Bacteroidetes are a phylum of Gram-negative bacteria abundant in mammalian-associated polymicrobial communities, where they impact digestion, immunity, and resistance to infection. Despite the extensive competition at high cell density that occurs in these settings, cell contact-dependent mechanisms of interbacterial antagonism, such as the type VI secretion system (T6SS), have not been defined in this group of organisms. Herein we report the bioinformatic and functional characterization of a T6SS-like pathway in diverse Bacteroidetes. Using prominent human gut commensal and soil-associated species, we demonstrate that these systems localize dynamically within the cell, export antibacterial proteins, and target competitor bacteria. The Bacteroidetes system is a distinct pathway with marked differences in gene content and high evolutionary divergence from the canonical T6S pathway. Our findings offer a potential molecular explanation for the abundance of Bacteroidetes in polymicrobial environments, the observed stability of Bacteroidetes in healthy humans, and the barrier presented by the microbiota against pathogens.

Inference-based decision-making, which underlies a broad range of behavioral tasks, is typically studied using a small number of handcrafted models. We instead enumerate a complete ensemble of strategies that could be used to effectively, but not necessarily optimally, solve a dynamic foraging task. Each strategy is expressed as a behavioral "program" that uses a limited number of internal states to specify actions conditioned on past observations. We show that the ensemble of strategies is enormous-comprising a quarter million programs with up to five internal states-but can nevertheless be understood in terms of algorithmic "mutations" that alter the structure of individual programs. We devise embedding algorithms that reveal how mutations away from a Bayesian-like strategy can diversify behavior while preserving performance, and we construct a compositional description to link low-dimensional changes in algorithmic structure with high-dimensional changes in behavior. Together, this work provides an alternative approach for understanding individual variability in behavior across animals and tasks.

Until recent advancements in genome editing via CRISPR/Cas9 technology, understanding protein function typically involved artificially overexpressing proteins of interest. Despite that CRISPR/Cas9 has ushered in a new era of possibilities for modifying endogenous genes with labeling tags (knock-in) to more accurately study proteins under physiological conditions, the technique is largely underutilized due to its tedious, multi-step process. Here we outline a homologous recombination system (FAST-HDR) to be used in combination with CRISPR/Cas9 that significantly simplifies and accelerates this process while introducing multiplexing to allow live-cell studies of 3 endogenous proteins within the same cell line. Furthermore, the recombination vectors are assembled in a single reaction that is enhanced for eliminating false positives and reduces the overall creation time for the knockin cell line from ~8 weeks to <15 days. Finally, the system utilizes a modular construction to allow for seamlessly swapping labeling tags to ensure flexibility according to the area under study. We validated this new methodology by developing advanced cell lines with 3 fluorescent-labeled endogenous proteins that support high-content phenotypic drug screening without using antibodies or exogenous staining. Therefore, Fast-HDR cell lines provide a robust alternative for studying multiple proteins of interest in live cells without artificially overexpressing labeled proteins.

Animal behaviour arises from computations in neuronal circuits, but our understanding of these computations has been frustrated by the lack of detailed synaptic connection maps, or connectomes. For example, despite intensive investigations over half a century, the neuronal implementation of local motion detection in the insect visual system remains elusive. Here we develop a semi-automated pipeline using electron microscopy to reconstruct a connectome, containing 379 neurons and 8,637 chemical synaptic contacts, within the Drosophila optic medulla. By matching reconstructed neurons to examples from light microscopy, we assigned neurons to cell types and assembled a connectome of the repeating module of the medulla. Within this module, we identified cell types constituting a motion detection circuit, and showed that the connections onto individual motion-sensitive neurons in this circuit were consistent with their direction selectivity. Our results identify cellular targets for future functional investigations, and demonstrate that connectomes can provide key insights into neuronal computations.

We have developed a miniature telemetry system that captures neural, EMG, and acceleration signals from a freely moving insect and transmits the data wirelessly to a remote digital receiver. The system is based on a custom low-power integrated circuit that amplifies and digitizes four biopotential signals as well as three acceleration signals from an off-chip MEMS accelerometer, and transmits this information over a wireless 920-MHz telemetry link. The unit weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts.

Electrons, because of their strong interaction with matter, produce high-resolution diffraction patterns from tiny 3D crystals only a few hundred nanometers thick in a frozen-hydrated state. This discovery offers the prospect of facile structure determination of complex biological macromolecules, which cannot be coaxed to form crystals large enough for conventional crystallography or cannot easily be produced in sufficient quantities. Two potential obstacles stand in the way. The first is a phenomenon known as dynamical scattering, in which multiple scattering events scramble the recorded electron diffraction intensities so that they are no longer informative of the crystallized molecule. The second obstacle is the lack of a proven means of de novo phase determination, as is required if the molecule crystallized is insufficiently similar to one that has been previously determined. We show with four structures of the amyloid core of the Sup35 prion protein that, if the diffraction resolution is high enough, sufficiently accurate phases can be obtained by direct methods with the cryo-EM method microelectron diffraction (MicroED), just as in X-ray diffraction. The success of these four experiments dispels the concern that dynamical scattering is an obstacle to ab initio phasing by MicroED and suggests that structures of novel macromolecules can also be determined by direct methods.

BACKGROUND: Female sexual receptivity offers an excellent model for complex behavioral decisions. The female must parse her own reproductive state, the external environment, and male sensory cues to decide whether to copulate. In the fly Drosophila melanogaster, virgin female receptivity has received relatively little attention, and its neural circuitry and individual behavioral components remain unmapped. Using a genome-wide neuronal RNAi screen, we identify a subpopulation of neurons responsible for pausing, a novel behavioral aspect of virgin female receptivity characterized in this study.

RESULTS: We show that Abdominal-B (Abd-B), a homeobox transcription factor, is required in developing neurons for high levels of virgin female receptivity. Silencing adult Abd-B neurons significantly decreased receptivity. We characterize two components of receptivity that are elicited in sexually mature females by male courtship: pausing and vaginal plate opening. Silencing Abd-B neurons decreased pausing but did not affect vaginal plate opening, demonstrating that these two components of female sexual behavior are functionally separable. Synthetic activation of Abd-B neurons increased pausing, but male courtship song alone was not sufficient to elicit this behavior.

CONCLUSIONS: Our results provide an entry point to the neural circuit controlling virgin female receptivity. The female integrates multiple sensory cues from the male to execute discrete motor programs prior to copulation. Abd-B neurons control pausing, a key aspect of female sexual receptivity, in response to male courtship.

Down syndrome (DS) is a genetic disorder that causes cognitive impairment. The staggering effects associated with an extra copy of human chromosome 21 (HSA21) complicates mechanistic understanding of DS pathophysiology. We examined the neuron-astrocyte interplay in a fully recapitulated HSA21 trisomy cellular model differentiated from DS-patient-derived induced pluripotent stem cells (iPSCs). By combining calcium imaging with genetic approaches, we discovered the functional defects of DS astroglia and their effects on neuronal excitability. Compared with control isogenic astroglia, DS astroglia exhibited more-frequent spontaneous calcium fluctuations, which reduced the excitability of co-cultured neurons. Furthermore, suppressed neuronal activity could be rescued by abolishing astrocytic spontaneous calcium activity either chemically by blocking adenosine-mediated signaling or genetically by knockdown of inositol triphosphate (IP3) receptors or S100B, a calcium binding protein coded on HSA21. Our results suggest a mechanism by which DS alters the function of astrocytes, which subsequently disturbs neuronal excitability.

Circulating tumor cells (CTCs) are critical biomarkers for predicting therapy response and survival in breast cancer patients. Multicellular CTC clusters exhibit enhanced metastatic potential, yet their detection and characterization are constrained by low frequency in blood samples and reliance on labor-intensive manual analysis. Advancing these methods could significantly improve prognostic evaluation and therapeutic strategies.Leveraging FDA-approved CellSearch technology and single-cell sequencing, we analyzed 2, 853 blood specimens, longitudinally collected from 1358 patients with advanced cancer (breast, prostate, etc) and other diseases. Integrating machine learning and deep learning tools, we developed a novel CTCpose platform to automate detection and analysis of CTCs, immune cells, and their interactions. Using artificial intelligence (AI)-driven image analysis, we extracted over 270 cellular and nuclear features including intensity, morphometry, fourier shape, gradient/edge, and haralick of cytokeratin, CD45, and DAPI expression patterns, enabling precise characterization of CTCs, white blood cells (WBCs), CTC clusters, and their interactions with immune cells (WBCs).The CTCpose platform enabled automated identification of CTCs, WBCs, homotypic CTC clusters, heterogenous CTC-WBC clusters, and immune cell clusters, providing comprehensive insights into cell morphology, biomarker expression, and spatial organization. These features correlated with patient survival, disease progression, and treatment response. Our findings highlight the clinical significance of CTC-immune cell interactions and dynamic alterations of CTCs (singles and clusters) and underscore their potential in stratifying patients into distinct risk categories.This study demonstrates the transformative potential of deep learning in overcoming limitations of traditional CTC detection methods and integrating imaging data with large cohorts of patient data. By automating and enhancing the analysis of CTC-immune cell interactions, we present a robust framework for developing predictive models with direct clinical relevance. This work opens avenues for personalized treatment strategies, underscoring the impact of AI in advancing precision oncology.Yuanfei Sun, Joshua R. Squires, Andrew Hoffmann, Youbin Zhang, Allegra Minor, Anmol Singh, David Scholten, Chengsheng Mao, Yuan Luo, Deyu Fang, William J. Gradishar, Massimo Cristofanilli, Carsen Stringer, Huiping Liu. Deep learning enables automated detection of circulating tumor cell-immune cell interactions with prognostic insights in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2420.