AI News Archive: July 4, 2026 — Part 6
Sourced from 500+ daily AI sources, scored by relevance.
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- The role of stridulations during the mating of Nicrophorus vespilloides
In many insect species, mating is coordinated through multimodal signaling, yet less obvious channels are often overlooked. In the burying beetle Nicrophorus vespilloides, chemical communication is well-documented, but the role of substrate-borne vibrational signals (stridulations) during courtship remains unknown. We investigated whether stridulation is essential for mating success through two sets of experiments. First, we found a positive correlation between the frequency of stridulations and both the number and duration of copulation events. Second, we employed a silencing experiment to test the necessity of these signals by silencing males, females, or both partners. We found no significant differences between silenced and control groups regarding the frequency or duration of physical contact and mounting events, suggesting that stridulation is not required for mate recognition or the initiation of courtship. However, the proportion of successful copulations relative to mounting events was significantly lower when females were silenced. These results suggest that while N. vespilloides relies on a redundant multimodal system that likely utilizes chemical cues to initiate mating, vibrational signals, particularly from the female, may play a critical role in facilitating successful copulation. This study provides the first evidence for the role of stridulation in the mating behavior of N. vespilloides and highlights the potential for female-mediated vibrational signaling in burying beetle courtship.
- TRIOPS: A deep learning framework for prediction of T cell receptor-MHC binding specificity
T cell receptor (TCR) recognition is MHC-restricted, yet accurately predicting a TCR's restricting HLA allele remains an open problem. We present TRIOPS, a dual-branch convolutional model with soft cross-attention that predicts TCR-MHC restriction from amino acid sequence alone. TRIOPS uses cross-reactivity-aware negative sampling by HLA pseudosequence similarity to reduce allele-boundary label noise, extending prediction to alleles absent from training. TRIOPS reaches a held-out AUC of 0.97 for paired TCR; and 0.92 for TCR-only inputs, generalizes to unseen receptors and HLA alleles, and after locus-specific calibration, assigns TCR clonotypes to their likeliest restricting allele across an individual's HLA genotype. In TCGA tumors, TCR repertoires preferentially engage the expression-lost allele at HLA-A and HLA-B and the retained allele at HLA-C, recapitulating from bulk tumor RNA-seq the allele specific HLA loss previously linked to immune escape.
- Connectome quality converges predictably to reveal optimal stopping points during proofreading
Volumetric electron microscopy (EM) has become a critical approach to generating high-resolution reconstructions of brain tissue. As the size of EM volumes increase, use of automated image segmentation within the reconstruction pipeline has become essential, although it generates errors that need correction. The proofreading and correcting of these errors has since become the dominant cost driver in the pipeline, but precisely estimating the sufficient number of proofreading edits to enable meaningful scientific analyses of the reconstructed neuronal networks remains a challenge. We present a fast, computationally inexpensive way to estimate the progress of a connectomic proofreading effort without requiring a priori knowledge of ground truth. We show that simple global graph invariants converge predictably to asymptotic limits with increasing numbers of proofreading edits, informing a quantitative "pencils down" criterion for proofreading completeness. We illustrate our method on two datasets in different stages of proofreading progress, a zebrafish spinal cord and the hemibrain Drosophila melanogaster dataset. Our method reduces the uncertainty associated with the planning and prioritization of proofreading activities and enables data owners to accurately predict and budget the amount of proofreading necessary for their scientific questions.
- Multimodal molecular profiling of the metabolic penumbra in hyperacute stroke
Background The ischemic penumbra, a metabolically compromised yet potentially salvageable region surrounding the ischemic core, is a prime target for acute stroke intervention. Yet an objective molecular definition of the penumbra, particularly during the earliest stages of ischemia, remains lacking. Methods and Results We applied principal component analysis (PCA) followed by k-means clustering to high-resolution mass spectrometry imaging data covering multiple metabolic pathways to identify a metabolically defined penumbra in a mouse model of hyperacute stroke (45 min middle cerebral artery occlusion, MCAO). Targeted spatial metabolomic profiling by matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI) reveals a distinct penumbral metabolic profile, marked by relative preservation of high-energy phosphates, comparable lactate accumulation, and reduced succinate accumulation relative to the core. Spatial transcriptomics revealed selective induction of immediate-early genes, including Npas4, Fos and Junb, within the penumbra. Consistently, imaging mass cytometry shows enrichment of phospho-histone H3 (pHH3) within the penumbra, suggesting a chromatin-associated response potentially linked to immediate-early gene activation. Conclusion Together, these findings provide a multimodal molecular atlas of the hyperacute metabolically defined penumbra and reveal molecular features that facilitates its identification and inform future therapeutic strategies.
- CryoROLE: describing large inter-domain rotation in single particle cryo-EM
In single particle cryo-EM, analysis of continuous conformational heterogeneity has always been challenging. Both linear and deep learning-based methods treat conformational heterogeneity as perturbations to the consensus average conformation, limiting their capability in analyzing large protein motions. While classic conformational classifications are capable of handling large domain motion, they bin continuous protein dynamics into discrete static substates. Here, we present cryoROLE, a computational tool that extracts the continuous conformational dynamics embedded in the static composite map constructed from multi-body refinement into a landscape of relative orientation between the moving domains. Depicted in real space, the landscape allows intuitive interpretations of domain motion and the population of poses in the conformational space. Applying it to various biological systems reveals hidden conformational dynamics that are relevant to protein functions.
- Connectome-scale self-supervised representation learning reveals neuronal organization beyond canonical labels
Dense electron-microscopy connectomes provide synaptic-resolution maps of neuronal structure and wiring, but learning scalable representations that integrate structure and connectivity for connectome discovery with minimal human intervention remains difficult. Here we present a self-supervised framework for structure-connectivity representation learning in dense connectomes. A hierarchical graph neural network with skeleton decomposition enables contrastive learning from finely sampled FlyWire neuronal skeletons, showing that fine skeletons preserve substantially richer identity information than coarse representations. Coordinate-free topology reduces developmental and geometric confounds, improving clustering and label-efficient inference. We then use learned structural embeddings as continuous descriptors of synaptic partners to construct structure-driven connectivity representations, improving subtype discrimination without predefined partner-type labels. Iterative multi-hop learning further reveals higher-order organization, including hemispheric connectivity lateralization and connectivity-defined subgroups. Attention analysis links these differences to specific synaptic partners. Together, these results establish a self-supervised and scalable framework for discovering neuronal identity and connectome organization in a large-scale dense connectome.
- Direct comparison of CRISPR knockout and interference with Perturb-seq
CRISPR knockout (CRISPRko) and CRISPR interference (CRISPRi) are two workhorse technologies for loss-of-function studies, yet direct comparisons between the two are scant relative to their widespread adoption. Here, we establish benchmarking libraries for Cas9-based CRISPRko and CRISPRi screens using Perturb-seq as the read-out. For both modalities, we observe consistent transcriptional signatures among cells with the same genes perturbed, strong evidence of on-target signal. We also examine tradeoffs between modalities: while CRISPRi guides demonstrate heightened rates of off-target activity, we also observe artifacts stemming from the cellular response to double-stranded breaks with the use of CRISPRko. The libraries and analyses presented here will be a useful benchmarking and de-risking resource for any group preparing for a large-scale Perturb-seq screen.
- Oxytocin receptor dysfunction during neurodevelopment programs lasting pain hypersensitivity and sex-specific cognitive deficits
Early life stress (ELS), modeled in rodents through neonatal maternal separation (NMS), induces lasting behavioral and molecular alterations including pain hypersensitivity, anxiety-like behaviors, and cognitive deficits. While NMS disrupts the oxytocinergic system, the specific contribution of oxytocin receptor (OTR) dysfunction during critical neurodevelopmental periods remains unclear. Here, we investigated whether neonatal OTR blockade alone could recapitulate key features of the NMS phenotype. Control rats received daily injections of the selective OTR antagonist d(CH2)5-Tyr(Me)-[Orn8]-vasotocin (dOVT) during postnatal days 2-12, matching the NMS period. At adulthood, behavioral assessments revealed that control+dOVT animals exhibited mechanical and cold thermal hypersensitivity similar to NMS rats, though hot thermal sensitivity was unaffected. Anxiety-like behaviors observed in NMS animals were not reproduced by dOVT treatment. Notably, sex-specific spatial memory deficits emerged: male NMS and female control+dOVT rats showed impaired object location recognition, while females and males in their respective opposite groups remained unaffected. Molecular analyses of spinal cord tissue revealed significant downregulation of GAD65, BDNF, and CD11b in control+dOVT animals. Chloride cotransporters NKCC1 and KCC2 exhibited sexual dimorphism with opposite changes in NMS males versus females and different responses to dOVT. These expressions yet converged on an elevated NKCC1/KCC2 ratio in both sexes, indicating compromised chloride homeostasis despite sex-divergent molecular pathways. These findings demonstrate that developmental OTR dysfunction likely contributes to nociceptive and cognitive consequences of ELS, while anxiety-like phenotypes probably involve additional mechanisms. This work highlights OTR as a critical mediator of neurodevelopmental programming and a potential therapeutic target for mitigating ELS-related disorders.
- Spatiotemporal transformation of neural data reveals representations of erroneous behaviors
Abnormal states such as erroneous behaviors are generally difficult to represent from neural data. However, such states are also known to have specific spatiotemporal features, indicating a feasibility of developing a method to focus on them. If a method can highlight these spatiotemporal features, it may effectively represent such abnormal states, helping evaluate abnormal brain functions. In the present study, we proposed the hierarchy of supported modules (HSM) to highlight spatiotemporal features that can represent abnormal states. HSM spatiotemporally transforms multidimensional neural time-series based on their spatiotemporal context. We evaluated HSM through decoding and similarity analyses using multiple publicly available datasets. In the HSM results, decoding accuracies were higher for erroneous behaviors than for normal behaviors, and similarities were lower between erroneous behaviors and normal behaviors than between normal behaviors, demonstrating the ability of HSM to capture the spatiotemporal features of erroneous behaviors. Surprisingly, many parts of these results were also present even before HSM learning, showing the virtue of HSM as a simple-to-use method. The proposed HSM method may help elucidate the mechanisms underlying erroneous behaviors.
- Structural brain alterations in autism: A large-scale voxel-based morphometry mega-analysis
Background: Previous large-scale structural MRI analyses of the brain in autism have identified gray matter (GM) differences when using region-of-interest analyses based on gross anatomical regions. However, such analyses have limited spatial specificity for localizing neuroanatomical alterations and may obscure subtle, spatially focal differences. Whole brain voxel-based morphometry (VBM) analyses enable greater spatial precision for localizing GM and white matter (WM) alterations in autism. Purpose: To rigorously identify voxel-wise GM and WM volume differences in autism in the largest VBM mega-analysis to date. Materials and Methods: This retrospective mega-analysis included structural 3D volumetric T1-weighted MRI brain scans from 3,051 participants (1,519 autism; 1,532 neurotypicals) collected across 51 sites/scanners. Voxel-wise GM and WM volumes were quantified using the ENIGMA CAT12 VBM pipeline. Linear mixed-effects regression was performed at each voxel to evaluate the association between diagnostic group and voxel-wise volume while adjusting for standard nuisance covariates Results: A total of 3,051 participants (15.0 {+/-} 8.2 yrs; 2,342 male) were included in the study. Autism was associated with widespread lower GM volume involving cortical, subcortical, and cerebellar regions. The most extensive alterations in autism were detected in the orbitofrontal cortex, amygdala, thalamus, and posterior lobes of the cerebellum. WM volume was lower in autism across major projection, commissural, association, and cerebellar/brainstem tracts, including the corona radiata, internal capsule, corpus callosum, and cerebellar peduncles. These findings remained consistent in sensitivity analyses, including the application of increasingly strict motion exclusion criteria. Conclusion: Autism is associated with smaller voxel-wise GM and WM volume involving widespread cortical, subcortical, and cerebellar regions. Our findings remained robust across supplementary analyses and provide high-resolution localization of structural brain differences in autism. These findings support the involvement of distributed neural systems underlying reward processing, sensory integration, and motor functioning in autism.
- Differential effects of piroxicam and nitroglycerine on memory and hippocampal neurochemistry in di-oestrous female rats
Abstract Objectives To evaluate and compare the neuro-behavioural safety profiles of piroxicam and nitroglycerine by investigating their differential effects on cognitive function, spatial and recognition memory, and hippocampal neurochemistry in a di-oestrous female Wistar rat model. Methods Female Wistar rats at di-oestrous were randomly assigned to receive distilled water, piroxicam, or nitroglycerine orally for four consecutive days. Following treatment, spatial and recognition memory were evaluated using standard behavioural paradigms. Hippocampal tissues were analysed for acetylcholinesterase and glutamate activity, oxidative stress markers, and neuroinflammatory indices. Results Piroxicam improved recognition memory and was associated with increased glutamatergic activity and a compensatory rise in superoxide dismutase. However, it also elicited elevated nitric oxide signaling, lipid peroxidation, and localized neuroinflammatory markers in the hippocampus. In contrast, nitroglycerine impaired non-spatial memory during di-oestrous. Although both treatments preserved working memory, they produced distinct effects on object recognition, memory discrimination, oxidative stress parameters, and neuroinflammatory mediators. Conclusions Piroxicam and nitroglycerine exert differential effects on cognition and hippocampal neurochemistry during di-oestrous. Piroxicam improved recognition memory and produced distinct hippocampal neurochemical alterations, whereas nitroglycerine impaired recognition memory. These findings highlight the influence of menstrual pain therapeutics on cognitive function and hippocampal physiology under hormonally sensitive conditions. Keywords: cognitive function; cognitive impairment; cyclooxygenase inhibitors; neuroinflammation; neurochemistry
- Peptide allosteric inhibitor of TNFR1 signaling attenuates inflammation and rheumatoid arthritis pathology in human TNF transgenic mice
Inhibition of tumor necrosis factor receptor 1 (TNFR1) represents a major therapeutic strategy for chronic autoimmune and inflammatory diseases such as rheumatoid arthritis (RA). As current anti-TNF therapies can cause adverse side effects due to global blockade of the ligand, receptor-specific inhibition of TNFR1 signaling has emerged as a highly sought-after strategy. We have recently identified a novel peptide-based allosteric inhibitor, FKC (FKCRRWQWRMKK), that targets TNFR1 conformationally active region to alter receptor conformational states and disable receptor-ligand signaling complex. Here, we evaluated the therapeutic efficacy of FKC in a human TNF (hTNF) transgenic mouse model of RA. FKC treatment improves clinical RA scores in hTNF mice, accompanied by enhanced grip strength and increased walking distance. Importantly, FKC treatment inhibits TNF/TNFR1-mediated inflammation and attenuates RA pathology in hTNF mice. Together, our findings establish FKC as a promising new class of peptide-based therapeutics for chronic inflammatory diseases through selective inhibition of TNFR1 signaling.
- Local inhibitory topology dictates the spatial compartmentalization of hippocampal sharp-wave ripples
Hippocampal sharp-wave ripples (SWRs) are essential for memory consolidation and represent among the most synchronous oscillatory events in the brain. Yet, despite their capacity for widespread synchronization, SWRs frequently remain confined to discrete hippocampal domains, revealing a paradox between global coordination and local autonomy. Here, by combining in vivo Neuropixels recordings with an experimentally constrained three-dimensional biophysical model, we show that inhibitory activity and inhibitory topology serve fundamentally distinct functions. Whereas perisomatic inhibition gates SWR generation and dendritic inhibition regulates the strength and spectral properties of ripple oscillations, the spatial organization of inhibitory connectivity establishes local computational domains that enable autonomous ripple generators to coexist. Together, our findings identify a spatial dimension of inhibition, in which inhibitory activity governs the emergence and dynamics of SWRs, while inhibitory topology determines their spatial organization and autonomy.
- Single-Molecule Imaging Reveals Differential Stability of Alpha-Synuclein Aggregates
Alpha-Synuclein (-syn) aggregation is central to Parkinson's disease (PD), yet measurements in biofluids are confounded by the coexistence of monomeric and aggregated species. Using Syn-IMAGR, a single-molecule imaging platform with sub-femtomolar sensitivity, we show that purified -syn aggregates undergo dilution-induced disassembly, revealing a concentration-dependent equilibrium. Applied to postmortem brain lysates, Syn-IMAGR distinguishes physiological -syn multimers, which are dimmer and readily dissociate upon dilution, from PD-associated aggregates, which remain detectable and exhibit greater structural resistance to disruption. These results indicate that -syn assemblies occupy distinct stability regimes, with PD-associated aggregates representing a more persistent and less dilution-sensitive structural state. Syn-IMAGR thus provides a quantitative framework for resolving -syn species and for probing their concentration-dependent equilibrium.
- Microbiome-derived Short Chain Fatty Acids modulate microglial inflammatory responses in a sex- and metabolite-specific manner
Microbes residing in the gastrointestinal tract exert immunomodulatory impacts on the brain through the gut-brain axis. Short-chain fatty acids (SCFAs) produced by bacterial fermentation of dietary fiber can enter the brain parenchyma and are implicated in microglia-mediated inflammation. While the gut microbiome is required to maintain microglial homeostasis, the mechanisms by which microbiota-derived metabolites affect microglia remains unknown. We examined the roles of SCFAs, specifically butyrate, propionate and acetate, on microglial function in response to SCFAs both in vitro using BV2 cells and in vivo in mice. We observed in vivo that SCFAs impact microglial transcriptional responses to LPS in a sex- and metabolite-specific manner with butyrate having the strongest effect. Enriched gene sets included signatures associated with LPS responsive microglia, Arg1 positive microglia, microglial cell cycle related genes and genes affiliated with changes in microglial morphology. We observed a similar effect in vitro, where metabolite administration enhanced phagocytosis, blunted proliferation and nitric oxide production. We then evaluated global histone modification levels following metabolite treatment and detected an enhancement of H3K9ac, H3K27ac, and H3K4me3 both in vivo and in BV2 cells treated with butyrate. Finally, we showed that butyrate is a potent HDAC inhibitor possibly contributing to enhanced acetylation. Hence, our findings suggest that SCFAs impact microglial function in a metabolite- and sex-specific manner, and that butyrate blunts inflammation by regulating microglial histone acetylation. Our results provide a more in-depth understanding of gut microbiome-microglia crosstalk, opening the door for new microbiome- and microglia-targeted therapies.
- The influence of virtual visual stimulus amplitude to induce standing postural responses
Upright postural control during movement relies on multisensory integration. Yet, the frequency-specific contribution of vision remains poorly characterized in virtual reality (VR). This study investigated how multi-sine visual stimulation amplitude delivered in VR influences standing postural responses. Fifteen healthy adults stood on a force plate wearing a VR headset. Visuo-postural coupling was assessed through coherence and gain analyses between a multi-sine signal (10 sinusoids, 0.12 to 1 Hz) oscillating a virtual environment in one of four amplitudes (0.5, 1, 2, 4 degrees peak-to-peak) and the anteroposterior whole-body angle. All amplitudes elicited measurable postural responses. Increasing amplitude significantly increased postural oscillation and tended to increase coherence, while gain significantly decreased. These results are consistent with a nonlinear control system. The 2 degrees amplitude elicited the largest gain with significant coherence across all stimulated frequencies, suggesting it is suitable for studying visual contributions to postural control during movement execution.
- Convergent Cysteine Enrichment in Diverse Gut Phage Capsids Suggests Gut-Associated Structural Adaptation
Background: The gut environment is hostile to life, yet the human virome, dominated by bacteriophages, persists. Adaptations to the major capsid protein (MCP) may explain this. Phage MCPs conserve the HK97 fold, ideal for detecting convergent features across phage populations. Prior capsid stability research focused on individual phages, limiting broader pattern identification. Methods: MCPs from the Gut Phage Database (GPD) (n=8,478) and INPHARED (n=4,905) were predicted using ProtPhage + Phold and clustered using MMseqs2 (GPD=902 vs INPHARED=606). Structural predictions, conservation analysis, and capsomere modeling were used to characterize cysteine environments. Results: Biochemical analysis identified cysteine enrichment in GPD MCPs. Phylogenetic mapping was consistent with convergent evolution of high-cysteine MCPs. Over 50% of cysteines were [≥]90% conserved within and between clusters. Simulated capsomeres showed 83% of cysteines are buried (RSA <10%). Conclusions: These findings suggest gut phages may have convergently evolved cysteine-based capsid stabilization, with implications for engineering therapeutic phages.
- SPICE: A Robust Computational Framework for Identifying Copy Number Variations in Spatial Transcriptomics
Copy number variation (CNV), which alters the number of genomic segments, is a major driver of intratumor heterogeneity, characterized by spatially organized and genetically distinct cell populations. Recent advances in spatially resolved transcriptomic (SRT) technologies, which profile gene expression across thousands of spatially indexed tissue locations, offer a powerful opportunity to reconstruct the CNV architecture and dissect the spatial organization of cancer subclones. Here, we introduce SPICE (spatial inference of CNV events), a probabilistic method for identifying somatic CNVs and allele-specific copy number (ASCN) profiles from SRT data. A key feature of SPICE is its ability to integrate multiple complementary information available in SRT data, including gene expression, spatial coordinates, and heterozygous SNPs inferred from transcriptomic reads, to substantially enhance the accuracy and power of CNV detection. Using datasets generated across different SRT platforms, we first assess the reliability of SNPs derived from SRT data to ensure robust downstream inference. We then demonstrate that SPICE effectively integrates these modalities to deliver accurate and spatially coherent reconstruction of CNV landscapes and subclonal architecture, while maintaining excellent control of false discoveries. Together, SPICE provides a robust and effective solution for dissecting genomic heterogeneity in SRT studies of cancer.
- HLiCA: An integrated cell atlas of the healthy human liver
The human liver is composed of a heterogeneous mix of cell types. How these distinct populations contribute individually and collectively to liver function remains poorly understood. Although single-cell technologies have advanced our understanding of liver biology, individual studies have often been limited by small donor cohorts and inconsistent cell type annotations. Integrating multiple datasets can overcome these challenges and better capture biological variability. We present the Human Liver Cell Atlas (HLiCA), an integrated reference of non-disease liver cells assembled from eight datasets across six research centers, encompassing more than 525,000 cells from 110 donors. Developed in collaboration with the Human Cell Atlas Liver Bionetwork, the HLiCA incorporates expert-curated cell annotations refined through community feedback and dedicated cell type annotation meetings. The HLiCA classifies cells into six lineages and expands the cell type resolution to include 47 distinct cell types. Starting from raw sequencing reads, we realigned all data and performed rigorous benchmarking to ensure robust integration across technical and biological variables. Genetic ancestry was inferred for all samples to evaluate the range of ancestral backgrounds represented in the atlas. The expanded cell type annotation enabled identification of previously unrecognized liver cell types, including NRXN1+ stromal cells. Their presence was validated using spatial transcriptomics, which localized NRXN1+ stromal cells to periportal regions. With the number of donors included in the HLiCA we were able to examine cell type specific associations with demographic covariates. In hepatocytes, drug metabolism genes showed differential expression between sexes, and in cholangiocytes, mucus-production genes varied with age. As the largest and most genetically diverse human liver cell atlas to date, the HLiCA provides a comprehensive, well-annotated reference for the field, annotated by expert consensus. This resource will enable deeper interrogation of liver cellular diversity, architecture, and function in the healthy human liver and serve as a reference to understand changes that occur with disease.
- From planktonic to sedentary lifestyle: Molecular dissection of the establishment and maintenance of mycobacterial biofilm
Biofilm represents a complex aggregation of bacteria embedded within a self-produced extracellular polymeric substance (EPS). We investigated the characteristics of mycobacterial biofilm using Mycobacterium smegmatis (Msm) as model organism. By combining transcriptomic (RNA-seq) and proteomic (LC-MS) analyses, the research captures dynamic changes during the establishment and maturation of the biofilm. Transcriptomics analysis showed a distinct gene expression profile as compared to its planktonic form. Interestingly, clear differences were seen between initial (~2-day old) and mature (~5-day old) biofilm stages, highlighting phasic gene expression throughout biofilm development. Marked alteration in oxidative stress-related genes and energy metabolism from ATP to NADH was observed. Furthermore, quantitative mass spectrometry-based proteome examination of EPS showed an abundance of cytoplasmic proteins present differentially between initial and mature biofilm stages. Pathway enrichment revealed enhanced oxidative stress responses and metabolic shifts in mature biofilms, including upregulation of NADH dehydrogenase and downregulation of ATP synthase, indicating altered energy metabolism. Our findings thus provide insights into the molecular adaptations, including production of mycofactocin, occurring during mycobacterial biofilm establishment and maturation, and advance our understanding of mycobacterial biofilm physiology.
- Bacillus adaptation to Pseudomonas secondary metabolites enhances its root competitiveness
Bacillus velezensis is a widely used plant growth-promoting rhizobacterium whose effectiveness under natural conditions is strongly influenced by interactions with surrounding microorganisms. While bacterial secondary metabolites are known to shape these interactions, little is known about their long-term evolutionary consequences. Here, we show that repeated exposure of B. velezensis GA1 to secondary metabolites produced by the competing rhizobacterium Pseudomonas sessilinigenes CMR12a drives the emergence of an adapted subpopulation with enhanced ecological fitness. Multi-omics analyses revealed extensive metabolomic and transcriptional changes associated with altered growth dynamics, sporulation, motility, and biofilm formation. Importantly, the evolved variant exhibited improved tomato root colonization and reduced the abundance of the competing Pseudomonas strain in planta. Together, our results demonstrate that prolonged exposure to diffusible bacterial metabolites can drive rapid adaptive diversification in rhizosphere-associated bacteria and highlight the importance of long-term interbacterial interactions in shaping the outcome of plant microbiome assembly and biocontrol performance.
- Colorectal cancers with distinct metastatic potential trigger divergent early T cell responses
Colorectal cancer (CRC) remains a leading cause of cancer mortality, with most cases refractory to immunotherapy. Distinguishing tumor-induced from steady-state mucosal T cell responses has been a critical barrier to understanding antitumor immunity in CRC. Using orthotopic transplantation of CRC organoids with and without metastatic potential, combined with temporal T cell fate-mapping, we show that non-metastatic tumors elicit early recruitment of CD8{beta}+ and CD4+ T cells that acquired cytotoxic and Th1-like programs, whereas pro-metastatic tumors induce a naive-like, hypoactivated state. Tumor-infiltrating CD4+ T cells underwent clonal expansion, including clones recognizing microbial and dietary antigens. T cells in physical contact with tumor cells, identified by uLIPSTIC, were enriched for expanded and cytotoxic clones. Fate-mapped T cells from non-metastatic tumors suppressed tumor growth in an IFN-{gamma}-dependent manner, whereas pro-metastatic tumor-derived T cells failed to do so. Mechanistically, pro-metastatic tumors downregulated MHCII, and Ciita targeting in non-metastatic organoids reduced CD4+ clonal expansion and led to tumor progression. Together, these findings define divergent early T cell trajectories associated with CRC metastatic potential, indicating that ineffective local immune engagement precedes metastatic dissemination.
- PRISM : Peptide-specificity annotation of T-cell receptors with uncertainty quantification
Mapping T-cell receptor (TCR) sequences to their cognate peptide-major histocompatibility complex (pMHC) ligands underlies both basic immunology and T-cell target discovery, yet current models aimed at predicting TCR specificity are limited by sparse labels, viral-biased training data, and an inability to recognize receptors outside their training distribution. We present PRISM, an uncertainty-aware metric-learning framework for TCR{beta} sequence representation. PRISM embeds receptors into a peptide-organized latent space, returns top-k peptides by nearest-neighbor retrieval, and abstains on out-of-distribution receptors by modeling an intrinsic uncertainty that tracks annotation correctness. To offset the viral bias of public databases, PRISM augments training data with structure-guided synthetic receptors that diversify TCR sequences while preserving the energetics of the TCR-pMHC interface. Across a held-out set of 923 peptides and the independent IMMREP23 benchmark, PRISM matches or exceeds sequence-based models, with largest gains on rare epitopes. Finally, PRISM learns attention weights on TCR residues that concentrate on the CDR3{beta} salt-bridge and hydrophobic contacts central to peptide recognition, linking PRISM's positional focus to the biochemical properties of TCR-pMHC structures.
- Microbial induction of MHC-II expression in colon cancer cells overcomes immunotherapy resistance and limits metastasis
Colorectal cancer remains a major cause of cancer mortality, and most microsatellite stable tumors derive little benefit from immune checkpoint blockade. Here, we identify a microbiome-dependent mechanism that converts immune-refractory colorectal cancer into a more immunologically responsive state. Using orthotopic mouse models spanning distinct genetic and immunologic contexts, we show that a Helicobacter-containing microbiome suppresses primary tumor growth and limits metastasis. This protective state is associated with increased intratumoral lymphocyte infiltration and stronger effector programs. Mechanistically, microbial exposure induces MHC class II expression in colon cancer cells to promote anti-tumor immunity. Tumor-intrinsic loss of CIITA abrogates microbial protection, whereas enforced CIITA expression is sufficient to increase intratumoral T cell accumulation, restrict progression and metastasis, and sensitize microsatellite-stable tumors to PD-1 and CTLA-4 blockade. In human microsatellite-stable patient-derived organoids, increased cancer-cell MHC-II enhanced interactions with autologous immune cells and increased tumor cell apoptosis. Together, these findings define a microbiome-cancer cell antigen presentation axis that restrains metastasis and overcomes immunotherapy resistance in colorectal cancer.
- Neural representation of hedonic valence during narrative listening
Hedonic valence, the intrinsic pleasantness or unpleasantness of an experience, is fundamental to human psychological functioning. Yet, how valence is represented in the brain remains an open question. Functional MRI studies have demonstrated that the brain encodes both positive and negative valence, but this evidence largely stems from experiments using simplified, controlled stimuli, such as images, sounds, or words. As a result, it remains unclear how valence is processed during rich, naturalistic experiences that more closely reflect real life. In addition, most studies adopt a single statistical model, raising concerns about the robustness of their findings. This study used a formal voxel-wise Bayesian model selection approach to test alternative statistical models supporting Bipo-larity, Valence-General, and Bivalence hypotheses to identify the most optimal model of valence representation during narrative listening. Our results provide evidence for the Bipolar model. We identified distributed brain re-gions that selectively encode valence as a bipolar continuum (negative to positive) during narrative comprehen-sion, including classical emotion-related hubs such as ventromedial prefrontal cortex, as well as regions not tradi-tionally associated with emotion processing, such as inferior occipital cortex, supramarginal cortex, inferior frontal cortex, and middle cingulate. Regions selectively encoding arousal and those broadly responsive to both valence and arousal were also identified. These findings highlight the importance of using formal model comparison and naturalistic paradigms in affective neuroscience, advancing our understanding of how valence is represented in the brain during real-world experiences.
- Cross-protocol comparison of iPSC-microglia reveals hypofunction contributes to neuronal vulnerability and synaptic alterations in the MAPT-S305N model of frontotemporal dementia.
Progressive and chronic neuroinflammation is associated with numerous neurodegenerative diseases, including primary tauopathies such as frontotemporal dementia and progressive supranuclear palsy. Unlike Alzheimer's disease, there is no clear genetic association implicating microglial dysfunction as a primary driver of tauopathy. As such, the contributions of microglia to tauopathy pathogenesis have been less well defined. Here, we explore the cell autonomous effects of the pathogenic MAPT-S305N variant on microglial function, across two distinct iPSC-microglia protocols, followed by examination of the non-cell autonomous effects of microglial MAPT genotype on neuronal health and function. We find that different protocols produce cells of equivalent microglial identity, but result in microglia in different functional states, thereby influencing reactivity and detectable phenotypes. Regardless, across both protocols we find that MAPT-S305N induces microglial hypoactivity, evidenced by impaired phagocytosis, reduced cytokine release and diminished regulation of synaptic function. We conclude that microglial hypoactivity may be an early event in disease pathogenesis, where MAPT mutation microglia fail to adequately respond to pathogenic stimuli, thereby contributing to subsequent neuronal vulnerability and susceptibility. Further studies are required to understand how and when this initial hypoactive state may switch to a toxic pro-inflammatory state, and whether early detection and correction may be of therapeutic value.
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