The reconstruction of neural circuits from serial section electron microscopy (ssEM) images is being accelerated by automatic image segmentation methods. Segmentation accuracy is often limited by the preceding step of aligning 2D section images to create a 3D image stack. Precise and robust alignment in the presence of image artifacts is challenging, especially as datasets are attaining the petascale. We present a computational pipeline for aligning ssEM images with several key elements. Self-supervised convolutional nets are trained via metric learning to encode and align image pairs, and they are used to initialize iterative fine-tuning of alignment. A procedure called vector voting increases robustness to image artifacts or missing image data. For speedup the series is divided into blocks that are distributed to computational workers for alignment. The blocks are aligned to each other by composing transformations with decay, which achieves a global alignment without resorting to a time-consuming global optimization. We apply our pipeline to a whole fly brain dataset, and show improved accuracy relative to prior state of the art. We also demonstrate that our pipeline scales to a cubic millimeter of mouse visual cortex. Our pipeline is publicly available through two open source Python packages.

Pfam, available via servers in the UK (http://pfam.sanger.ac.uk/) and the USA (http://pfam.janelia.org/), is a widely used database of protein families, containing 14 831 manually curated entries in the current release, version 27.0. Since the last update article 2 years ago, we have generated 1182 new families and maintained sequence coverage of the UniProt Knowledgebase (UniProtKB) at nearly 80%, despite a 50% increase in the size of the underlying sequence database. Since our 2012 article describing Pfam, we have also undertaken a comprehensive review of the features that are provided by Pfam over and above the basic family data. For each feature, we determined the relevance, computational burden, usage statistics and the functionality of the feature in a website context. As a consequence of this review, we have removed some features, enhanced others and developed new ones to meet the changing demands of computational biology. Here, we describe the changes to Pfam content. Notably, we now provide family alignments based on four different representative proteome sequence data sets and a new interactive DNA search interface. We also discuss the mapping between Pfam and known 3D structures.

Fluorescence microscopy is an invaluable tool in biology, yet its performance is compromised when the wavefront of light is distorted due to optical imperfections or the refractile nature of the sample. Such optical aberrations can dramatically lower the information content of images by degrading image contrast, resolution, and signal. Adaptive optics (AO) methods can sense and subsequently cancel the aberrated wavefront, but are too complex, inefficient, slow, or expensive for routine adoption by most labs. Here we introduce a rapid, sensitive, and robust wavefront sensing scheme based on phase diversity, a method successfully deployed in astronomy but underused in microscopy. Our method enables accurate wavefront sensing to less than λ/35 root mean square (RMS) error with few measurements, and AO with no additional hardware besides a corrective element. After validating the method with simulations, we demonstrate calibration of a deformable mirror > 100-fold faster than comparable methods (corresponding to wavefront sensing on the ~100 ms scale), and sensing and subsequent correction of severe aberrations (RMS wavefront distortion exceeding λ/2), restoring diffraction-limited imaging on extended biological samples.

We show through experiments and simulations that parallel phase modulation, a technique developed in the field of adaptive optics, can be employed to quickly determine the spectral phase profile of ultrafast laser pulses and to perform phase compensation as well as pulse shaping. Different from many existing ultrafast pulse measurement methods, the technique reported here requires no spectrum measurements of nonlinear signals. Instead, the power of nonlinear signals is used directly to quickly measure the spectral phase, a convenient feature for applications such as two-photon fluorescence microscopy. The method is found to work with both smooth and even completely random distortions. The experimental results are verified with MIIPS measurements.

The Hippo pathway was originally discovered to control tissue growth in Drosophila and includes the Hippo kinase (Hpo; MST1/2 in mammals), scaffold protein Salvador (Sav; SAV1 in mammals) and the Warts kinase (Wts; LATS1/2 in mammals). The Hpo kinase is activated by binding to Crumbs-Expanded (Crb-Ex) and/or Merlin-Kibra (Mer-Kib) proteins at the apical domain of epithelial cells. Here we show that activation of Hpo also involves the formation of supramolecular complexes with properties of a biomolecular condensate, including concentration dependence and sensitivity to starvation, macromolecular crowding, or 1,6-hexanediol treatment. Overexpressing Ex or Kib induces formation of micron-scale Hpo condensates in the cytoplasm, rather than at the apical membrane. Several Hippo pathway components contain unstructured low-complexity domains and purified Hpo-Sav complexes undergo phase separation in vitro. Formation of Hpo condensates is conserved in human cells. We propose that apical Hpo kinase activation occurs in phase separated "signalosomes" induced by clustering of upstream pathway components.

Yes-associated protein (YAP) is a transcriptional co-activator that regulates cell proliferation and survival by binding to a select set of enhancers for target gene activation. How YAP coordinates these transcriptional responses is unknown. Here, we demonstrate that YAP forms liquid-like condensates in the nucleus. Formed within seconds of hyperosmotic stress, YAP condensates compartmentalized the YAP transcription factor TEAD1 and other YAP-related co-activators, including TAZ, and subsequently induced the transcription of YAP-specific proliferation genes. Super-resolution imaging using assay for transposase-accessible chromatin with photoactivated localization microscopy revealed that the YAP nuclear condensates were areas enriched in accessible chromatin domains organized as super-enhancers. Initially devoid of RNA polymerase II, the accessible chromatin domains later acquired RNA polymerase II, transcribing RNA. The removal of the intrinsically-disordered YAP transcription activation domain prevented the formation of YAP condensates and diminished downstream YAP signalling. Thus, dynamic changes in genome organization and gene activation during YAP reprogramming is mediated by liquid-liquid phase separation.

The cricket's auditory system is a highly directional pressure difference receiver whose function is hypothesised to depend on phase relationships between the sound waves propagating through the auditory trachea that connects the left and right hearing organs. We tested this hypothesis by measuring the effect of experimentally constructed phase shifts in acoustic stimuli on phonotactic behavior of Gryllus bimaculatus, the oscillatory response patterns of the tympanic membrane, and the activity of the auditory afferents. The same artificial calling song was played simultaneously at the left and right sides of the cricket, but one sound pattern was shifted in phase by 90 deg (carrier frequencies between 3.6 and 5.4 kHz). All three levels of auditory processing are sensitive to experimentally induced acoustic phase shifts, and the response characteristics are dependent on the carrier frequency of the sound stimulus. At lower frequencies, crickets steered away from the sound leading in phase, while tympanic membrane vibrations and auditory afferent responses were smaller when the ipsilateral sound was leading. In contrast, opposite responses were observed at higher frequencies in all three levels of auditory processing. Minimal responses occurred near the carrier frequency of the cricket's calling song, suggesting a stability at this frequency. Our results indicate that crickets may use directional cues arising from phase shifts in acoustic signals for sound localisation, and that the response properties of pressure difference receivers may be analysed with phase-shifted sound stimuli to further our understanding of how insect auditory systems are adapted for directional processing.

The first general phase-sensitive sum-frequency vibrational spectroscopy (SFVS) was described, which recovers the phase information lost in conventional SFVS measurements. Using a self-assembled monolayer, we demonstrated that this novel technique measures the absolute orientation of surface molecular moieties and is very powerful in resolving spectral features.

Electron crystallography is arguably the only electron cryomicroscopy (cryo EM) technique able to deliver atomic resolution data (better then 3 Å) for membrane proteins embedded in a membrane. The progress in hardware improvements and sample preparation for diffraction analysis resulted in a number of recent examples where increasingly higher resolutions were achieved. Other chapters in this book detail the improvements in hardware and delve into the intricate art of sample preparation for microscopy and electron diffraction data collection and processing. In this chapter, we describe in detail the protocols for molecular replacement for electron diffraction studies. The use of a search model for phasing electron diffraction data essentially eliminates the need of acquiring image data rendering it immune to aberrations from drift and charging effects that effectively lower the attainable resolution.

The distribution of chromatin-associated proteins plays a key role in directing nuclear function. Previously, we developed an image-based method to quantify the nuclear distributions of proteins and showed that these distributions depended on the phenotype of human mammary epithelial cells. Here we describe a method that creates a hierarchical tree of the given cell phenotypes and calculates the statistical significance between them, based on the clustering analysis of nuclear protein distributions.