Synthetic mammalian trigger-controlled bipartite transcription factors

Synthetic biology has significantly advanced the design of synthetic control devices, gene circuits and networks that can reprogram mammalian cells in a trigger-inducible manner. Prokaryotic helix-turn-helix motifs have become the standard resource to design synthetic mammalian transcription factors that tune chimeric promoters in a small molecule-responsive manner. We have identified a family of Actinomycetes transcriptional repressor proteins showing a tandem TetR-family signature and have used a synthetic biology-inspired approach to reveal the potential control dynamics of these bi-partite regulators. Daisy-chain assembly of well-characterized prokaryotic repressor proteins such as TetR, ScbR, TtgR or VanR and fusion to either the Herpes simplex transactivation domain VP16 or the Krueppel-associated box domain (KRAB) of the human kox-1 gene resulted in synthetic bi- and even tri-partite mammalian transcription factors that could reversibly program their individual chimeric or hybrid promoters for trigger-adjustable transgene expression using tetracycline (TET), γ-butyrolactones, phloretin and vanillic acid. Detailed characterization of the bi-partite ScbR-TetR-VP16 (ST-TA) transcription factor revealed independent control of TET- and γ-butyrolactone-responsive promoters at high and double-pole double-throw (DPDT) relay switch qualities at low intracellular concentrations. Similar to electromagnetically operated mechanical DPDT relay switches that control two electric circuits by a fully isolated low-power signal, TET programs ST-TA to progressively switch from TetR-specific promoter-driven expression of transgene one to ScbR-specific promoter-driven transcription of transgene two while ST-TA flips back to exclusive transgene 1 expression in the absence of the trigger antibiotic. We suggest that natural repressors and activators with tandem TetR-family signatures may also provide independent as well as DPDT-mediated control of two sets of transgenes in bacteria, and that their synthetic transcription-factor analogs may enable the design of compact therapeutic gene circuits for gene and cell-based therapie

The forebrain synaptic transcriptome is organized by clocks but its proteome is driven by sleep

Neurons have adapted mechanisms to traffic RNA and protein into distant dendritic and axonal arbors. Taking a biochemical approach, we reveal that forebrain synaptic transcript accumulation shows overwhelmingly daily rhythms, with two-thirds of synaptic transcripts showing time-of-day-dependent abundance independent of oscillations in the soma. These transcripts formed two sharp temporal and functional clusters, with transcripts preceding dawn related to metabolism and translation and those anticipating dusk related to synaptic transmission. Characterization of the synaptic proteome around the clock demonstrates the functional relevance of temporal gating for synaptic processes and energy homeostasis. Unexpectedly, sleep deprivation completely abolished proteome but not transcript oscillations. Altogether, the emerging picture is one of a circadian anticipation of messenger RNA needs in the synapse followed by translation as demanded by sleep-wake cycles

Structural connectivity in a single case of progressive prosopagnosia: The role of the right inferior longitudinal fasciculus

Progressive prosopagnosia (PP) is a clinical syndrome characterized by a progressive and selective inability to recognize and identify faces of familiar people. Here we report a patient (G.S.) with PP, mainly related to a prominent deficit in recognition of familiar faces, without a semantic (cross-modal) impairment. An in-depth evaluation showed that his deficit extended to other classes of objects, both living and non-living. A follow-up neuropsychological assessment did not reveal substantial changes after about 1 year. Structural MRI showed predominant right temporal lobe atrophy. Diffusion tensor imaging was performed to elucidate structural connectivity of the inferior longitudinal fasciculus (ILF) and the inferior fronto-occipital fasciculus (IFOF), the two major tracts that project through the core fusiform region to the anterior temporal and frontal cortices, respectively. Right ILF was markedly reduced in G.S., while left ILF and IFOFs were apparently preserved. These data are in favour of a crucial role of the neural circuit subserved by right ILF in the pathogenesis of PP

“Keep up the good work!”: A case study of the effects of a specific cognitive training in Alzheimer’s disease

Alzheimer's disease (AD) is a neurodegenerative condition characterized by significant impairment in multiple cognitive domains. In recent years, the development of cognitive trainings in AD has received significant attention. In the present case study we designed a cognitive training program (GEO, Geographical Exercises for cognitive Optimization) based on an errorless paradigm and tailored to the patient's cultural interests. The aim of this training was to investigate the potential for acquiring and possibly retaining both procedural and verbal knowledge in early-stage AD. This study involved an 80-year-old female patient diagnosed with early-stage AD, and 10 matched healthy subjects. Participants were asked to perform the two GEO training tasks: a "puzzle-like" task for procedural memory, and an "association" task for verbal memory. Both the patient and the healthy controls were subsequently trained with GEO using the same two tasks for 2 months. Although the patient's performance before training in both tasks was poor compared to healthy controls, after the training these differences disappeared. Our results showed that the patient was able to acquire new procedural abilities and verbal knowledge, and that her achievements were stable at the follow-up testing scheduled 3 months after the end of the intervention. This case study suggests a potentially useful strategy for cognitive training in AD. </p

Synthetic mammalian trigger-controlled bipartite transcription factors

Synthetic biology has significantly advanced the design of synthetic control devices, gene circuits and networks that can reprogram mammalian cells in a trigger-inducible manner. Prokaryotic helix-turn-helix motifs have become the standard resource to design synthetic mammalian transcription factors that tune chimeric promoters in a small molecule-responsive manner. We have identified a family of Actinomycetes transcriptional repressor proteins showing a tandem TetR-family signature and have used a synthetic biology-inspired approach to reveal the potential control dynamics of these bi-partite regulators. Daisy-chain assembly of well-characterized prokaryotic repressor proteins such as TetR, ScbR, TtgR or VanR and fusion to either the Herpes simplex transactivation domain VP16 or the Krueppel-associated box domain (KRAB) of the human kox-1 gene resulted in synthetic bi- and even tri-partite mammalian transcription factors that could reversibly program their individual chimeric or hybrid promoters for trigger-adjustable transgene expression using tetracycline (TET), γ-butyrolactones, phloretin and vanillic acid. Detailed characterization of the bi-partite ScbR-TetR-VP16 (ST-TA) transcription factor revealed independent control of TET- and γ-butyrolactone-responsive promoters at high and double-pole double-throw (DPDT) relay switch qualities at low intracellular concentrations. Similar to electromagnetically operated mechanical DPDT relay switches that control two electric circuits by a fully isolated low-power signal, TET programs ST-TA to progressively switch from TetR-specific promoter-driven expression of transgene one to ScbR-specific promoter-driven transcription of transgene two while ST-TA flips back to exclusive transgene 1 expression in the absence of the trigger antibiotic. We suggest that natural repressors and activators with tandem TetR-family signatures may also provide independent as well as DPDT-mediated control of two sets of transgenes in bacteria, and that their synthetic transcription-factor analogs may enable the design of compact therapeutic gene circuits for gene and cell-based therapies.ISSN:1362-4962ISSN:0301-561

Dynamic- and Frequency-Specific Regulation of Sleep Oscillations by Cortical Potassium Channels

Primary electroencephalographic (EEG) features of sleep arise in part from thalamocortical neural assemblies, and cortical potassium channels have long been thought to play a critical role. We have exploited the regionally dynamic nature of sleep EEG to develop a novel screening strategy and used it to conduct an adeno-associated virus (AAV)-mediated RNAi screen for cellular roles of 31 different voltage-gated potassium channels in modulating cortical EEG features across the circadian sleep-wake cycle. Surprisingly, a majority of channels modified only electroencephalographic frequency bands characteristic of sleep, sometimes diurnally or even in specific vigilance states. Confirming our screen for one channel, we show that depletion of the KCa1.1 (or “BK”) channel reduces EEG power in slow-wave sleep by slowing neuronal repolarization. Strikingly, this reduction completely abolishes transcriptomic changes between sleep and wake. Thus, our data establish an unexpected connection between transcription and EEG power controlled by specific potassium channels. We postulate that additive dynamic roles of individual potassium channels could integrate different influences upon sleep and wake within single neurons

GNPy Experimental Validation for Nyquist Subcarriers Flexible Transmission up to 800 G

We test the performance of Nyquist subcarriers flexible transponders up to 800 Gbit/s over a 20×80-km optical link operated at full WDM spectral load, obtaining excellent accuracy in GSNR and optimal power predictions using GNP

SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species

Understanding sleep and its perturbation by environment, mutation, or medication remains a central problem in biomedical research. Its examination in animal models rests on brain state analysis via classification of electroencephalographic (EEG) signatures. Traditionally, these states are classified by trained human experts by visual inspection of raw EEG recordings, which is a laborious task prone to inter-individual variability. Recently, machine learning approaches have been developed to automate this process, but their generalization capabilities are often insufficient, especially across animals from different experimental studies. To address this challenge, we crafted a convolutional neural network-based architecture to produce domain invariant predictions, and furthermore integrated a hidden Markov model to constrain state dynamics based upon known sleep physiology. Our method, which we named SPINDLE (Sleep Phase Identification with Neural networks for Domain-invariant LEearning) was validated using data of four animal cohorts from three independent sleep labs, and achieved average agreement rates of 99%, 98%, 93%, and 97% with scorings from five human experts from different labs, essentially duplicating human capability. It generalized across different genetic mutants, surgery procedures, recording setups and even different species, far exceeding state-of-the-art solutions that we tested in parallel on this task. Moreover, we show that these scored data can be processed for downstream analyzes identical to those from human-scored data, in particular by demonstrating the ability to detect mutation-induced sleep alteration. We provide to the scientific community free usage of SPINDLE and benchmarking datasets as an online server at https://sleeplearning.ethz.ch. Our aim is to catalyze high-throughput and well-standardized experimental studies in order to improve our understanding of sleep