Protein Expression and Purification

Human Ca2+/calmodulin (CaM)-dependent protein kinase II alpha (CaMKII) is a highly abundant and conserved protein in the brain. It is a multifunctional serine/threonine kinase that phosphorylates cellular substrates across subcellular compartments, activating signaling pathways essential for long-term memory storage. However, a detailed understanding of protein structure and enzyme-substrate interaction mechanisms require a method to produce active, stable, and pure proteins at scale. Since phosphorylation can alter catalytic activity and substrate affinity, examining the non-phosphorylated state enables an unbiased characterization of basal enzymatic function. Therefore, producing the non-phosphorylated form of the kinase is important for biochemical and structural studies aimed at understanding kinase activation mechanisms. We describe a detailed protocol for the expression and high-yield purification of full-length, non-phosphorylated human CaMKII in bacterial cells. CaMKII was co-expressed with {lambda}-phosphatase to maintain it in a non-phosphorylated state. Protein expression was induced by autoinduction at low temperature to enhance the stability and solubility of CaMKII. Recombinant CaMKII was purified by Ni-NTA affinity chromatography, followed by gel filtration chromatography. Although CaMKII has been considered difficult to purify in its non-phosphorylated form, we obtained it in high yield, and the protein was predominantly non-phosphorylated. Our results show that combining co-expression with autoinduction improves both the solubility and yield of the homogeneous non-phosphorylated form of CaMKII, which could be suitable for subsequent biochemical and structural studies.

Background. Vaccines have been an essential tool in bringing the world close to polio eradication, with over 99.9 percent of the global population free of poliovirus. No antiviral drugs or monoclonal antibody products, however, are currently licensed for treatment of polio. We previously isolated a human monoclonal antibody (9H2) with potent neutralizing activity against all three poliovirus serotypes. To advance 9H2 as a therapeutic candidate, we optimized its sequence to extend serum half-life and improve manufacturability. Methods. A Multi-Attribute Method under stress conditions identified post-translational modification sites, and Abacus (Trademark) ranked sequence liabilities. Six amino acid substitutions were introduced into the variable regions, generating 23 combinatorial variants. Codon-optimized genes were synthesized and engineered into a human immunoglobulin G1 backbone containing crystallizable fragment (Fc) mutations (M428L/N434S) to extend serum half-life. Constructs were transfected into CHO K1 cells to generate stable pools in 24 well plates. Protein A purified antibodies were characterized using biophysical assays and an in vitro poliovirus neutralization assay. Results. All variants retained high in vitro neutralizing activity against poliovirus. A lead candidate was selected based on integrated assessment of biophysical properties across eight assays and expression yield. Conclusions. Structure-guided engineering and experimental evaluation enabled optimization of the 9H2 antibody sequence and identification of a lead candidate suitable for clinical manufacturing as a potential anti-poliovirus immunotherapeutic agent.

Drug targets and vaccines for bacterial diseases are challenging to develop. Computational subtractive genomics and reverse vaccinology offer a viable substitute for conventional drug and vaccine development approaches. In recent years, Pasteurella multocida, a Gram-negative pathogen responsible for severe infections in humans along with major diseases in livestock and poultry, has developed resistance to multiple drugs. As a result, there is an urgent demand for research into reliable, efficient, highly potent, and cost-effective strategies to combat the rise of Pasteurella multocida infections. To address this, the present study integrated an in silico subtractive genomics and reverse vaccinology workflow to pinpoint proteins with potential value as both drug and vaccine targets. From the complete Pasteurella multocida Pm70 proteome, we identified 446 proteins that had no similarities with human proteins, out of which 129 were found to be essential for the pathogens survival. These 129 proteins are therefore potential candidates for drug development. Further metabolic pathway analysis, virulence potential, subcellular localization, and structural analyses revealed two outer membrane proteins, namely, 47 kDa outer membrane protein and lipopolysaccharide-assembly protein LptD, as promising candidates for therapeutic development. Subsequent antigenicity analysis revealed both outer membrane proteins as potential vaccine targets, exhibiting highly favorable antigenicity scores. Candidate B- and T-cell epitopes were systematically mapped from these two targets based on antigenicity, immunogenicity, toxicity, and allergenicity potential and only high-confidence epitopes were assembled using adjuvants and class-specific linkers to construct the final multi-epitope vaccine (MEV). The designed MEV construct was demonstrated to be highly antigenic, non-toxic and non-allergenic to humans, while possessing favorable structural and physicochemical properties, and exhibited strong binding interactions with human toll-like receptors with minimal molecular deformability. Although further experimental validation is recommended to fully assess their efficacy, the present study establishes a solid foundation for the development of novel therapeutics and vaccine candidates against P. multocida, ultimately contributing to the reduction of its rising infections.

Thrombostasin is a cysteine-free anticoagulant protein produced by the horn fly Haematobia irritans, featuring an unusual stretch of seven consecutive aspartate residues within the polypeptide sequence. Here, we report the first chemical synthesis of native thrombostasin and a hepta-glutamate analogue, together with assessment of their thrombin inhibitory and anticoagulant activity.

Abstract The canonical WNT signaling pathway guides cell growth throughout the human lifespan. In adults, WNT plays an essential role in tissue homeostasis by maintaining tissue stem cells. In the intestine, the WNT transcription factor, TCF4, is necessary for stem cell maintenance. Aberrant activation of WNT signaling is generally accepted as an initiating event in colon cancer, leading to constitutive TCF4 activity. To investigate the role of this key transcription factor in global gene regulation, we abrogated TCF4 expression in colon cancer cells. Loss of TCF4 function resulted in the over-expression of the WNT transcription factor, LEF1. LEF1 was transcriptionally competent and over-compensated for TCF4 (TCF7L2) silencing in a WNT reporter assay. TCF4 enlisted the transcriptional repressor CtBP1, and bound the LEF1 promoter, indicative of direct repression. TCF4 and LEF1 drove different transcriptional programs, with TCF4 favoring MYC and cell cycle progression, while LEF1 favored immune-related gene signatures. TCF4 was the primary regulator of MYC expression, yet also the mediator of LEF1 repression, suggestive of competition centered on TCF4 transcriptional output despite the {beta}-catenin saturated colon cancer nucleus. We conclude that TCF4 has dual activator-repressor activity in colon cancer.

CRISPR base editor (BE) scanning enables sequence-level interrogation of proteins at scale in their native cellular and genomic contexts. This approach opens new opportunities to dissect cellular pathways, where signaling depends on coordinated interactions among multiple pathway proteins. We apply BE scanning to the RAS-RAF-MEK-ERK (MAPK) cascade, a central oncogenic pathway and major therapeutic target. Compounds targeting the MAPK pathway have mechanisms of action and resistance that remain incompletely characterized. By base editing 22 MAPK genes under either hyperactivation or inhibition at various nodes, we present a chemical-genetic map of the signaling pathway. Pathway-wide analysis shows that drug resistance mutations frequently occur in proteins other than the direct drug target itself, and we exploit these chemical-genetic interactions to recapitulate key pathway connections. Our BE scanning also identified underappreciated functional hotspots, including an allosteric site in the KRAS N-terminus. We also identify catalytically impaired CRAF mutants that confer bidirectional resistance and sensitization to structurally similar MEK inhibitors, distinguishing functional differences between structurally related compounds. These findings establish BE scanning as a scalable approach for network-level chemical-genetic interaction mapping, revealing new mechanistic insights into one of the most studied oncogenic pathways.

Stromal cell composition has been proposed as a potential biomarker in ductal carcinoma in situ (DCIS) for assessing the risk of subsequent recurrence or progression to invasive breast cancer (IBC). However, the characteristics of the tumor microenvironment within DCIS associated with these outcomes remain poorly understood. Here, we perform spatial transcriptomic analyses of 49 primary DCIS specimens from patients with no recurrence, DCIS recurrence, or recurrence as IBC. Cell mapping reveals spatially organized stromal cell gradients within DCIS, with enrichment of TREM2+ macrophages and myofibroblastic cancer-associated fibroblasts (myCAFs) in tumor-proximal niches. Notably, the abundance of TREM2+ macrophages near tumor nests is associated with subsequent recurrence as IBC. Moreover, ligand-receptor pair analysis identifies GRN--SORT1, SPP1--CD44, and LGALS9--CD44 interactions as spatially plausible signaling interactions between TREM2+ macrophages and epithelial cells. Finally, these findings are validated at the protein level by multiplex immunostaining of serial sections. This study characterizes the spatial landscape of the DCIS tumor microenvironment associated with subsequent recurrence, providing a basis for developing biomarkers of disease progression and identifying potential therapeutic targets.

Palmitate-associated lipotoxic stress activates the endoplasmic-reticulum stress sensor protein IRE1, but how IRE1 signaling influences genotoxic-stress responses in triple-negative breast cancer remains unclear. Here, we investigated IRE1 and XBP1 signaling in MDA-MB-231 cells exposed to palmitate and etoposide. Under combined lipotoxic and genotoxic stress, XBP1 depletion increased DNA-damage accumulation in IRE1 wild-type cells but not in IRE1-deficient cells, whereas IRE1 re-expression reduced DNA damage. Pharmacologic IRE1 RNase inhibition also increased etoposide-associated DNA damage, supporting a protective role for IRE1 RNase-dependent signaling. IRE1 status and XBP1 manipulation differentially affected H2A.X and {gamma}H2A.X abundance, indicating context-dependent regulation of chromatin-associated DNA-damage signaling. At the RNA level, H2A.X was enriched in IRE1 immunoprecipitates, and the H2A.X-linked DNA-damage-response transcripts HUWE1 and BRCA2 also associated with IRE1 under combined stress. These findings link palmitate-activated IRE1-XBP1 signaling to genome-protective responses during genotoxic stress and identify a network of IRE1-associated DNA-damage-response transcripts in triple-negative breast cancer cells. Direct IRE1-mediated cleavage of these transcripts remains to be established.

Azetidine-2-carboxylic acid (Aze) is a toxic, non-proteogenic amino acid produced in restricted plants. It can enter the human food chain through direct or indirect dietary exposure and has been linked to neurological disorders due to its ability to misincorporate for its structural analog proline (Pro) during translation and lead to protein misfolding. Although several microorganisms have evolved mechanisms to detoxify Aze, these pathways have not previously been exploited to engineer Aze tolerance in plants. Here, we heterologously expressed a bacterial Aze hydrolase (HAS) in Arabidopsis thaliana to establish a metabolic strategy for Aze detoxification in plants. Transgenic plants exhibited markedly enhanced tolerance to Aze, as demonstrated by improved root growth, cotyledon development, and survival compared with wild-type plants under Aze stress. We further showed that HAS localized to the cytosol, where it converted Aze into the non-toxic metabolite 2-hydroxy-4-aminobutyrate (HAB). HAB formation was confirmed both in planta and in vitro, demonstrating that HAS remained catalytically active in plant cells and effectively detoxified Aze. Enzyme kinetics revealed that HAS has a high affinity for Aze and is stereospecific for L-Aze, with no activity toward D-Aze. Multi-omics analysis including transcriptomics and misincorporation proteomics show that the transgenic lines misincorporate Aze significantly less compared to wild-type leading to enhanced Aze tolerance. Our findings establish bacterial HAS as an effective metabolic detoxification system that confers enhanced Aze tolerance in plants. This study provides a promising strategy for engineering plant resistance to toxic non-proteogenic amino acids.

Blooms of the toxic dinoflagellate Ostreopsis cf. ovata can cause respiratory irritation in beach users, yet their environmental drivers and temporal dynamics remain poorly understood. Here, we use a dynamical-systems approach to investigate how environmental conditions shape bloom dynamics from long-term time series of algal abundance and abiotic variables. Using the global modelling framework GPoM, we reconstruct nonlinear ordinary differential equation systems and identify candidate models capable of reproducing key features of the observed dynamics, including chaotic behaviour. Topological and statistical analyses reduce the candidate models to two systems that best capture the observed distributions and dynamical patterns. These models reveal distinct combinations of environmental conditions associated with bloom occurrence and amplitude, providing a framework for interpreting bloom trajectories and a potential basis for short-term prediction.

NF-{kappa}B must remain bound to chromatin long enough to activate innate immune genes, but what stabilizes this transcriptionally productive state is unknown. Here, we identify the Integrator complex as an essential determinant of NF-{kappa}B chromatin residence in mouse and human cells. Integrator associated with NF-{kappa}B and co-occupied its genomic targets. Single-molecule tracking revealed that Integrator markedly prolonged the chromatin residence of RELA molecules in a low-mobility state. Catalytically inactive INTS11-E203Q fully restored NF-{kappa}B-dependent transcription, separating this chromatin-retention function from RNA cleavage. Conditional Ints11 deletion abolished TLR4-dependent dendritic-cell activation in adult mice and impaired LPS-induced transcription in mouse embryonic fibroblasts. Loss of Integrator in human cancer cells similarly suppressed TNF-induced inflammatory gene expression. These findings uncover a noncatalytic function for Integrator that stabilizes NF-{kappa}B at enhancers, complementing its established catalytic control of RNA polymerase II pause release. By coupling signal recognition at enhancers to productive elongation, Integrator provides a molecular solution to a central challenge of multicellularity: converting transient extracellular cues into coherent gene-expression programs across complex chromatin landscapes.

Subcellular mass spectrometry imaging (MSI) has required specialized instrumentation and approaches. Additionally, data analysis has required expensive proprietary software, or code-based open-source tools. These barriers render spatial metabolomics less accessible than peer spatial omics techniques (transcriptomics, proteomics). Here we demonstrate subcellular MSI on standard commercial hardware, analyzed using code-free, open-source software. An inexpensive, fully reversible modification of a stock DESI source takes the platform past its typical 5-10 m pixels to routine 2x2 m pixels, and 1x1 m in proof-of-principle experiments. At a tissue-glass boundary imaged at 2x2 m, tissue-specific ions showed no measurable spillover onto the adjacent glass within the {+/-}4.4 m uncertainty of the edge position. To make these data interpretable, we extend MSI.EAGLE, an open-source, vendor-agnostic application with two new methods: i) Spatial UMAP preserves tissue architecture alongside subcellular detail, where conventional clustering breaks apart at high resolution; ii) Histology Fit performs landmark-free co-registration, and recovers synthetic misalignments of up to 8 m to within one pixel of a reference registration. Together, these enable previously high-burden spatial metabolomics experiments. In mouse brain tissue, we demonstrate genuine subcellular signal by resolving mitochondrial cardiolipin into perinuclear puncta, quantifying cytoplasmic enrichment across 6,073 cells. Cell identities are assigned to MSI pixels using histology-predicted transcriptomics, linking cell provenance to metabolism in 2D space directly. Finally, we recover cell-type-specific metabolomes consistent with the transcriptomic identities. This workflow allows cellular and subcellular spatial metabolomics linked to cell provenance, with only stock MSI hardware, open-source GUI-based software, and common histology techniques, putting it within reach of many researchers and laboratories.

Hydractiniidae is a diverse family of colonial hydrozoans exhibiting substantial variation in colony organization, reproduction and life-cycle strategies, including species with and without a medusa stage. Several hydractiniids are also established model organisms, yet species boundaries and distributions remain incompletely resolved, limiting comparisons of reproductive and developmental traits across taxa. Here, we combine morphological and molecular data to reassess hydractiniid diversity, species identities, and life-cycle variation in material from the North Atlantic and Arctic Ocean. We integrate detailed observations of colonies and reproductive structures with DNA barcoding and mitochondrial genomes to evaluate species boundaries and provide molecular support for taxonomic identifications. Our results confirm 10 species in the study area, occurring from shallow waters to 2600 m depth and from coastal fjords to deep-sea hydrothermal vents. We further show that some historical species identifications and distribution records require reassessment. We establish a new genus for Arctic hydractiniid species (Bonneviactinia gen. nov.) and reassign two species to Schuchertinia. Mapping reproductive strategies onto the phylogeny reveals a broad pattern of increasing retention of medusa characters, from fixed sporosacs through reduced and fixed medusoids and non-liberated eumedusoids to fully developed, free-swimming feeding medusae, suggesting a progressive evolutionary trajectory in life-cycle complexity across Hydractiniidae. Furthermore, we clarify the identity of Podocoryna carnea and, through rearing experiments from polyp stage to medusae, characterize its morphological variation and developmental stages. By linking morphologically documented specimens and vouchers to genetic data, we establish reference resources that will facilitate future taxonomic, phylogenetic and biodiversity studies, including molecular surveys of marine communities. Together, these results demonstrate the value of integrative taxonomy for resolving hydractiniid diversity and provide a comparative foundation for investigating the evolution of reproductive strategies and life-cycle complexity in Medusozoa.

Chemical modifications of RNA provide an additional regulatory layer essential for development. N6A methyladenosine (m6A) is the most abundant internal mRNA mark, but how site specificity, stoichiometry, and cellular context together determine mRNA fate remains unclear. Here, we define these rules in cardiogenesis by combining single-molecule nanopore direct RNA sequencing (DRS) with a CRISPRdCas13 epitranscriptomic editing platform in human induced pluripotent stem cells and a conditional Mettl14 cardiac knockout in mice, integrated with multiomics, to map m6A sites and quantify stoichiometry. We uncover a bimodal m6A code in which low versus high modification ratios are associated with opposite mRNA and protein outcomes. We further show that Mettl14 loss causes developmental cardiomyopathy and embryonic lethality by disrupting the glycolysis to oxidative phosphorylation (OXPHOS) metabolic switch, and identify an m6A YY1 (Yin Yang 1) axis that post transcriptionally controls OXPHOS genes. Finally, targeted installation of m6A at defined sites using CRISPR/dCas13 reveals that m6A effects on YY1 are strongly locus and context dependent. Together, these findings establish m6A as a site and stoichiometry dependent regulatory code interpreted by cellular context to direct cardiac metabolic maturation. These principles are likely to extend to other developmental and physiological contexts in which precise control of metabolic state and gene dosage is required.

High-grade serous ovarian cancer progresses within a lipid-rich ascites microenvironment that engages stress-adaptation programs supporting malignant growth, yet how failed stress resolution influences tumor progression remains incompletely defined. Here, we show that unresolved lysosomal stress restrains tumor progression by sustaining tumor cell-intrinsic STING activity and reorganizing antitumor immunity. We identify BLTP3A as a lysosomal stress-resolution factor in ovarian cancer and show that the common germline missense variant BLTP3A M1098T increases stress-induced lysosomal damage. Patients carrying M1098T had longer overall survival and tumors enriched for cytotoxic T cell-myeloid neighborhoods. In syngeneic tumors, Bltp3a loss or orthologous variant expression delayed progression and generated Cxcl9+ antigen-presenting macrophage niches; M1098T-expressing human tumors similarly promoted interferon-responsive myeloid and T-cell enrichment in humanized mice. Mechanistically, ascites-induced lysosomal stress activated a STING-ATF4-BLTP3A feedback program. BLTP3A dysfunction disrupted CASM-associated lysosomal stress resolution, resulting in prolonged STING activity and sustained tumor-derived IFN-{lambda} without increased cGAMP. Tumor-cell STING and IFN-{lambda} were required for immune remodeling and tumor control. Thus, BLTP3A-dependent lysosomal stress resolution constrains the persistence of stress-induced STING signaling, whereas failure of this response sustains a tumor-intrinsic inflammatory program that organizes protective antitumor immunity.

1. Temperature shapes life histories through its effects on energy allocation among growth, reproduction and maintenance. The resulting temperature dependence of performance is commonly characterised using thermal performance curves (TPCs), which are often treated as static descriptions that apply uniformly throughout life. Yet the response to thermal variability may change across ontogeny. 2. We recorded growth, reproduction and survival throughout the lifetimes of individual Daphnia magna under four thermal regimes: Constant Low (15C), Constant Rearing (20C), Constant High (25C) and Variable (15C to 25C). The mean temperature under Variable closely matched that under Constant Rearing. Using an allometric energy-allocation model, we derived age specific and lifetime performance measures and quantified their uncertainty with a stratified individual-level bootstrap. Our principal quantity was the Jensen contrast, defined as performance under Variable minus that under Constant Rearing. 3. Age specific point estimates of the Jensen contrast changed sign across ontogeny. A positive aggregate contrast in full trajectory growth concealed a negative mid-life contrast; reproductive point estimates were positive during early and mid life but negative later. Bootstrap support was strong for the positive early life and negative mid-life growth contrasts, and for the positive early life reproductive contrast. Under a second-order approximation, this pattern of estimated signs is consistent with ontogenetic changes in effective thermal curvature. 4. The positive early life reproductive response did not carry through to the lifetime outcome: expected lifetime reproduction was lower under Variable than under Constant Rearing, with strong bootstrap support for the negative lifetime contrast. Because lifetime reproduction is survival weighted, lower survival under Variable reduced later reproductive contributions; across the estimated trajectories, the accumulated negative late life contribution out-weighed the earlier positive contributions. 5. These results show why forecasts based on mean temperature, a single life stage or an aggregate TPC may misrepresent lifetime performance under variable thermal regimes. Accounting for both ontogeny and temperature variability may therefore improve forecasts of life-history performance in increasingly variable thermal environments.

Temporal stability of plant populations is a key determinant of species coexistence and ecosystem functioning, yet its trait-based explanation has remained largely aboveground. Whether root functional traits contribute to long-term population stability remains poorly understood, despite roots mediating water and nutrient acquisition. We combined 17 years of vegetation monitoring from 150 temperate grassland plots across three regions in Germany with root functional trait data for 72 common grassland species. Temporal stability was computed as coefficient of variation (CV), with lower CV indicating higher stability. We tested whether root traits predict stability, and specifically which belowground dimensions from resource acquisition/conservation or soil exploration dominate, and whether differences in land use intensity modifies these relationships. Root traits were stronger and more consistent predictors of temporal stability than the classical aboveground traits specific leaf area (SLA) and leaf dry matter content (LDMC). Higher average root diameter (AD), root hair incidence (RHI), specific root length (SRL), and root tissue density (RTD) were generally associated with higher temporal stability, although the strength of these relationships varied among regions. Land use modified selected trait and stability relationships, with the strongest shifts occurring along the mowing gradient. Increasing mowing strengthened the associations of higher RHI and RTD with temporal stability, whereas the associations of AD and root N shifted towards lower stability. Our results identify belowground functional traits as an important missing component of trait-based temporal stability research and advance our understanding of the functional strategies underlying population temporal stability in managed semi-natural grasslands.

Forests regulate climate and sustain biodiversity, but their resilience is increasingly threatened by drought-induced hydraulic failure, when xylem water transport is impaired by embolism. A critical but poorly constrained determinant of this risk largely due to limited observations of deep root water uptake is the amount of root-accessible (sub)soil water storage (SR), which governs land-atmosphere exchanges during prolonged dry periods. While ecohydrological theory has long suggested a balance between soil water storage in the rooting zone, vegetation growth and drought tolerance, this concept has not yet been integrated into predictive models of hydraulic failure. Here we propose a novel, process-based inversion framework that integrates ecohydrological optimality theory with principles of plant hydraulic to infer SR. Using the SurEau plant hydraulic model, we estimate the SR value that balances the costs of soil exploration with the avoidance of drought-induced hydraulic damage. Applied first to a well-instrumented Mediterranean Quercus ilex forest, the inferred SR closely matched independent neutron probe and eddy covariance measurements and accurately reproduced observed drought responses, including leaf water potential and sap flow dynamics. We then scaled the approach across European forests remotely-sensed data, to assess spatially explicit SR estimates and associated hydraulic failure risk. Across more than 20 species and sites, inferred SR and drought stress metrics aligned with field observations and outperformed estimates based on conventional soil databases or remote-sensing-only approaches. By linking plant physiology and ecohydrological theory within a scalable inversion framework, this approach improves predictions of forest drought risk under climate change.

This study examined how prenatal CBD and {Delta}9-tetrahydrocannabinol (THC) exposure affects maternal caregiving in C57BL/6J mice. We developed the Machine-Automated Scoring of the Pup Retrieval Test (MAS-PRT) to overcome limitations of manual behavioral scoring. MAS-PRT integrates Multi-Animal DeepLabCut for dam and pup tracking with Detectron2 for dynamic nest reconstruction. Validated against 170 manually annotated retrieval trials, the pipeline showed high concordance with manual measurements and enabled reproducible extraction of encounter latency, retrieval latency, and locomotor trajectories. Prenatal exposure did not impair general nest-building or overall home-cage maternal care. However, pups from both CBD and THC groups showed reduced body weight at postnatal day 5. Cox proportional hazards modeling revealed divergent effects by compound: CBD-exposed dams exhibited a weight-dependent increase in probability of encountering and retrieving lighter pups, independent of pup sex. Spatial tracking further showed that dams traversed significantly shorter total trajectories when retrieving female progeny exposed to either compound. Longitudinal trial-by-trial analysis indicated intact task acquisition in controls and CBD dams, whereas THC dams displayed a flattened learning curve driven by lower retrieval latencies on initial trials. Together, these findings indicate that prenatal cannabinoid exposure does not produce generalized disruption of maternal care but instead induces compound-specific alterations in maternal reactivity, retrieval kinematics, and learning dynamics.

Whole-cell biosensors can detect many types of chemicals in complex environments, but existing designs force a tradeoff in multiplexed sensing: separating sensor strains into individual reservoirs limits how many analytes can be monitored at once, while pooling strains in open co-culture lets faster-growing strains take over within days, corrupting the signal. The microfluidic "mother machine" has been used for over a decade, mostly to study individual bacterial strains with single-cell resolution, but never to house multiple engineered strains simultaneously for sensing applications. We repurpose this device to hold a library of genetically distinct biosensor strains, physically isolating each strain in its own growth channel while continuous flow keeps every strain fed. Each strain reports on a target chemical through a unique combination of three fluorescent proteins, so seven distinguishable signals emerge from only three optical channels. We characterized turn-on and turn-off kinetics of several biosensors in the mother machine. Over a multi-day experiment with repeated chemical exposures, biosensors housed this way matched the expected on/off state and held stable population ratios, while biosensors in an open batch co-culture drifted and lost reliable signal. This establishes mother-machine-based multiplexing as a scalable route to long-term chemical monitoring with living sensors.