Theta and gamma rhythmic coding through two spike output modes in the hippocampus during spatial navigation.

Hippocampal CA1 neurons generate single spikes and stereotyped bursts of spikes. However, it is unclear how individual neurons dynamically switch between these output modes and whether these two spiking outputs relay distinct information. We performed extracellular recordings in spatially navigating rats and cellular voltage imaging and optogenetics in awake mice. We found that spike bursts are preferentially linked to cellular and network theta rhythms (3-12 Hz) and encode an animal's position via theta phase precession, particularly as animals are entering a place field. In contrast, single spikes exhibit additional coupling to gamma rhythms (30-100 Hz), particularly as animals leave a place field. Biophysical modeling suggests that intracellular properties alone are sufficient to explain the observed input frequency-dependent spike coding. Thus, hippocampal neurons regulate the generation of bursts and single spikes according to frequency-specific network and intracellular dynamics, suggesting that these spiking modes perform distinct computations to support spatial behavior.

Striatal cholinergic interneuron membrane voltage tracks locomotor rhythms in mice.

Rhythmic neural network activity has been broadly linked to behavior. However, it is unclear how membrane potentials of individual neurons track behavioral rhythms, even though many neurons exhibit pace-making properties in isolated brain circuits. To examine whether single-cell voltage rhythmicity is coupled to behavioral rhythms, we focused on delta-frequencies (1-4 Hz) that are known to occur at both the neural network and behavioral levels. We performed membrane voltage imaging of individual striatal neurons simultaneously with network-level local field potential recordings in mice during voluntary movement. We report sustained delta oscillations in the membrane potentials of many striatal neurons, particularly cholinergic interneurons, which organize spikes and network oscillations at beta-frequencies (20-40 Hz) associated with locomotion. Furthermore, the delta-frequency patterned cellular dynamics are coupled to animals' stepping cycles. Thus, delta-rhythmic cellular dynamics in cholinergic interneurons, known for their autonomous pace-making capabilities, play an important role in regulating network rhythmicity and movement patterning.

A Viral Toolbox of Genetically Encoded Fluorescent Synaptic Tags.

Fibronectin intrabodies generated with mRNA display (FingRs) are a recently developed tool for labeling excitatory or inhibitory synapses, with the benefit of not altering endogenous synaptic protein expression levels or synaptic transmission. Here, we generated a viral vector FingR toolbox that allows for multi-color, neuron-type-specific labeling of excitatory or inhibitory synapses in multiple brain regions. We screened various fluorophores, FingR fusion configurations, and transcriptional control regulations in adeno-associated virus (AAV) and retrovirus vector designs. We report the development of a red FingR variant and demonstrated dual labeling of excitatory and inhibitory synapses in the same cells. Furthermore, we developed cre-inducible FingR AAV variants and demonstrated their utility, finding that the density of inhibitory synapses in aspiny striatal cholinergic interneurons remained unchanged in response to dopamine depletion. Finally, we generated FingR retroviral vectors, which enabled us to track the development of excitatory and inhibitory synapses in hippocampal adult-born granule cells.

Voltage Imaging of Cardiac Cells and Tissue Using the Genetically Encoded Voltage Sensor Archon1.

Precise measurement of action potentials (APs) is needed to observe electrical activity and cellular communication within cardiac tissue. Voltage-sensitive dyes (VSDs) are traditionally used to measure cardiac APs; however, they require acute chemical addition that prevents chronic imaging. Genetically encoded voltage indicators (GEVIs) enable long-term studies of APs without the need of chemical additions, but current GEVIs used in cardiac tissue exhibit poor kinetics and/or low signal to noise (SNR). Here, we demonstrate the use of Archon1, a recently developed GEVI, in hiPSC-derived cardiomyocytes (CMs). When expressed in CMs, Archon1 demonstrated fast kinetics comparable with patch-clamp electrophysiology and high SNR significantly greater than the VSD Di-8-ANEPPS. Additionally, Archon1 enabled monitoring of APs across multiple cells simultaneously in 3D cardiac tissues. These results highlight Archon1's capability to investigate the electrical activity of CMs in a variety of applications and its potential to probe functionally complex in vitro models, as well as in vivo systems.

Population imaging of neural activity in awake behaving mice.

A longstanding goal in neuroscience has been to image membrane voltage across a population of individual neurons in an awake, behaving mammal. Here we describe a genetically encoded fluorescent voltage indicator, SomArchon, which exhibits millisecond response times and is compatible with optogenetic control, and which increases the sensitivity, signal-to-noise ratio, and number of neurons observable several-fold over previously published fully genetically encoded reagents1-8. Under conventional one-photon microscopy, SomArchon enables the routine population analysis of around 13 neurons at once, in multiple brain regions (cortex, hippocampus, and striatum) of head-fixed, awake, behaving mice. Using SomArchon, we detected both positive and negative responses of striatal neurons during movement, as previously reported by electrophysiology but not easily detected using modern calcium imaging techniques9-11, highlighting the power of voltage imaging to reveal bidirectional modulation. We also examined how spikes relate to the subthreshold theta oscillations of individual hippocampal neurons, with SomArchon showing that the spikes of individual neurons are more phase-locked to their own subthreshold theta oscillations than to local field potential theta oscillations. Thus, SomArchon reports both spikes and subthreshold voltage dynamics in awake, behaving mice.

Gene Co-Expression Analysis Predicts Genetic Variants Associated with Drug Responsiveness in Lung Cancer.

Responsiveness to drugs is an important concern in designing personalized treatment for cancer patients. Currently genetic markers are often used to guide targeted therapy. However, deeper understanding of the molecular basis for drug responses and discovery of new predictive biomarkers for drug sensitivity are much needed. In this paper, we present a workflow for identifying condition-specific gene co-expression networks associated with responses to the tyrosine kinase inhibitor, Erlotinib, in lung adenocarcinoma cell lines using data from the Cancer Cell Line Encyclopedia by combining network mining and statistical analysis. Particularly, we have identified multiple gene modules specifically co-expressed in the drug responsive cell lines but not in the unresponsive group. Interestingly, most of these modules are enriched on specific cytobands, suggesting potential copy number variation events on these loci. Our results therefore imply that there are multiple genetic loci with copy number variations associated with the Erlotinib responses. The existence of CNVs in these loci is also confirmed in lung cancer tissue samples using the TCGA data. Since these structural variations are inferred from functional genomics data, these CNVs are functional variations. These results suggest the condition specific gene co- expression network mining approach is an effective approach in predicting candidate biomarkers for drug responses.