Highlights:

• Biological specimens introduce wavefront aberrations and deteriorate the image quality of optical microscopy.
• Adaptive optics is used in optical microscopy to recover ideal imaging performance.
• Adaptive optical imaging improves structural imaging of neurons, allowing for synaptic-level resolution at depth.
• Adaptive optical imaging leads to a more accurate characterization of the functional properties of neurons.

With the ability to correct for the aberrations introduced by biological specimens, adaptive optics—a method originally developed for astronomical telescopes—has been applied to optical microscopy to recover diffraction-limited imaging performance deep within living tissue. In particular, this technology has been used to improve image quality and provide a more accurate characterization of both structure and function of neurons in a variety of living organisms. Among its many highlights, adaptive optical microscopy has made it possible to image large volumes with diffraction-limited resolution in zebrafish larval brains, to resolve dendritic spines over 600μm deep in the mouse brain, and to more accurately characterize the orientation tuning properties of thalamic boutons in the primary visual cortex of awake mice.

Third-harmonic generation microscopy is a powerful label-free nonlinear imaging technique, providing essential information about structural characteristics of cells and tissues without requiring external labelling agents. In this work, we integrated a recently developed compact adaptive optics module into a third-harmonic generation microscope, to measure and correct for optical aberrations in complex tissues. Taking advantage of the high sensitivity of the third-harmonic generation process to material interfaces and thin membranes, along with the 1,300-nm excitation wavelength used here, our adaptive optical third-harmonic generation microscope enabled high-resolution in vivo imaging within highly scattering biological model systems. Examples include imaging of myelinated axons and vascular structures within the mouse spinal cord and deep cortical layers of the mouse brain, along with imaging of key anatomical features in the roots of the model plant Brachypodium distachyon. In all instances, aberration correction led to significant enhancements in image quality.

Adjusting the objective correction collar is a widely used approach to correct spherical aberrations (SA) in optical microscopy. In this work, we characterized and compared its performance with adaptive optics in the context of in vivo brain imaging with two-photon fluorescence microscopy. We found that the presence of sample tilt had a deleterious effect on the performance of SA-only correction. At large tilt angles, adjusting the correction collar even worsened image quality. In contrast, adaptive optical correction always recovered optimal imaging performance regardless of sample tilt. The extent of improvement with adaptive optics was dependent on object size, with smaller objects having larger relative gains in signal intensity and image sharpness. These observations translate into a superior performance of adaptive optics for structural and functional brain imaging applications in vivo, as we confirmed experimentally.

Biological specimens are rife with optical inhomogeneities that seriously degrade imaging performance under all but the most ideal conditions. Measuring and then correcting for these inhomogeneities is the province of adaptive optics. Here we introduce an approach to adaptive optics in microscopy wherein the rear pupil of an objective lens is segmented into subregions, and light is directed individually to each subregion to measure, by image shift, the deflection faced by each group of rays as they emerge from the objective and travel through the specimen toward the focus. Applying our method to two-photon microscopy, we could recover near-diffraction-limited performance from a variety of biological and nonbiological samples exhibiting aberrations large or small and smoothly varying or abruptly changing. In particular, results from fixed mouse cortical slices illustrate our ability to improve signal and resolution to depths of 400 microm.

Biological specimens are rife with optical inhomogeneities that seriously degrade imaging performance under all but the most ideal conditions. Measuring and then correcting for these inhomogeneities is the province of adaptive optics. Here we introduce an approach to adaptive optics in microscopy wherein the rear pupil of an objective lens is segmented into subregions, and light is directed individually to each subregion to measure, by image shift, the deflection faced by each group of rays as they emerge from the objective and travel through the specimen toward the focus. Applying our method to two-photon microscopy, we could recover near-diffraction-limited performance from a variety of biological and nonbiological samples exhibiting aberrations large or small and smoothly varying or abruptly changing. In particular, results from fixed mouse cortical slices illustrate our ability to improve signal and resolution to depths of 400 microm.

Commentary: Introduces a new, zonal approach to adaptive optics (AO) in microscopy suitable for highly inhomogeneous and/or scattering samples such as living tissue. The method is unique in its ability to handle large amplitude aberrations (>20 wavelengths), including spatially complex aberrations involving high order modes beyond the ability of most AO actuators to correct. As befitting a technique designed for in vivo fluorescence imaging, it is also photon efficient.
Although used here in conjunction with two photon microscopy to demonstrate correction deep into scattering tissue, the same principle of pupil segmentation might be profitably adapted to other point-scanning or widefield methods. For example, plane illumination microscopy of multicellular specimens is often beset by substantial aberrations, and all far-field superresolution methods are exquisitely sensitive to aberrations.

Drug addiction and obesity share the core feature that those afflicted by the disorders express a desire to limit drug or food consumption yet persist despite negative consequences. Emerging evidence suggests that the compulsivity that defines these disorders may arise, to some degree at least, from common underlying neurobiological mechanisms. In particular, both disorders are associated with diminished striatal dopamine D2 receptor (D2R) availability, likely reflecting their decreased maturation and surface expression. In striatum, D2Rs are expressed by approximately half of the principal medium spiny projection neurons (MSNs), the striatopallidal neurons of the so-called 'indirect' pathway. D2Rs are also expressed presynaptically on dopamine terminals and on cholinergic interneurons. This heterogeneity of D2R expression has hindered attempts, largely using traditional pharmacological approaches, to understand their contribution to compulsive drug or food intake. The emergence of genetic technologies to target discrete populations of neurons, coupled to optogenetic and chemicogenetic tools to manipulate their activity, have provided a means to dissect striatopallidal and cholinergic contributions to compulsivity. Here, we review recent evidence supporting an important role for striatal D2R signaling in compulsive drug use and food intake. We pay particular attention to striatopallidal projection neurons and their role in compulsive responding for food and drugs. Finally, we identify opportunities for future obesity research using known mechanisms of addiction as a heuristic, and leveraging new tools to manipulate activity of specific populations of striatal neurons to understand their contributions to addiction and obesity.

Understanding the structure and function of neural circuits are central questions in neuroscience research. To address these questions, new genetically encoded tools have been developed for mapping, monitoring, and manipulating neurons. Essential to implementation of these tools is their selective delivery to defined neuronal populations in the brain. This has been facilitated by recent improvements in cell type-specific transgene expression using recombinant adeno-associated viral vectors. Here, we highlight these developments and discuss areas for improvement that could further expand capabilities for neural circuit analysis.

Tsetse flies (Glossina spp.), vectors of African trypanosomes, are distinguished by their specialized reproductive biology, defined by adenotrophic viviparity (maternal nourishment of progeny by glandular secretions followed by live birth). This trait has evolved infrequently among insects and requires unique reproductive mechanisms. A key event in Glossina reproduction involves the transition between periods of lactation and nonlactation (dry periods). Increased lipolysis, nutrient transfer to the milk gland, and milk-specific protein production characterize lactation, which terminates at the birth of the progeny and is followed by a period of involution. The dry stage coincides with embryogenesis of the progeny, during which lipid reserves accumulate in preparation for the next round of lactation. The obligate bacterial symbiont Wigglesworthia glossinidia is critical to tsetse reproduction and likely provides B vitamins required for metabolic processes underlying lactation and/or progeny development. Here we describe findings that utilized transcriptomics, physiological assays, and RNA interference-based functional analysis to understand different components of adenotrophic viviparity in tsetse flies.

Mitochondria control eukaryotic cell fate by producing the energy needed to support life and the signals required to execute programed cell death. The biochemical milieu is known to affect mitochondrial function and contribute to the dysfunctional mitochondrial phenotypes implicated in cancer and the morbidities of aging. However, the physical characteristics of the extracellular matrix are also altered in cancerous and aging tissues. Here, we demonstrate that cells sense the physical properties of the extracellular matrix and activate a mitochondrial stress response that adaptively tunes mitochondrial function via solute carrier family 9 member A1-dependent ion exchange and heat shock factor 1-dependent transcription. Overall, our data indicate that adhesion-mediated mechanosignaling may play an unappreciated role in the altered mitochondrial functions observed in aging and cancer.

Systemic lupus erythematosus (SLE) is an inflammatory autoimmune disease with a strong genetic component. African-Americans (AA) are at increased risk of SLE, but the genetic basis of this risk is largely unknown. To identify causal variants in SLE loci in AA, we performed admixture mapping followed by fine mapping in AA and European-Americans (EA). Through genome-wide admixture mapping in AA, we identified a strong SLE susceptibility locus at 2q22-24 (LOD=6.28), and the admixture signal is associated with the European ancestry (ancestry risk ratio  1.5). Large-scale genotypic analysis on 19,726 individuals of African and European ancestry revealed three independently associated variants in the IFIH1 gene: an intronic variant, rs13023380 [P(meta) = 5.20×10(-14); odds ratio, 95% confidence interval = 0.82 (0.78-0.87)], and two missense variants, rs1990760 (Ala946Thr) [P(meta) = 3.08×10(-7); 0.88 (0.84-0.93)] and rs10930046 (Arg460His) [P(dom) = 1.16×10(-8); 0.70 (0.62-0.79)]. Both missense variants produced dramatic phenotypic changes in apoptosis and inflammation-related gene expression. We experimentally validated function of the intronic SNP by DNA electrophoresis, protein identification, and in vitro protein binding assays. DNA carrying the intronic risk allele rs13023380 showed reduced binding efficiency to a cellular protein complex including nucleolin and lupus autoantigen Ku70/80, and showed reduced transcriptional activity in vivo. Thus, in SLE patients, genetic susceptibility could create a biochemical imbalance that dysregulates nucleolin, Ku70/80, or other nucleic acid regulatory proteins. This could promote antibody hypermutation and auto-antibody generation, further destabilizing the cellular network. Together with molecular modeling, our results establish a distinct role for IFIH1 in apoptosis, inflammation, and autoantibody production, and explain the molecular basis of these three risk alleles for SLE pathogenesis.