SLAS Technology

Transcriptional bursts regulate gene expression by altering burst size or burst frequency. Here, we present a protocol that integrates fixed-cell smFISH and live-cell single-molecule imaging to analyze estrogen-responsive transcriptional bursting of the TFF1 gene in human breast cancer cell lines. This workflow enables measurement of burst size, burst initiation, and active allele frequency to determine how endocrine disruptor chemicals modulate transcriptional bursting dynamics. For complete details on the use and execution of this protocol, please refer to Day, Yasar et al.1

Manual colony counting remains the rate-limiting, operator-dependent step in culture-based food microbiology quality control (QC). Automated colony analysis using machine learning (ML) offers the potential to standardise, accelerate, and improve the traceability of this process. However, systematic multi-method validation data for AI-based platforms against recognised international standards remain scarce. We conducted a prospective, multi-study validation of the Reshape Smart Incubator which is an automated imaging and ML-based colony analysis system, across eight ISO microbiological reference methods. In total, 887 plates were analysed, spanning qualitative (presence/absence) detection of Listeria spp. (ISO 11290-1) and Salmonella spp. (ISO 6579), and quantitative enumeration of total viable count (ISO 4833), Bacillus cereus (ISO 7932), Enterobacteriaceae (ISO 21528), coagulase-positive Staphylococci (ISO 6888), yeasts and moulds (ISO 21527), and lactic acid bacteria (ISO 15214). Automated results were benchmarked against the consensus of three or more trained technicians. The platform achieved 100% agreement with manual assessment for all both qualitative detection methods (ISO 11290-1, ISO 6579) with zero false positives and zero false negatives. For quantitative enumeration, agreement ranged from 92.97% (ISO 15214, n=122, using ISO-aligned {+/-}10%/>30 CFU thresholds) to 98.46% (ISO 21528, n=130). Where discrepancies occurred, they largely coincided with plates showing high inter-technician variability. Precision testing demonstrated a coefficient of variation of 5.88% and a mean standard deviation of 0.44 CFU for low-count plates. This study presents a comprehensive multi-ISO validation of an AI-based colony analysis system to date. The AI models demonstrated performance comparable to or exceeding that of trained human technicians across a broad range of microbiological targets, agar types, and colony morphologies, thereby supporting their use as a validated and traceable alternative to manual plate reading in accredited food microbiology quality control laboratories.

Aroma perception during food consumption results from the combined effects of food composition, oral processing (such as chewing and saliva action), the release and transport of volatile compounds toward the olfactory epithelium, followed by cognitive integration in the brain. Recent advances in real-time analytical techniques, particularly Proton Transfer Reaction-Time-of-Flight Mass Spectrometry (PTR-ToF-MS), enable in vivo monitoring of aroma release with high temporal resolution and have become widely used for analyzing the composition of exhaled air. However, the interpretation of aroma release kinetics remains challenging due to substantial intra- and inter-individual variability caused by differences in physiology, anatomy, oral behavior, and respiratory patterns. In this context, the present study was designed to quantify aroma release associated with different food oral processing (FOP) mechanisms, such as chewing and swallowing, using simple model matrices containing a single aroma compound, and to document inter- and intra-individual variability among subjects. Real-time PTR-MS measurements were combined with self-reported oral events and simultaneous respiratory monitoring to analyze aroma release from aqueous solutions and gummy discs flavored with isoamyl acetate. The results showed that inter-individual variability was higher than intra-individual variability and allowed its quantification in aroma release. Significant differences in aroma release kinetics were observed depending on FOP protocols. The importance of considering swallowing events when analyzing aroma release data was also highlighted.

Osteocytes play a central role in bone remodeling, mineral metabolism, and skeletal homeostasis, but direct molecular analysis of human osteocytes remains technically challenging because they are embedded within the mineralized bone matrix. Surgically obtained human bone specimens provide valuable material for studying human bone biology; however, surface-associated cells, marrow-derived cells, and adherent soft tissues can confound downstream transcript analysis. Here, we describe a bone fragment-based protocol for preparing surgically obtained human bone specimens for molecular analysis of osteocyte-associated transcripts. The protocol consists of mechanical trimming, mincing into small bone fragments, repeated washing, and five sequential rounds of collagenase digestion to reduce non-osteocytic cellular components associated with the bone surface and marrow spaces. The remaining mineralized bone fragments are then frozen in liquid nitrogen, cryogenically pulverized, and lysed in TRIzol reagent for total RNA extraction. Histological validation using residual maxillary bone specimens showed that sequential collagenase digestion markedly reduced adherent soft tissue and extra-matrix nuclei while preserving osteocyte lacunar occupancy. This protocol provides a practical workflow for bone fragment-based RNA analysis focused on osteocyte-associated transcripts in human bone specimens. Specifications table O_TBL View this table: org.highwire.dtl.DTLVardef@1cec618org.highwire.dtl.DTLVardef@2f746forg.highwire.dtl.DTLVardef@1854247org.highwire.dtl.DTLVardef@1c26c1aorg.highwire.dtl.DTLVardef@1473a88_HPS_FORMAT_FIGEXP M_TBL C_TBL

Transcriptomic and proteomic measurements from the same single cell provide complementary information that cannot be inferred from either modality alone, yet methods for the parallel recovery of both analyte classes from a single-cell lysate remain limited. Here, we describe a workflow in which individual cells are isolated by automated dispensing into a minimal, MS-compatible lysis volume, followed by sequential mRNA capture and protein supernatant recovery, prior to independent downstream processing. The method is compatible with standard library preparation and data-independent acquisition proteomics pipelines and requires no dedicated instrumentation beyond a single-cell dispensing platform. We evaluated workflow performance on 67 single cells across 3 iBlastoids. Transcriptomic sequencing detected a median of 5375 genes per cell, and proteomic analysis identified a median of 2123 protein groups per cell across two mass spectrometry platforms. Compared with a standalone single-cell proteomics protocol, incorporating the mRNA extraction step reduced median proteomic depth by approximately 11% (median 1,965 vs. 2,204 protein groups per cell), while mean percell identification remained comparable across workflows (1,790 vs. 1,775 protein groups per cell). Direct comparison of paired transcript and protein abundance yielded a median Spearman correlation of {rho} {approx} 0.38; after correction for detection depth, the partial correlation was 0.067.

Advances in transcriptome profiling have revealed transcriptomic differences across different cellular states. However, functional interpretation requires precise perturbation tools and experimental frameworks. This study benchmarked two widely used modalities: CRISPR interference (CRISPRi) and Cas13d/CasRx. A standardized workflow was established to generate human pluripotent stem cells (PSCs) with inducible ZIM3-dCas9 or CasRx expression. The cell lines were subjected to flow cytometry, copy number, and immunocytochemical analyses. The knockdown performance was validated via robust OCT4 suppression and the expected downstream effects on pluripotency genes. Time-course measurements indicated that CRISPRi produced faster and stronger repression but slower recovery after inducer withdrawal. In contrast, CasRx yielded slower and typically weaker knockdown with rapid reversibility. Furthermore, a key limitation of CRISPRi was demonstrated using the ATF5-NUP62 locus, wherein CRISPRi could co-repress genes with overlapping promoter regions. In contrast, CasRx avoids these limitations and supports isoform-resolved targeting of circular and alternatively spliced transcripts, albeit with variable efficiency. These results provide practical guidance for selecting complementary knockdown tools to improve the interpretability of transcriptomic function studies. MOTIVATIONAdvances in transcriptome profiling have enabled the detection of subtle cell type-specific differences. However, mechanistic interpretation still depends on perturbation tools that can modulate transcripts with high precision and efficiency. Recent CRISPR-based modalities, CRISPRi and Cas13/CasRx, function as robust and orthogonal methods to achieve the knockdown of specific gene targets. However, a standardized approach for cell line preparation and comparative studies on their relative performances and limitations remains unclear. Consequently, this study presents a standardized workflow for generating cell lines that support high-efficiency knockdown using CRISPRi and CasRx. Moreover, it compares the trade-offs in potency, reversibility, and isoform resolution, along with a practical overview of method-specific pitfalls to guide tool selection and data interpretation in future studies. HIGHLIGHTSO_LIDoxycycline-inducible AAVS1 knock-in human PSC platforms for CRISPRi (ZIM3-dCas9) and CasRx (RfxCas13d) were generated to enable standardized RNA perturbation experiments. C_LIO_LIThe prepared cell lines demonstrated strong OCT4 knockdown, with expected downstream effects on the expression of another pluripotency gene, NANOG. C_LIO_LIA comparison of knockdown characteristics and their reversibility revealed rapid and sustained repression with CRISPRi, whereas slow but rapid recovery was observed with CasRx. C_LIO_LIA CRISPRi-specific off-target effect arising from TSS proximity/overlap (ATF5-NUP62) was identified, whereas CasRx achieved ATF5 knockdown without collateral repression of the neighboring NUP62 gene. C_LIO_LICasRx enables isoform-resolved knockdown of structural isoforms (circHIPK3 vs. linear HIPK3 mRNA) and splice isoforms (RAB6A-iso1 vs. RAB6A-iso2). C_LI

ObjectivesTo characterize longitudinal age-related changes in abdominal organ volumes using CT volumetry and to model nonlinear trajectories across multiple organs. Materials & MethodsThis retrospective single-center study included adults who underwent whole-body screening low-dose CT between 2006 and 2017. Subjects with at least eight examinations during a follow-up period of at least 78 months were included. After applying exclusion criteria, 700 participants with 6,739 CT series were analyzed. Non-contrast CT images were processed using automated organ segmentation, and volumes of the liver, pancreas, spleen, and kidneys were quantified. Longitudinal changes were modeled using generalized additive mixed models with sex-specific smooth functions of age and subject-level random effects. Age-dependent rates of change were estimated from model derivatives. ResultsA total of 700 participants (mean age, 56.9 {+/-} 9.8 years, 29.6% women) were evaluated. Liver, pancreas, and kidney volumes showed mild increases or plateaued at approximately 40-60 years of age, depending on the organ, and were followed by gradual declines with advancing age, whereas splenic volume showed a progressive decrease across the age range. These patterns showed nonlinear age dependence. The transition from positive to negative change rates tended to occur earlier in women than in men for several organs, particularly the liver and kidneys. ConclusionLongitudinal CT analysis demonstrated nonlinear age-related changes in abdominal organ volumes, with organ-specific trajectories and sex-related differences in the timing and magnitude of volume changes. QuestionHow do abdominal organ volumes change longitudinally with age, and can their trajectories be characterized for each organ? FindingsLongitudinal CT analysis demonstrated nonlinear, organ-specific volume trajectories, with transitions from stability to decline around 40-60 years and earlier transitions in women than men. Clinical RelevanceLongitudinal reference patterns of abdominal organ volumes on CT improve the interpretation of age-related changes and support more accurate differentiation between physiological variation and disease-related volume alterations.

BackgroundHepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, with particularly severe consequences in sub-Saharan Africa where access to advanced diagnostic imaging remains limited. Ultrasound is the most widely available imaging modality in low-resource settings, yet its sensitivity for detecting early-stage HCC remains insufficient when used in conventional B-mode alone. MethodsWe present a dual-path convolutional neural network (CNN) that jointly analyzes B-mode and contrast-enhanced ultrasound (CEUS) images for automated HCC detection. The model processes 1,057 labeled liver ultrasound images from 85 patients sourced from The Cancer Imaging Archive, a publicly available single-center dataset. A preprocessing pipeline extracts liver-centered regions of interest from heterogeneous DICOM files, including automatic separation of dual-panel B-mode and CEUS frames. Each imaging modality is processed through a dedicated ResNet-34 backbone initialized with ImageNet weights, and the resulting feature embeddings are fused through a late-fusion classification head. The model is evaluated using patient-wise five-fold cross-validation and a held-out 20% patient-level test set. ResultsOn the held-out test set, the model achieved 94.2% accuracy, 93.6% precision, 100% sensitivity, 83.3% specificity, and a 96.7% F1-score for binary HCC versus non-HCC classification. Cross-validation analysis showed consistently high discrimination across folds, with AUC values ranging from 0.93 to 0.98. Training dynamics indicated that early stopping typically activated between epochs seven and eleven, with validation loss closely tracking training loss and no evidence of severe overfitting under the chosen regularization scheme. ConclusionsThese findings demonstrate that a relatively lightweight multimodal CNN, trained on carefully preprocessed public data, can provide strong imaging-level discrimination between HCC and non-HCC findings within a single-center dataset. However, the small sample size, pronounced class imbalance, and single-center origin of the data preclude any claims of clinical utility at this stage. This work is a transparent, reproducible methodological baseline intended to support future multi-site validation, particularly in African and other low-resource clinical settings where ultrasound-based decision support could have the greatest impact.

AimsExercise capacity is a powerful predictor of cardiovascular risk. In patients unable to exercise, body composition analysis can potentially be used to estimate cardiorespiratory fitness. We developed a body composition "fitness" score, then validated its utility in two external populations. Methods and ResultsWe included patients from four sites undergoing single photon emission computed tomography (SPECT) and twelve sites undergoing positron emission tomography (PET). We quantified body composition using deep learning. We evaluated associations between body composition and good exercise capacity (defined as completing [&ge;]7 minutes on a Bruce protocol) then developed a body composition "fitness" score. We then assessed the associations of "fitness" score with exercise capacity and all-cause mortality in external populations. In total, 36471 patients were included with median age 67 (interquartile range 58 - 74). Median skeletal muscle density was higher among patients with good exercise capacity. In the external SPECT population, the body composition "fitness" score had higher prediction performance for good exercise capacity (AUC 0.771, 95% CI 0.752 - 0.789) than age (AUC 0.717, p<0.01). In the external PET population, high body composition "fitness" score was associated with lower cardiovascular death (adjusted hazard ratio 0.70, 95% CI 0.62 - 0.79, p<0.001). ConclusionsWe demonstrated that a comprehensive body composition "fitness" score could identify patients with good cardiorespiratory fitness. This approach transforms routinely acquired CT data into a surrogate marker of fitness which can be applied in patients undergoing PET, or other CT imaging, where exercise testing is not performed. Graphical AbstractOverview of study design. The overall population (n=36471) was split as outlined above. Body composition was analyzed from available computed tomography imaging. The distribution of body composition measures were analyzed in the combined single photon emission computed tomography (SPECT) populations. A body composition "fitness" score was derived to predict good exercise capacity in the internal population, with associations assessed in the two external testing populations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/26352573v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@1b98c3eorg.highwire.dtl.DTLVardef@a64282org.highwire.dtl.DTLVardef@1589559org.highwire.dtl.DTLVardef@b5423f_HPS_FORMAT_FIGEXP M_FIG C_FIG

Bone is a highly durable biological tissue widely used in forensic, archaeological, and anthropological investigations; however, efficient protein recovery and understanding of protein stability over time remain major challenges in skeletal proteomics. Here, we systematically evaluated three bone protein extraction workflows and integrated them with data-independent acquisition (DIA) mass spectrometry to assess proteome coverage, reproducibility, and temporal protein dynamics under environmentally exposed conditions. Comparative analysis demonstrated that extraction strategy is a primary determinant of detectable proteome composition. EDTA-based demineralization followed by SDS extraction provided the deepest proteome coverage and highest reproducibility, whereas guanidine hydrochloride extraction preferentially enriched collagen and extracellular matrix proteins. In contrast, acid-based extraction yielded limited protein recovery. Temporal profiling of bone samples collected at 10 and 45 days post-exposure revealed two distinct protein classes. A temporally stable module, enriched in collagens and extracellular matrix proteins including COL1A2, COL5A2, BGN, SPARCL1, and NID2, exhibited minimal abundance change, indicating resistance to environmental degradation. In contrast, temporally dynamic proteins, enriched in mitochondrial, metabolic, and intracellular pathways such as ACO2, OGDH, PDHA1, ATP5PO, and PFKM, showed marked decline over time. These findings support a two-compartment model of bone protein preservation in which matrix-embedded proteins are preferentially retained while exposed intracellular proteins undergo progressive degradation. Collectively, this study establishes an integrated framework linking extraction methodology with temporal proteome stability and identifies candidate markers for skeletal preservation assessment and temporal biomarker development in forensic and archaeological applications.

Blood-based biomarkers are increasingly used to investigate brain health, but collecting venous blood is difficult in remote and field settings. Capillary microsampling offers a practical alternative, although the ability to delay processing and its agreement with gold-standard venous blood require validation. We evaluated Tasso+, a minimally invasive upper-arm capillary blood collection system, for measuring neurological and host-response biomarkers in plasma and serum during an exercise-based protocol. Sampling occurred before, immediately after, and approximately 24-to-36 hours after exercise; Tasso+ samples were processed with or without a 72-hour room-temperature delay. Tasso+ samples were compared with matched venous blood, and Capitainer SEP10 dried plasma spots were also evaluated, using Quanterix Simoa and Alamar Biosciences NULISAseq CNS panel. Tasso+ enabled reliable measurement of several key biomarkers, including GFAP and NfL, even after delayed processing. These findings support capillary microsampling for neurological biomarker studies where venepuncture is challenging, including field-based research and participant-led remote sampling.

Image-based liver Couinaud segmentation is designed to automatically provide the locations of suspicious objects in liver CT/MR images. Once achieved, the physicians will be guided to the target slice and area where the suspicious node is located. However, conventional algorithms trained primarily on healthy liver images often fail to generalize to Hepatocellular Carcinoma (HCC) cases due to pathological structural distortions. In this work, we propose a robust two-stage framework that integrates a 3D Unet with a 3D Anatomical Structure-Guided Graph Convolutional Network (3D GCN). This two-stage strategy effectively isolates the liver volume to eliminate structural noise from neighboring organs, such as the spleen, allowing the framework to focus exclusively on the complex 3D anatomical relationships among the eight segments. To ensure the topological consistency required for global spatial reasoning, we implement a standardized preprocessing pipeline that normalizes liver-only volumes to exactly 50 frames along the z-axis. By combining a lightweight 3D UNet backbone with the 3D GCN for refined boundary reasoning, our model demonstrates superior generalization performance on unseen clinical datasets, achieving a mean Dice score of 0.828 in blind testing. By releasing our code and pretrained weights, we aim to provide the first publicly available deep learning resource for robust Couinaud segmentation.

This work aimed to establish a translationally viable, xeno-free, serum-free platform and protocol for the isolation and expansion of human salivary stem/progenitor cells (hS/PCs) suitable for regulatory qualification and future FDA-approved first-in-human autologous regenerative therapy trials for the treatment of hyposalivation disorders. Parotid gland specimens from non-cancerous regions/tissues were collected from consented surgical patients. Primary hS/PCs were isolated from tissue specimens, cultured in animal-component-free conditions, expanded to produce millions of cells, then enriched for CD44+ stem/progenitor cells by magnetic cell sorting. Normal epithelial purity was assessed using cytokeratins 5/14. Anti-CD133/PROM1 (cancer marker) and anti- fibroblast (clone TE-7) antibodies were used to demonstrate a lack of contaminating cells. Phenotype validation was performed by flow cytometry and immunocytochemistry on both CD44+ sorted and unsorted populations. Senescence-associated beta-galactosidase (SA-{beta}-gal) assays were performed across serial passages (P1-P6). Pluripotency was demonstrated by culture under conditions supporting lineage-specific differentiation. Primary hS/PCs demonstrated consistent expansion and epithelial morphology under serum-free conditions. CD44 expression remained high (>95%) throughout expansion, with negligible detection of CD133 or fibroblast markers, confirming epithelial purity and absence of tumorigenic or stromal contamination. Immunocytochemistry corroborated these expression profiles. SA-{beta}-gal staining revealed only a minor, passage-dependent increase (5-16%) in senescent cells from multiple donors, indicating retention of proliferative potential. Our defined, animal-free culture system supports stable expansion of pure low passage hS/PCs under conditions compatible with good manufacturing practice (GMP).

Multiplex bead-based immunoassays (MIAs) are promising tools for simultaneously detecting humoral immunity to multiple targets, potentially playing a crucial role in serosurveillance and vaccine response assessments. However, evaluation of assay performance is paramount prior to widespread use. This study presents a performance evaluation of a pan-filovirus MIA through characterization of the analytical range for the EBOV glycoprotein (GP) target and assessments of assay precision and antigen discrimination. The precision of the MIA was evaluated by comparing the detection of anti-filovirus antibodies at two independent laboratory sites: the University of Hawaii, Honolulu (UH), and the Institut National de Recherche Biomedicale (INRB) in Kinshasa, Democratic Republic of the Congo (DRC). Forty-six samples from Yambuku, DRC, including Ebola virus Disease (EVD) survivors and close contacts, were tested at both sites. Additionally, 858 samples were tested in DRC before and after vaccination with a prophylactic EVD vaccine, ERVEBO. Results demonstrated low variability between laboratories, with intra-assay and inter-laboratory coefficients of variation below predefined thresholds for all filovirus targets included in the multiplex panel. Analyte correlations between sites were high (r2=0.86-0.92). Longitudinal analysis detected increased EBOV GP reactivity following vaccination, while reactivity to non-vaccine filovirus antigens remained stable, consistent with minimal cross-reactivity in a vaccinated cohort. These findings suggest that this pan-filovirus MIA produces reproducible results across distinct laboratory settings and may serve as a useful tool for comparative serologic investigations, serosurveillance, and evaluation of EBOV vaccine-associated antibody responses. IMPORTANCE STATEMENTThis study investigates the functionality and intra-laboratory consistency of a novel multiplex bead-based immunoassay with pan-filovirus targets. As part of the evaluation process, the feasibility of using the assay in resource-limited settings was demonstrated in the Democratic Republic of the Congo. This assay holds significant promise as a tool for detecting filovirus-specific antibody responses. By leveraging its multiplex capabilities, it may be used for widespread serosurveillance of high-consequence pathogens, including the pan-filovirus antigens such as Ebolavirus and Marburg virus already incorporated in the assay, as well as other targets of interest.

IntroductionReliable generation of hepatocyte-like cells (HLCs) from pluripotent stem cells remains limited by heterogeneity and incomplete maturation of the cells. Derivation of induced pluripotent- and embryonic stem cells into hepatocytes typically relies on complex, and costly reagent-intensive protocols, with inconsistent reporting of differentiation efficiencies and functional maturation criteria. Variability in protocol designs highlights the need for optimisation, particularly in mouse embryonic stem cells (mESCs) systems that can be more comparable with mouse models for underpinning translational and toxicological studies. Here, we developed and evaluated two cytokine-based strategies: an advanced hepatic-inducing cocktail (A-HIC) and a simplified hepatic-inducing cocktail (HIC), both designed to reduce complexity while increasing functional maturation. MethodsHepatic differentiation and maturation were assessed by morphology, immunofluorescence, flow cytometry, and qRT-PCR. Functional competence was evaluated via urea production, glutathione synthesis, indocyanine green handling, cytochrome P450 inducibility, and impedance-based cell layer integrity monitoring. ResultsMorphological, molecular and phenotypic analyses confirmed that both protocols supported hepatic lineage progression, generating heterogeneous populations of hepatoblast-like and more mature HLCs. Gene expression confirmed the loss of pluripotency, transient endoderm induction, and subsequent hepatic specification. Functionally, cells exhibited glycogen storage, inducible urea production, glutathione depletion, and active ICG uptake and clearance, with stable monolayer formation by day 21. A-HIC-derived HLCs demonstrated enhanced maturation, with higher ASGR1 expression and stronger Cyp1a1 induction. DiscussionThese findings suggest that both protocols generate functional HLCs; however, A-HIC yields a higher proportion of functionally mature cells with reduced variability. This approach enables a simple, cost-effective, and time-efficient generation of HLCs, supported by improved functional characterisation with potential applicability to more complex pluripotent systems, including human iPSC-based models for disease modelling and toxicology.

Rapid and specific diagnosis of viral and bacterial infections is a significant challenge in medicine and veterinary science, especially in the case of epidemically dangerous pathogens. The African swine fever virus (ASFV), for example, causes annual outbreaks among livestock, resulting in significant economic losses for farmers. DNA aptamers have been identified as a promising tool for point-of-care diagnostics, being highly specific to the target and stable ambient temperatures during storage. In this study, we describe the selection of DNA aptamers targeting the p54 viral protein using a single-round selection process. These aptamers were able to bind both to recombinant protein and inactivated ASFV viral particles. Analysis of the newly generated aptamers revealed a dependence of affinity and thermal stability on Ni2+ content, which was a dopant in the selection process. In some cases, the affinity increased 100 times, and melting temperature increased by 30{degrees}C. We have identify two novel DNA motifs that bound 2-3 Ni2+ or Zn2+ ions.

Fluorescent biosensors have proven valuable for revealing the spatio-temporal dynamics of protein conformation in live cells and animals. The great majority of biosensors are genetically encoded, but genetic encoding is difficult or impossible to apply in many cases, including cells or animals with poorly understood genomes, no DNA, or sensitive to manipulation. Using biosensors without genetic manipulation could greatly simplify studies in animals, expand the range of accessible organisms, and ultimately enable application in humans. Here we explore using a membrane-permeable small molecule as a fluorescent biosensor. The drug trifluoperazine, which binds only to the active conformation of calmodulin, was covalently linked to an environment-sensing merocyanine dye to create CaMero, a biosensor of calmodulin activation. Simple incubation of CaMero in the extracellular medium, or injection in the tail vein of mice, led to sensitive real time reporting of calmodulin activity. The dye underwent a 12-fold change in fluorescence intensity upon binding to activated calmodulin, revealing waves of activation in peristaltic intestine, localization and kinetics of calmodulin activation during serum stimulation in fibroblasts, and localized activation in the single-celled marine protist foraminifera.

Monoclonal antibody (mAb) glycosylation is a critical quality attribute that is difficult to rationally engineer and rapidly assess during cell line development. Here, we investigate whether cell-surface glycosylation can serve as a predictive indicator of mAb product glycosylation following targeted glycogene engineering in CHO cells. Five key glycogenes (COSMC, FUT8, B4GALT1, ST3GAL4, ST6GAL1) were investigated in two mAb-producing CHO cell lines. Product glycan analysis revealed consistent, gene-specific effects across hosts, including loss of core fucosylation, and tuneable galactosylation and sialylation. Lectin-based surface profiling reliably reflected product outcomes for COSMC and FUT8 modifications but showed limited predictive power for galactosylation and 2,3-sialylation, highlighting glycosylation pathway redundancy and context dependence. This study provides the first systematic, cross-cell line evaluation of lectin-based cell-surface glycan profiling as a predictor of mAb product glycosylation, establishing its practical utility and inherent limitations for CHO glycoengineering workflows. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/724788v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@6d5cfborg.highwire.dtl.DTLVardef@1f38e0aorg.highwire.dtl.DTLVardef@f25fa2org.highwire.dtl.DTLVardef@64a0dc_HPS_FORMAT_FIGEXP M_FIG C_FIG

Expanding genetic engineering beyond model microorganisms is critical to unlocking novel applications in biotechnology, yet the low efficiency of DNA delivery methods like conjugation, remains a major bottleneck in non-model and environmental microbes. Here, we present an automated, high-throughput droplet microfluidic platform that enhances conjugation by encapsulating donor and recipient microbes in picoliter-scale water-in-oil microdroplets, stabilizing cell-cell contact and DNA transfer. Optimization of incubation time, donor to recipient ratio, and plasmid type yielded over a 100-fold increase in conjugation efficiency compared to conventional methods and enabled delivery of complex DNA libraries in low reaction volumes, demonstrating scalability for pooled plasmid library delivery. We further utilized a synthetic biology circuit for donor removal within microdroplets without antibiotic selection, eliminating the need for host-specific selection markers or engineered auxotrophs. When applied to a soil microbial community, this platform improved community-level conjugation, preserving microbial diversity and enabling the identification of genetically accessible chassis. Collectively, this platform establishes a scalable, generalizable solution for high throughput DNA delivery in previously inaccessible microbial hosts. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=54 SRC="FIGDIR/small/721591v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@c7a8d4org.highwire.dtl.DTLVardef@1d1fbaorg.highwire.dtl.DTLVardef@e1faforg.highwire.dtl.DTLVardef@14234dc_HPS_FORMAT_FIGEXP M_FIG C_FIG

Data-driven materials development requires large, well-characterized libraries of precisely defined formulations. While microfluidic platforms excel at generating highly controlled materials, their throughput is often limited by the challenge of efficiently interfacing device outputs with standard well plates. This bottleneck frequently necessitates manual transfer or non-microfluidic workflows, constraining both throughput and reproducibility. Here, we present LMNOP-bot (Libraries of Micro- and Nano-materials, OPen-source bot), an open-source robotic platform for the automated generation and collection of micro- and nanomaterial libraries from serial microfluidic outputs. Using synchronized, pressure-driven flow, LMNOP-bot enables continuous formulation and direct deposition into standard well plates. The system is low-cost (<$700, excluding pressure regulators), constructed from readily available or easily fabricated components, and designed for broad accessibility. LMNOP-bot collects [&ge;]30 {micro}L per formulation at a rate of one sample every four seconds, representing an approximately 50x increase in throughput over existing serial microfluidic workflows, and operates robustly for over 10,000 runs without maintenance. We demonstrate compatibility with both PDMS/glass and commercial polycarbonate devices, with seamless interfacing to 96- and 384-well plates. Repeated sampling confirms high precision and reproducibility. By removing a key bottleneck in microfluidic library generation, LMNOP-bot enables rapid, scalable, and accessible exploration of material design spaces.