specificity, with neighboring regions such as the amygdala remaining unaffected. These findings support a view of temporal lobe epilepsy as a disease of a complex functional network, with alterations that extend well beyond the seizure onset area, and the specificity of the observed connectivity changes suggests the possibility of a functional imaging biomarker for temporal lobe epilepsy.

It is well known that even under identical task conditions, there is a tremendous amount of trial-to-trial variability in both brain activity and behavioral output. Thus far the vast majority of event-related potential (ERP) studies investigating the relationship between trial-to-trial fluctuations in brain activity and behavioral performance have only tested a monotonic relationship between them. However, it was recently found that across-trial variability can correlate with behavioral performance independent of trial-averaged activity. This finding predicts a U- or inverted-U- shaped relationship between trial-to-trial brain activity and behavioral output, depending on whether larger brain variability is associated with better or worse behavior, respectively. Using a visual stimulus detection task, we provide evidence from human electrocorticography (ECoG) for an inverted-U brain-behavior relationship: When the raw fluctuation in broadband ECoG activity is closer to the across-trial mean, hit rate is higher and reaction times faster. Importantly, we show that this relationship is present not only in the post-stimulus task-evoked brain activity, but also in the pre-stimulus spontaneous brain activity, suggesting anticipatory brain dynamics. Our findings are consistent with the presence of stochastic noise in the brain. They further support attractor network theories, which postulate that the brain settles into a more confined state space under task performance, and proximity to the targeted trajectory is associated with better performance.

T-cells have evolved the unique ability to discriminate "self" from "non-self" with high sensitivity and selectivity. However, tissue-specific autoimmunity, tolerance or eradication of cancer does not fit into the self/non-self paradigm because the T-cell responses in these situations are most often directed to non-mutated self-proteins. To determine the TCR affinity threshold defining the optimal balance between effective antitumor activity and autoimmunity in vivo, we used a novel self-antigen system comprised of seven human melanoma gp100209-217-specific TCRs spanning physiological affinities (1 to 100 muM). We found that in vitro and in vivo T cell responses are determined by TCR affinity. Strikingly, we found that T cell antitumor activity and autoimmunity are closely coupled but plateau at a defined TCR affinity of 10 muM, likely due to diminished contribution of TCR affinity to avidity above the threshold. Our results suggest a relatively low affinity threshold is necessary for the immune system to avoid selfdamage given the close relationship between antitumor activity and autoimmunity. This, in turn, indicates that treatment strategies focusing on TCRs in the intermediate affinity range (KD ~10 muM) or targeting or targeting shared tumor antigens would dampen the potential for autoimmunity during adoptive T cell therapy for the treatment of cancer

When natural photoreception is disrupted, as in outer-retinal degenerative diseases, artificial stimulation of surviving nerve cells offers a potential strategy for bypassing compromised neural circuits. Recently, light-sensitive proteins that photosensitize quiescent neurons have generated unprecedented opportunities for optogenetic neuronal control, inspiring early development of optical retinal prostheses. Selectively exciting large neural populations are essential for eliciting meaningful perceptions in the brain. Here we provide the first demonstration of holographic photo-stimulation strategies for bionic vision restoration. In blind retinas, we demonstrate reliable holographically patterned optogenetic stimulation of retinal ganglion cells with millisecond temporal precision and cellular resolution. Holographic excitation strategies could enable flexible control over distributed neuronal circuits, potentially paving the way towards high-acuity vision restoration devices and additional medical and scientific neuro-photonics applications.

Incorporation of photoisomerizable chromophores into small molecule ligands represents a general approach for reversibly controlling protein function with light. Illumination at different wavelengths produces photostationary states (PSSs) consisting of different ratios of photoisomers. Thus optimal implementation of photoswitchable ligands requires knowledge of their wavelength sensitivity. Using an azobenzene-based ion channel blocker as an example, this protocol describes a (1)H NMR assay that can be used to precisely determine the isomeric content of photostationary states (PSSs) as a function of illumination wavelength. Samples of the photoswitchable ligand are dissolved in deuterated water and analyzed by UV/VIS spectroscopy to identify the range of illumination wavelengths that produce PSSs. The PSSs produced by these wavelengths are quantified using (1)H NMR spectroscopy under continuous irradiation through a monochromator-coupled fiber-optic cable. Because aromatic protons of azobenzene trans and cis isomers exhibit sufficiently different chemical shifts, their relative abundances at each PSS can be readily determined by peak integration. Constant illumination during spectrum acquisition is essential to accurately determine PSSs from molecules that thermally relax on the timescale of minutes or faster. This general protocol can be readily applied to any photoswitch that exhibits distinct (1)H NMR signals in each photoisomeric state.