Dietary restriction increases the longevity of many organisms but the cell signaling and organellar mechanisms underlying this capability are unclear. We demonstrate that to permit long-term survival in response to sudden glucose depletion, yeast cells activate lipid-droplet (LD) consumption through micro-lipophagy (µ-lipophagy), in which fat is metabolized as an alternative energy source. AMP-activated protein kinase (AMPK) activation triggered this pathway, which required Atg14p. More gradual glucose starvation, amino acid deprivation or rapamycin did not trigger µ-lipophagy and failed to provide the needed substitute energy source for long-term survival. During acute glucose restriction, activated AMPK was stabilized from degradation and interacted with Atg14p. This prompted Atg14p redistribution from ER exit sites onto liquid-ordered vacuole membrane domains, initiating µ-lipophagy. Our findings that activated AMPK and Atg14p are required to orchestrate µ-lipophagy for energy production in starved cells is relevant for studies on aging and evolutionary survival strategies of different organisms.

Macrophage fusion resulting in the formation of multinucleated giant cells occurs in a variety of chronic inflammatory diseases, yet the mechanism responsible for initiating macrophage fusion is unknown. Here, we used live cell imaging to show that actin-based protrusions at the leading edge initiate macrophage fusion. Phase contrast video microscopy demonstrated that in the majority of events, short protrusions (3 ± 1 μm) between two closely apposed cells initiated fusion, but occasionally we observed long protrusions (16 ± 7 μm). Using macrophages isolated from LifeAct mice and imaging with lattice light sheet microscopy, we further found that fusion-competent actin-based protrusions formed at sites enriched in podosomes. Inducing fusion in mixed populations of GFP- and mRFP-LifeAct macrophages showed rapid spatial overlap between GFP and RFP signal at the site of fusion. Cytochalasin B strongly reduced fusion and when rare fusion events occurred, protrusions were not observed. Fusion of macrophages deficient in Wiskott-Aldrich syndrome protein and Cdc42, key molecules involved in the formation of actin-based protrusions and podosomes, was also impaired both in vitro and in vivo. Finally, inhibiting the activity of the Arp2/3 complex decreased fusion and podosome formation. Together these data indicate that an actin-based protrusion formed at the leading edge macrophage fusion.

Understanding complex biological systems requires visualizing structures and processes deep within living organisms. We developed a compact adaptive optics module and incorporated it into two- and three-photon fluorescence microscopes, to measure and correct tissue-induced aberrations. We resolved synaptic structures in deep cortical and subcortical areas of the mouse brain, and demonstrated high-resolution imaging of neuronal structures and somatosensory-evoked calcium responses in the mouse spinal cord at unprecedented depths in vivo.

Understanding complex biological systems requires visualizing structures and processes deep within living organisms. We developed a compact adaptive optics module and incorporated it into two- and three-photon fluorescence microscopes, to measure and correct tissue-induced aberrations. We resolved synaptic structures in deep cortical and subcortical areas of the mouse brain, and demonstrated high-resolution imaging of neuronal structures and somatosensory-evoked calcium responses in the mouse spinal cord at great depths in vivo.

Mycobacteria possess a multi-layered cell wall that requires extensive remodelling during cell division. We investigated the role of an amidase_3 domain-containing N-acetylmuramyl-L-alanine amidase, a peptidoglycan remodelling enzyme implicated in cell division. We demonstrated that deletion of MSMEG_6281 (Ami1) in Mycobacterium smegmatis resulted in the formation of cellular chains, illustrative of cells that were unable to complete division. Suprisingly, viability in the Δami1 mutant was maintained through atypical lateral branching, the products of which proceeded to form viable daughter cells. We showed that these lateral buds resulted from mislocalization of DivIVA, a major determinant in facilitating polar elongation in mycobacterial cells. Failure of Δami1 mutant cells to separate also led to dysregulation of FtsZ ring bundling. Loss of Ami1 resulted in defects in septal peptidoglycan turnover with release of excess cell wall material from the septum or newly born cell poles. We noted signficant accumulation of 3-3 crosslinked muropeptides in the Δami1 mutant. We further demonstrated that deletion of ami1 leads to increased cell wall permeability and enhanced susceptiblity to cell wall targeting antibiotics. Collectively, these data provide novel insight on cell division in actinobacteria and highlights a new class of potential drug targets for mycobacterial diseases.

Animals can perform complex and purposeful behaviors by executing simpler movements in flexible sequences. It is particularly challenging to analyze behavior sequences when they are highly variable, as is the case in language production, certain types of birdsong and, as in our experiments, flies grooming. High sequence variability necessitates rigorous quantification of large amounts of data to identify organizational principles and temporal structure of such behavior. To cope with large amounts of data, and minimize human effort and subjective bias, researchers often use automatic behavior recognition software. Our standard grooming assay involves coating flies in dust and videotaping them as they groom to remove it. The flies move freely and so perform the same movements in various orientations. As the dust is removed, their appearance changes. These conditions make it difficult to rely on precise body alignment and anatomical landmarks such as eyes or legs and thus present challenges to existing behavior classification software. Human observers use speed, location, and shape of the movements as the diagnostic features of particular grooming actions. We applied this intuition to design a new automatic behavior recognition system (ABRS) based on spatiotemporal features in the video data, heavily weighted for temporal dynamics and invariant to the animal’s position and orientation in the scene. We use these spatiotemporal features in two steps of supervised classification that reflect two time-scales at which the behavior is structured. As a proof of principle, we show results from quantification and analysis of a large data set of stimulus-induced fly grooming behaviors that would have been difficult to assess in a smaller dataset of human-annotated ethograms. While we developed and validated this approach to analyze fly grooming behavior, we propose that the strategy of combining alignment-invariant features and multi-timescale analysis may be generally useful for movement-based classification of behavior from video data.

Advances in neuro-technology for mapping, manipulating, and monitoring molecularly defined cell types are rapidly advancing insight into neural circuits that regulate appetite. Here, we review these important tools and their applications in circuits that control food seeking and consumption. Technical capabilities provided by these tools establish a rigorous experimental framework for research into the neurobiology of hunger.

The training of deep neural networks is a high-dimension optimization problem with respect to the loss function of a model. Unfortunately, these functions are of high dimension and non-convex and hence difficult to characterize. In this paper, we empirically investigate the geometry of the loss functions for state-of-the-art networks with multiple stochastic optimization methods. We do this through several experiments that are visualized on polygons to understand how and when these stochastic optimization methods find minima.

Intracellular levels of the amino acid aspartate are responsive to changes in metabolism in mammalian cells and can correspondingly alter cell function, highlighting the need for robust tools to measure aspartate abundance. However, comprehensive understanding of aspartate metabolism has been limited by the throughput, cost, and static nature of the mass spectrometry (MS)-based measurements that are typically employed to measure aspartate levels. To address these issues, we have developed a green fluorescent protein (GFP)-based sensor of aspartate (jAspSnFR3), where the fluorescence intensity corresponds to aspartate concentration. As a purified protein, the sensor has a 20-fold increase in fluorescence upon aspartate saturation, with dose-dependent fluorescence changes covering a physiologically relevant aspartate concentration range and no significant off target binding. Expressed in mammalian cell lines, sensor intensity correlated with aspartate levels measured by MS and could resolve temporal changes in intracellular aspartate from genetic, pharmacological, and nutritional manipulations. These data demonstrate the utility of jAspSnFR3 and highlight the opportunities it provides for temporally resolved and high-throughput applications of variables that affect aspartate levels.

Ends-out gene targeting allows seamless replacement of endogenous genes with engineered DNA fragments by homologous recombination, thus creating designer "genes" in the endogenous locus. Conventional gene targeting in Drosophila involves targeting with the preintegrated donor DNA in the larval primordial germ cells. Here we report G: ene targeting during O: ogenesis with L: ethality I: nhibitor and C: RISPR/Cas (Golic+), which improves on all major steps in such transgene-based gene targeting systems. First, donor DNA is integrated into precharacterized attP sites for efficient flip-out. Second, FLP, I-SceI, and Cas9 are specifically expressed in cystoblasts, which arise continuously from female germline stem cells, thereby providing a continual source of independent targeting events in each offspring. Third, a repressor-based lethality selection is implemented to facilitate screening for correct targeting events. Altogether, Golic+ realizes high-efficiency ends-out gene targeting in ovarian cystoblasts, which can be readily scaled up to achieve high-throughput genome editing.