Two-photon probe excitation data are commonly presented as absorption cross section or molecular brightness (the detected fluorescence rate per molecule). We report two-photon molecular brightness spectra for a diverse set of organic and genetically encoded probes with an automated spectroscopic system based on fluorescence correlation spectroscopy. The two-photon action cross section can be extracted from molecular brightness measurements at low excitation intensities, while peak molecular brightness (the maximum molecular brightness with increasing excitation intensity) is measured at higher intensities at which probe photophysical effects become significant. The spectral shape of these two parameters was similar across all dye families tested. Peak molecular brightness spectra, which can be obtained rapidly and with reduced experimental complexity, can thus serve as a first-order approximation to cross-section spectra in determining optimal wavelengths for two-photon excitation, while providing additional information pertaining to probe photostability. The data shown should assist in probe choice and experimental design for multiphoton microscopy studies. Further, we show that, by the addition of a passive pulse splitter, nonlinear bleaching can be reduced-resulting in an enhancement of the fluorescence signal in fluorescence correlation spectroscopy by a factor of two. This increase in fluorescence signal, together with the observed resemblance of action cross section and peak brightness spectra, suggests higher-order photobleaching pathways for two-photon excitation.

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

Imaging mRNA with single-molecule sensitivity in live cells has become an indispensable tool for quantitatively studying RNA biology. The MS2 system has been extensively used due to its unique simplicity and sensitivity. However, the levels of the coat protein needed for consistent labeling of mRNAs limits the sensitivity and quantitation of this technology. Here, we applied fluorescence fluctuation spectroscopy to quantitatively characterize and enhance the MS2 system. Surprisingly, we found that a high fluorescence background resulted from inefficient dimerization of fluorescent protein (FP)-labeled MS2 coat protein (MCP). To mitigate this problem, we used a single-chain tandem dimer of MCP (tdMCP) that significantly increased the uniformity and sensitivity of mRNA labeling. Furthermore, we characterized the PP7 coat protein and the binding to its respective RNA stem loop. We conclude that the PP7 system performs better for RNA labeling. Finally, we used these improvements to study endogenous β-actin mRNA, which has 24xMS2 binding sites inserted into the 3' untranslated region. The tdMCP-FP allowed uniform RNA labeling and provided quantitative measurements of endogenous mRNA concentration and diffusion. This work provides a foundation for quantitative spectroscopy and imaging of single mRNAs directly in live cells.

Fluorescence imaging has revolutionized biomedical research over the past three decades. Its high molecular specificity and unrivalled single-molecule-level sensitivity have enabled breakthroughs in a number of research fields. For in vivo applications its major limitation is its superficial imaging depth, a result of random scattering in biological tissues causing exponential attenuation of the ballistic component of a light wave. Here, we present fluorescence imaging beyond the ballistic regime by combining single-cycle pulsed ultrasound modulation and digital optical phase conjugation. We demonstrate a near-isotropic three-dimensional localized sound–light interaction zone. With the exceptionally high optical gain provided by the digital optical phase conjugation system, we can deliver sufficient optical power to a focus inside highly scattering media for not only fluorescence imaging but also a variety of linear and nonlinear spectroscopy measurements. This technology paves the way for many important applications in both fundamental biology research and clinical studies.

Recent behavioral studies have given rise to two contrasting models for limited working memory capacity: a "discrete-slot" model in which memory items are stored in a limited number of slots, and a "shared-resource" model in which the neural representation of items is distributed across a limited pool of resources. To elucidate the underlying neural processes, we investigated a continuous network model for working memory of an analog feature. Our model network fundamentally operates with a shared resource mechanism, and stimuli in cue arrays are encoded by a distributed neural population. On the other hand, the network dynamics and performance are also consistent with the discrete-slot model, because multiple objects are maintained by distinct localized population persistent activity patterns (bump attractors). We identified two phenomena of recurrent circuit dynamics that give rise to limited working memory capacity. As the working memory load increases, a localized persistent activity bump may either fade out (so the memory of the corresponding item is lost) or merge with another nearby bump (hence the resolution of mnemonic representation for the merged items becomes blurred). We identified specific dependences of these two phenomena on the strength and tuning of recurrent synaptic excitation, as well as network normalization: the overall population activity is invariant to set size and delay duration; therefore, a constant neural resource is shared by and dynamically allocated to the memorized items. We demonstrate that the model reproduces salient observations predicted by both discrete-slot and shared-resource models, and propose testable predictions of the merging phenomenon.

Generating diverse neurons in the central nervous system involves three major steps. First, heterogeneous neural progenitors are specified by positional cues at early embryonic stages. Second, neural progenitors sequentially produce neurons or intermediate precursors that acquire different temporal identities based on their birth-order. Third, sister neurons produced during asymmetrical terminal mitoses are given distinct fates. Determining the molecular mechanisms underlying each of these three steps of cellular diversification will unravel brain development and evolution. Drosophila has a relatively simple and tractable CNS, and previous studies on Drosophila CNS development have greatly advanced our understanding of neuron fate specification. Here we review those studies and discuss how the lessons we have learned from fly teach us the process of neuronal diversification in general.

The developing spinal cord is subdivided into distinct progenitor domains, each of which gives rise to different types of neurons. However, the developmental mechanisms responsible for generating neuronal diversity within a domain are not well understood. Here, we have studied zebrafish V0 neurons, those that derive from the p0 progenitor domain, to address this question. We find that all V0 neurons have commissural axons, but they can be divided into excitatory and inhibitory classes. V0 excitatory neurons (V0-e) can be further categorized into three groups based on their axonal trajectories; V0-eA (ascending), V0-eB (bifurcating), and V0-eD (descending) neurons. By using time-lapse imaging of p0 progenitors and their progeny, we show that inhibitory and excitatory neurons are produced from different progenitors. We also demonstrate that V0-eA neurons are produced from distinct progenitors, while V0-eB and V0-eD neurons are produced from common progenitors. We then use birth-date analysis to reveal that V0-eA, V0-eB, and V0-eD neurons arise in this order. By perturbing Notch signaling and accelerating neuronal differentiation, we predictably alter the generation of early born V0-e neurons at the expense of later born ones. These results suggest that multiple types of V0 neurons are produced by two distinct mechanisms; from heterogeneous p0 progenitors and from the same p0 progenitor, but in a time-dependent manner.

The transition from outcrossing to predominant self-fertilization is one of the most common evolutionary transitions in flowering plants. This shift is often accompanied by a suite of changes in floral and reproductive characters termed the selfing syndrome. Here, we characterize the genetic architecture and evolutionary forces underlying evolution of the selfing syndrome in Capsella rubella following its recent divergence from the outcrossing ancestor C. grandiflora. We conduct genotyping by multiplexed shotgun sequencing and map floral and reproductive traits in a large (N= 550) F2 population. Our results suggest that in contrast to previous studies of the selfing syndrome, changes at a few loci, some with major effects, have shaped the evolution of the selfing syndrome in Capsella. The directionality of QTL effects, as well as population genetic patterns of polymorphism and divergence at 318 loci, is consistent with a history of directional selection on the selfing syndrome. Our study is an important step toward characterizing the genetic basis and evolutionary forces underlying the evolution of the selfing syndrome in a genetically accessible model system.

Recording activity from identified populations of neurons is a central goal of neuroscience. Changes in membrane depolarization, particularly action potentials, are the most important features of neural physiology to extract, although ions, neurotransmitters, neuromodulators, second messengers, and the activation state of specific proteins are also crucial. Modern fluorescence microscopy provides the basis for such activity mapping, through multi-photon imaging and other optical schemes. Probes remain the rate-limiting step for progress in this field: they should be bright and photostable, and ideally come in multiple colors. Only protein-based reagents permit chronic imaging from genetically specified cells. Here we review recent progress in the design, optimization and deployment of genetically encoded indicators for calcium ions (a proxy for action potentials), membrane potential, and neurotransmitters. We highlight seminal experiments, and present an outlook for future progress.

The anterodorsal projection neuron lineage of Drosophila melanogaster produces 40 neuronal types in a stereotypic order. Here we take advantage of this complete lineage sequence to examine the role of known temporal fating factors, including Chinmo and the Hb/Kr/Pdm/Cas transcriptional cascade, within this diverse central brain lineage. Kr mutation affects the temporal fate of the neuroblast (NB) itself, causing a single fate to be skipped, whereas Chinmo null only elicits fate transformation of NB progeny without altering cell counts. Notably, Chinmo operates in two separate windows to prevent fate transformation (into the subsequent Chinmo-indenpendent fate) within each window. By contrast, Hb/Pdm/Cas play no detectable role, indicating that Kr either acts outside of the cascade identified in the ventral nerve cord or that redundancy exists at the level of fating factors. Therefore, hierarchical fating mechanisms operate within the lineage to generate neuronal diversity in an unprecedented fashion.