Advances in microscopy hold great promise for allowing quantitative and precise readouts of morphological and molecular phenomena at the single cell level in bacteria. However, the potential of this approach is ultimately limited by the availability of methods to perform unbiased cell segmentation, defined as the ability to faithfully identify cells independent of their morphology or optical characteristics. In this study, we present a new algorithm, Omnipose, which accurately segments samples that present significant challenges to current algorithms, including mixed bacterial cultures, antibiotic-treated cells, and cells of extended or branched morphology. We show that Omnipose achieves generality and performance beyond leading algorithms and its predecessor, Cellpose, by virtue of unique neural network outputs such as the gradient of the distance field. Finally, we demonstrate the utility of Omnipose in the characterization of extreme morphological phenotypes that arise during interbacterial antagonism and on the segmentation of non-bacterial objects. Our results distinguish Omnipose as a uniquely powerful tool for answering diverse questions in bacterial cell biology.

Advances in microscopy hold great promise for allowing quantitative and precise measurement of morphological and molecular phenomena at the single-cell level in bacteria; however, the potential of this approach is ultimately limited by the availability of methods to faithfully segment cells independent of their morphological or optical characteristics. Here, we present Omnipose, a deep neural network image-segmentation algorithm. Unique network outputs such as the gradient of the distance field allow Omnipose to accurately segment cells on which current algorithms, including its predecessor, Cellpose, produce errors. We show that Omnipose achieves unprecedented segmentation performance on mixed bacterial cultures, antibiotic-treated cells and cells of elongated or branched morphology. Furthermore, the benefits of Omnipose extend to non-bacterial subjects, varied imaging modalities and three-dimensional objects. Finally, we demonstrate the utility of Omnipose in the characterization of extreme morphological phenotypes that arise during interbacterial antagonism. Our results distinguish Omnipose as a powerful tool for characterizing diverse and arbitrarily shaped cell types from imaging data.

Sex determination in Drosophila melanogaster is under the control of the X chromosome:autosome ratio and at least four major regulatory genes: transformer (tra), transformer-2 (tra-2), doublesex (dsx) and intersex (ix). Attention is focused here on the roles of these four loci in sex determination. By examining the sexual phenotype of clones of homozygous mutant cells produced by mitotic recombination in flies heterozygous for a given recessive sex-determination mutant, we have shown that the tra, tra-2 and dsx loci determine sex in a cell-autonomous manner. The effect of removing the wild-type allele of each locus (by mitotic recombination) at a number of times during development has been used to determine when the wild-type alleles of the tra, tra-2 and dsx loci have been transcribed sufficiently to support normal sexual development. The wild-type alleles of all three loci are needed into the early pupal period for normal sex determination in the cells that produce the sexually dimorphic (in pigmentation) cuticle of the fifth and sixth dorsal abdominal segments. tra(+) and tra-2(+) cease being needed shortly before the termination of cell division in the abdomen, whereas dsx(+) is required at least until the end of division. By contrast, in the foreleg, the wild-type alleles of tra(+) and tra-2(+) have functioned sufficiently for normal sexual differentiation to occur by about 24 to 48 hours before pupariation, but dsx(+) is required in the foreleg at least until pupariation.--A comparison of the phenotypes produced in mutant/deficiency and homozygous mutant-bearing flies shows that dsx, tra-2 and tra mutants result in a loss of wild-type function and probably represent null alleles at these genes.-All possible homozygous doublemutant combinations of ix, tra-2 and dsx have been constructed and reveal a clear pattern of epistasis: dsx > tra, tra-2 > ix. We conclude that these genes function in a single pathway that determines sex. The data suggest that these mutants are major regulatory loci that control the batteries of genes necessary for the development of many, and perhaps all, secondary sexual characteristics.-The striking similarities between the properties of these loci and those of the homeotic loci that determine segmental and subsegmental specialization during development suggest that the basic mechanisms of regulation are the same in the two situations. The phenotypes and interactions of these sex-determination mutants provide the basis for the model of how the wild-type alleles of these loci act together to effect normal sex determination. Implications of these observations for the function of other homeotic loci are discussed.

Under certain conditions, regenerative voltage spikes can be initiated locally in the dendrites of CA1 pyramidal neurons. These are interesting events that could potentially provide neurons with additional computational abilities. Using whole-cell dendritic recordings from the distal apical trunk and proximal tuft regions and realistic computer modeling, we have determined that highly synchronized and moderately clustered inputs are required for dendritic spike initiation: approximately 50 synaptic inputs spread over 100 mum of the apical trunk/tuft need to be activated within 3 msec. Dendritic spikes are characterized by a more depolarized voltage threshold than at the soma [-48 +/- 1 mV (n = 30) vs -56 +/- 1 mV (n = 7), respectively] and are mainly generated and shaped by dendritic Na+ and K+ currents. The relative contribution of AMPA and NMDA currents is also important in determining the actual spatiotemporal requirements for dendritic spike initiation. Once initiated, dendritic spikes can easily reach the soma, but their propagation is only moderately strong, so that it can be modulated by physiologically relevant factors such as changes in the V(m) and the ionic composition of the extracellular solution. With effective spike propagation, an extremely short-latency neuronal output is produced for greatly reduced input levels. Therefore, dendritic spikes function as efficient detectors of specific input patterns, ensuring that the neuronal response to high levels of input synchrony is a precisely timed action potential output.

Onconase (ONC) is a member of the ribonuclease A superfamily that is toxic to cancer cells in vitro and in vivo. ONC is now in Phase IIIb clinical trials for the treatment of malignant mesothelioma. Internalization of ONC to the cytosol of cancer cells is essential for its cytotoxic activity, despite the apparent absence of a cell-surface receptor protein. Endocytosis and cytotoxicity do, however, appear to correlate with the net positive charge of ribonucleases. To dissect the contribution made by the endogenous arginine and lysine residues of ONC to its cytotoxicity, 22 variants were created in which cationic residues were replaced with alanine. Variants with the same net charge (+2 to +5) as well as equivalent catalytic activity and conformational stability were found to exhibit large (> 10-fold) differences in toxicity for the cells of a human leukemia line. In addition, a more cationic ONC variant could be either much more or much less cytotoxic than a less cationic variant, again depending on the distribution of its cationic residues. The endocytosis of variants with widely divergent cytotoxic activity was quantified by flow cytometry using a small-molecule fluorogenic label, and was found to vary by twofold or less. This small difference in endocytosis did not account for the large difference in cytotoxicity, implicating the distribution of cationic residues as being critical for lipid-bilayer translocation subsequent to endocytosis. This finding has fundamental implications for understanding the interaction of ribonucleases and other proteins with mammalian cells.

Memory guides the choices an animal makes across widely varying conditions in dynamic environments. Consequently, the most adaptive choice depends on the options available. How can a single memory support optimal behavior across different sets of choice options? We address this using olfactory learning in Drosophila. Even when we restrict an odor-punishment association to a single set of synapses using optogenetics, we find that flies still show choice behavior that depends on the options it encounters. Here we show that how the odor choices are presented to the animal influences memory recall itself. Presenting two similar odors in sequence enabled flies to not only discriminate them behaviorally but also at the level of neural activity. However, when the same odors were encountered as solitary stimuli, no such differences were detectable. These results show that memory recall is not simply a comparison to a static learned template, but can be adaptively modulated by stimulus dynamics.

Behavioral neuroscience faces two conflicting demands: long-duration recordings from large neural populations and unimpeded animal behavior. To meet this challenge we developed ONIX, an open-source data acquisition system with high data throughput (2 GB s) and low closed-loop latencies (<1 ms) that uses a 0.3-mm thin tether to minimize behavioral impact. Head position and rotation are tracked in three dimensions and used to drive active commutation without torque measurements. ONIX can acquire data from combinations of passive electrodes, Neuropixels probes, head-mounted microscopes, cameras, three-dimensional trackers and other data sources. We performed uninterrupted, long (~7 h) neural recordings in mice as they traversed complex three-dimensional terrain, and multiday sleep-tracking recordings (~55 h). ONIX enabled exploration with similar mobility as nonimplanted animals, in contrast to conventional tethered systems, which have restricted movement. By combining long recordings with full mobility, our technology will enable progress on questions that require high-quality neural recordings during ethologically grounded behaviors.

Insect neural systems are a promising source of inspiration for new navigation algorithms, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral and neural imaging experiments as well as the mapping of detailed connectivity of neural structures. General mechanisms for learning orientation in the central complex (CX) of Drosophila have been investigated previously; however, it is unclear how these underlying mechanisms extend to cases where there is translation through an environment (beyond only rotation), which is critical for navigation in robotic systems. Here, we develop a CX neural connectivity-constrained model that performs sensor fusion, as well as unsupervised learning of visual features for path integration; we demonstrate the viability of this circuit for use in robotic systems in simulated and physical environments. Furthermore, we propose a theoretical understanding of how distributed online unsupervised network weight modification can be leveraged for learning in a trajectory through an environment by minimizing orientation estimation error. Overall, our results may enable a new class of CX-derived low power robotic navigation algorithms and lead to testable predictions to inform future neuroscience experiments.

A group leader decided that his lab would share the fluorescent dyes they create, for free and without authorship requirements. Nearly 12,000 aliquots later, he reveals what has happened since.

New technologies for monitoring and manipulating the nervous system promise exciting biology but pose challenges for analysis and computation. Solutions can be found in the form of modern approaches to distributed computing, machine learning, and interactive visualization. But embracing these new technologies will require a cultural shift: away from independent efforts and proprietary methods and toward an open source and collaborative neuroscience.