Journal of Biological Engineering

BackgroundProlonged hyperglycemia in diabetes activates platelets and immune cells, forming platelet-immune complexes that damage blood vessels in the retina. However, the role of platelet-neutrophil interactions and neutrophil extracellular traps(NETs) in the development of diabetic retinopathy (DR) was not well studied. In this study, we investigated the mechanisms underlying platelet-mediated NET formation in DR. MethodologyPlatelet activation markers, platelet-neutrophil aggregates (PNA), and NETs markers were assessed by flowcytometry, and the circulatory level of inflammatory markers was measured by Luminex assays in healthy control(HC), type 2 diabetes mellitus(T2DM), non-proliferative DR(NPDR) and proliferative DR(PDR) subjects. In vitro studies investigated platelet-neutrophil interaction in NETs formation using an immunofluorescence assay. Proteomics analysis identified the mechanistic regulators of platelet-induced NETs in DR. Platelet pellet and plasma CXCL7 were quantified using western blot and ELISA, respectively. The role of the CXCL7/CXCR2 axis in inducing NETs formation was examined using CXCL7 recombinant protein, anti-CXCL7 antibody and CXCR2 antagonist (SB225002). ResultsPlatelet activation markers (p-selectin & PF4), PNA, and NETs markers (%NETs, proteinase-3 (PR3), neutrophil elastase (NE)) were significantly increased in the DR group. In vitro studies confirmed that DR-platelets aggregate with healthy neutrophils and form NETs compared to T2DM and HC-platelets. Furthermore, platelet activation and NETs markers were positively correlated with pro-angiogenic (ANGPT2, VEGFA) and inflammatory markers (IL18, ICAM1). In vitro studies reveal that NETs induce inflammation, endothelial dysfunction, disrupt the endothelial monolayer and exacerbate angiogenesis in RF/6A endothelial cell spheroids. Proteomics analysis of platelet-induced NETs in DR revealed dysregulation of proteins involved in platelet activation and NET formation, including CXCL7. Furthermore, increased CXCL-7 levels were observed in platelet pellet and plasma samples from the DR group. Additionally, CXCL7-treated neutrophils formed NETs via the CXCR2 receptor, and inhibition of NETosis was observed in neutrophils exposed to an anti-CXCL-7 antibody and a CXCR2 antagonist. ConclusionOur findings revealed that platelets released CXCL-7 induce NETs formation via the CXCL7/CXCR2 axis and blockade of CXCL7/CXCR2 axis inhibits the NETosis in DR, thereby inhibiting the pathogenesis of DR. Circulating CXCL7 serves as a potential prognostic marker, and the CXCL7/CXCR2 axis may be a therapeutic target for the treatment of DR. What Are the Clinical Implications?Platelets have emerged as immune cells, and platelet-neutrophil interactions are reported to play a significant role in the pathogenesis of various metabolic diseases. The role of platelet-neutrophil interactions and neutrophil extracellular traps (NETs) in the development of diabetic retinopathy (DR) remains poorly understood. Investigating the mechanistic regulators of platelet-mediated NETs in DR is crucial for identifying new therapeutic approaches. Our study observed increased platelet activation, platelet-neutrophil aggregates and NETs among DR subjects. Further, DR-platelet induces NET in healthy neutrophils, and NETs induce inflammation, angiogenesis, and disrupt endothelial barrier function in RF/6A cells in vitro. These findings strengthen the evidence that platelet-neutrophil interactions play a major role in DR pathogenesis. Proteomic analysis identified CXCL7 as a mechanistic regulator of platelet-induced NETs formation in DR. Inhibitors that target the platelet-derived CXCL7/CXCR2 axis for NETosis can be used for the prevention of retinal injury in DR. Overall, our work emphasises the mechanistic understanding of platelet-neutrophil interactions and CXCL7/CXCR2 axis as a therapeutic target for inhibiting the pathogenesis of DR. Graphical abstractScheme for the platelet-derived CXCL7 regulation of NETs in DR. Activated platelets release CXCL7 and platelet aggregates with neutrophils to form NETs via the CXCL7:CXCR2 axis. Blockade of the CXCL7:CXCR2 axis by anti-CXCL7 antibody and CXCR2 inhibitor prevents NETs formation in DR.

Crop loss due to infection by pests and pathogens is a major barrier to the large-scale production of algal biofuels. Test systems have seen loss of green algae crops due to infection by the fungus-like Amoeboaphelidium occidentale FD01. While current antifungal compounds are effective in inhibiting the infection, their application raises the overall cost of the crop and lowers its economic viability as a biofuel source. Here we show that co-culturing environmentally harvested bacteria alongside algae crops can drastically lower the rate of infection in two different green algae species of interest for biofuel production. These bacteria-algae consortia increase the mean time to crop failure (MTTF) by up to 350% when tested under environmentally relevant conditions. While there was an increase in diversity over time, there was no statistically significant correlation between an increase in diversity and a longer MTTF. Community composition analysis reveals similarities between the bacterial genera growing alongside both green algae species even as bacterial harvest locations differed, although there was not a single dominant genus responsible for the increase in crop protection. These results show a promising new method of anti-fungal crop protection that can be applied to algal biofuels with no increase in fuel cost. HighlightsO_LIBacteria-algal cocultures protect against fungal pests without impact to productivity C_LIO_LIBacterial community composition is variable over time even as protection persists C_LIO_LIBacterial consortia can increase mean time to failure by 350% C_LI

Cardiac fibrosis is a pathological process in which the myocardium stiffens due to the overproduction of extracellular matrix (ECM) proteins. Cardiac fibroblasts activate to myofibroblasts in response to the inflammatory cytokine transforming growth factor beta1 (TGF-{beta}1) to promote fibrotic scarring. Biological sex also influences cardiac fibrosis progression and patient outcomes, where males exhibit increased fibrotic scarring after acute inflammation relative to females. At the cellular level, sex differences in TGF-{beta}1-mediated cardiac myofibroblast activation processes have not been clearly defined. We hypothesized that TGF-{beta}1 would cause sex-specific cardiac myofibroblast activation levels and alter the secretion of bioactive molecules to modulate sex differences in cardiac fibrosis. Primary left ventricle cardiac fibroblasts were isolated from male and female C57BL/6J mice and cultured on hydrogel biomaterials mimicking native myocardial ECM stiffness and treated with TGF-{beta}1 and/or the TGF-{beta}1 receptor inhibitor SD208. Male myofibroblasts exhibited increased -SMA stress fiber formation, increased SMAD2/3 localization, and greater resistance to SD208 inhibition compared to female myofibroblasts on hydrogels at various time points tested. Sex differences in relative secreted cytokine abundance were also determined, with male CFs secreting increased vascular endothelial growth factor (VEGF) and female CFs producing increased periostin and fibroblast growth factor 21 in response to TGF-{beta}1. Our findings establish that TGF-{beta}1 mediates sex differences in cardiac myofibroblast activation on hydrogels and secreted factors that may modulate the myocardial microenvironment. Our work underscores the importance of using hydrogels as cell culture platforms to recapitulate sex-specific cardiac fibrosis phenotypes as a steppingstone towards identifying sex-dependent therapeutic interventions for cardiac fibrosis.

Traumatic joint injuries both disrupt chondrocyte metabolism and increase the risk for post-traumatic osteoarthritis. Yet the relationships between trauma, altered metabolism, and cartilage degradation remains unclear. This study compares the metabolic responses of bovine (normal) and osteoarthritic (OA) chondrocytes to physiological and injurious mechanical stimuli under normoxic (20% O2) and hypoxic (5% O2) conditions. Using primary chondrocytes encapsulated in agarose, physiological and injurious mechanical stimulation, targeted metabolomic profiling of central carbon metabolites, and O2 saturation measurements, we find that healthy bovine chondrocytes exhibit robust, time-dependent adaptation to mechanical stimuli, whereas OA chondrocytes display a blunted response, particularly under injury conditions. Injurious mechanical stimuli led to altered O2 consumption and glutamine accumulation, suggesting disrupted respiration and reduced protein synthesis hypothesized to be a result of altered mitochondrial metabolism in OA cells. These findings underscore the role of mechanical cues in chondrocyte metabolism and inform future studies aimed at identifying metabolic targets relevant to post-traumatic osteoarthritis progression.

CRISPR interference (CRISPRi) has emerged as a versatile approach for targeted gene repression in many organisms, including microbes and bacteria, due to the simple design of sequence-specific transcriptional silencing of gene expression. However, the strain-specific effects on repression efficiency and the host when translating a CRISPRi system from a laboratory strain to non-model strains are not well understood, yet they can present important limitations to its use. Here, we investigated the repression efficiency and toxicity of three CRISPRi systems (one dCas9 and two dCas12a variants) across four different Escherichia coli strains, including a laboratory K-12 strain (MG1655) and three non-model strains that are clinical isolates (probiotic Nissle 1917, uropathogenic CFT073, and uropathogenic UMN026). We evaluated the repression in each strain using sets of guide RNAs (gRNAs) targeting along the gene sequence and assayed cytotoxicity of expressing each dCas protein. Growth toxicity from expression of the different dCas proteins notably differed and showed high variation between some host strains. We also observed variable repression among the strains and notably poorer repression in multiple clinical strains. Therefore, we developed a dual gRNA CRISPRi system for enhanced gene silencing among the strains, which achieved up to 824-fold repression in CFT073. The results demonstrate that strain-specific design considerations can arise when a CRISPRi genetic system is transferred to a closely related bacterial strain. These findings provide insight into the relationships between criteria used for CRISPRi genetic design and in vivo activity across non-model E. coli strains, providing guidelines for diverse applications of these tools.

Formate is emerging as an important molecule in carbon capture and utilization technologies. However, its low electron density makes formate less attractive for energy storage. Some hydrogenotrophic methanogens can reduce formate to methane, thereby upgrading it into an established energy carrier. The bottleneck in this process is that 75% of the carbon is lost as carbon dioxide, and achieving a complete formate-to-methane conversion requires co-feeding hydrogen. However, hydrogen-dependent genetic regulation of formate metabolism inhibits simultaneous formate and hydrogen utilization in hydrogenotrophic methanogens. Here, we compared the catalytic performance of the genetically modified strain Methanothermobacter thermautotrophicus {Delta}H (pFdh) with M. thermautotrophicus Z-245 by conducting continuous cultivation at different hydrogen concentrations. While M. thermautotrophicus Z-245 is a natural formatotroph, M. thermautotrophicus {Delta}H (pFdh) was engineered to enable formate utilization via episomal expression of a formate dehydrogenase-gene cassette. We found that M. thermautotrophicus {Delta}H (pFdh) can simultaneously utilize formate and hydrogen. It continuously consumed formate at {approx} 0.1 mM dissolved hydrogen, enabling a 75.6% formate-to-methane conversion efficiency. M. thermautotrophicus Z-245 showed a declining formate consumption at {approx} 0.016 mM and only reached a maximum stable efficiency of 36.3%. These results suggest that M. thermautotrophicus {Delta}H (pFdh) is largely insensitive to hydrogen-induced genetic regulation; however, it still faces redox-related metabolic limitations at dissolved hydrogen concentrations above 0.4 mM. Overall, the findings reveal a potential strategy to circumvent hydrogen-induced regulation of formate metabolism and identify M. thermautotrophicus {Delta}H (pFdh) as a promising biocatalyst for formate-to-methane conversion.

Plastic materials are widely used in engineered systems and increasingly accumulate in natural environments, where their surfaces interact with colloids, microorganisms, and dissolved organic matter. However, the relative roles of plastic surface properties versus particle-specific characteristics in governing organic matter retention remain poorly constrained. Here, attachment efficiency () was used to quantify intrinsic particle-collector affinity on three common thermoplastics (ABS, HDPE, HIPS) and glass beads as an inorganic reference. Surface chemistry, hydrophobicity, roughness, and charge were characterized, and interactions with submicron carbon particles (SCPs) and Escherichia coli were evaluated using column experiments. Extended DLVO (XDLVO) theory was applied to predict interaction energy barriers, and humic acid (HA) adsorption was quantified through batch isotherms. XDLVO modeling predicted higher affinity of particles for plastics relative to glass; however, experimentally measured attachment efficiencies were uniformly low ( < 0.05) across all materials. Attachment was primarily governed by particle size and surface charge rather than collector hydrophobicity, roughness, or surface chemistry. SCP consistently exhibited higher than bacteria, while differences among plastics were minor. Similarly, HA adsorption was weak and near-linear, with uptake following ABS {approx} HIPS > HDPE > glass, indicating reversible, partitioning-like association dominated by polymer-specific functionality rather than electrostatics. The absence of correlation between and XDLVO-predicted energy barriers further demonstrates limitations of classical physicochemical models in describing particle- plastic interactions. Collectively, these results indicate that pristine thermoplastic surfaces exhibit intrinsically low affinity for organic matter and that particle-specific properties dominate retention under low ionic strength conditions. Enhanced accumulation in environmental systems likely requires surface aging or conditioning processes not captured by classical interaction theory.

Hydrogenotrophic methanogens are of high environmental and biotechnological importance, converting CO2 with H2 into CH4. Despite their common metabolism, variations in the energy metabolism among these methanogens exist, likely affecting their H2 thresholds and growth yields. However, a systematic comparison of these traits for a wide range of hydrogenotrophic methanogens has been lacking. Here, we measured the H2 thresholds and growth yields of nine different hydrogenotrophic methanogens. The H2 threshold, i.e. the H2 partial pressure at which H2 consumption halts, ranged over two orders of magnitude from 1.0 {+/-} 0.5 Pa for Methanobrevibacter arboriphilus to 120 {+/-} 10 Pa for Methanosarcina mazei. Growth yields in our experimental conditions ranged from 0.51 {+/-} 0.28 gDCWx(mol CH4)-1 for Methanococcus maripaludis to 5.28 {+/-} 1.25 gDCWx(mol CH4)-1 for Methanosarcina mazei. The ATP gains, estimated from both H2 thresholds and growth yields, correlated reasonably well, confirming that these variations are due to differences in energy conservation strategies. Our results strongly differentiated the two previously proposed groups of hydrogenotrophic methanogens: methanogens with cytochromes had a high H2 threshold ([&ge;] 21 Pa) and high growth yield (> 4.0 gDCWx(mol CH4)-1), whereas methanogens without cytochromes had lower H2 threshold ([&le;] 7 Pa) and low growth yield (< 1.7 gDCWx(mol CH4)-1). Moreover, our H2 thresholds indicated that additional variations in energy metabolism exist within both groups. Overall, this study found strong variations between hydrogenotrophic methanogens, which are important to understand their environmental prevalence and biotechnological applicability.

Proteins can be actively packaged into extracellular vesicles (EVs) through mechanisms dependent on the stimulus that activated the cells. Identifying proteins released in endothelial EVs in response to stimuli relevant to cardiovascular disease (CVD) may therefore reveal potential biomarkers that provide information about the vascular endothelium. This study aimed to identify differentially expressed proteins in EVs released from human umbilical vein endothelial cells (HUVEC) in response to stimuli relevant to vascular endothelium activation. HUVEC were stimulated with TNF (10 ng/mL) or oxLDL (10 {micro}g/mL). Apoptosis was assessed using a flow cytometric DNA fragmentation protocol and caspase-3/7 activity assay. Size distributions of EVs were examined by nanoparticle tracking analysis. Isolated EVs were examined using tandem liquid-chromatography-mass spectrometry (LC-MS/MS). While treatment of HUVECs with TNF or oxLDL resulted in non-significant elevations in levels of EVs, only TNF increased apoptosis. Mass spectrometry quantified 1355 proteins and revealed significant differences in the proteome of EVs from TNF-treated HUVEC compared to EVs from oxLDL-treated or untreated cells. Several candidate biomarkers were significantly and differentially expressed in response to TNF, including E-selectin and dual specificity phosphatase 7. This study further associated E-selectin on endothelial-derived EVs with endothelial apoptosis and may offer a biomarker of endothelial damage in patients with CVD.

AimsTo characterize subtype-associated heterogeneity in type 2 diabetes mellitus (T2DM), particularly normal-weight diabetes, using extracellular vesicle (EV)-associated molecular features in a clinically stratified cohort. MethodsEVs were isolated from plasma using ExoTIC and validated by transmission electron microscopy, nanoparticle tracking analysis, flow cytometry, and Western blotting. EVs from Asian normal-weight (A-NWD), Asian overweight (A-OWD), Non-Hispanic White normal-weight (W-NWD), and Non-Hispanic White overweight (W-OWD) T2DM patients were analyzed by multimodal surface-enhanced Raman spectroscopy (SERS; n=65) and EV-RNA sequencing (n=39). ResultsSERS identified subgroup-associated spectral fingerprints that distinguished the four BMI- and race/ethnicity-defined groups in this cohort. EV-RNA sequencing revealed differential microRNA expression across subgroups, with higher miR-208a and miR-132 in A-OWD and higher miR-484 in A-NWD. Unsupervised analyses also showed partially overlapping EV-associated molecular features between A-NWD and W-OWD, suggesting that BMI-based subgrouping alone may not fully capture shared metabolic states. ConclusionsMultimodal EV profiling identified subgroup-associated spectral and miRNA features in clinically stratified T2DM and provides a framework for studying diabetes heterogeneity, including molecular patterns associated with normal-weight diabetes.

Cyclic dinucleotide (CDN) signaling molecules, such as cyclic di-GMP (c-di-GMP) and 3,3 cyclic GMP-AMP (cGAMP), are second messengers that play critical roles in phenotypic regulation, such as biofilm formation, host colonization, and bacterial virulence. Recently, hybrid promiscuous (Hypr) GGDEF proteins have been identified in certain bacteria to produce both cyclic dinucleotides. One such enzyme, Bd0367, from the predatory Bdellovibrio bacteriovorus, switches between synthesizing c-di-GMP and cGAMP to regulate the bacterial predation cycle and prey exit. However, the molecular mechanism controlling this switch remains unknown. Here, we introduce an RNA-based ratiometric, dual metabolite biosensor that enables simultaneous detection of c-di-GMP and cGAMP in live cells. This sensor integrates a Pepper-based biosensor for c-di-GMP detection and a Spinach2-based biosensor for cGAMP detection into a single transcript, producing distinct fluorescent outputs. In E. coli, the dual metabolite sensor reliably reported shifts in c-di-GMP/cGAMP production ratios from various CDN synthases, including Bd0367. Additionally, a histidine kinase was discovered as the probable regulatory partner of Bd0367. These findings demonstrate the sensors capacity to assess relative CDN levels and to uncover complex signaling pathways. Together, this ratiometric dual metabolite biosensor provides a foundation for broader applications of fluorogenic RNA biosensors in dissecting bacterial signaling networks, microbial ecology, and host-pathogen interactions.

BackgroundEpithelial-mesenchymal transition (EMT) and its reverse process Mesenchymal-Epithelial Transition (MET) are crucial during metastasis and therapy resistance. While the dynamics and master regulators of EMT are well-studied, the transcription factors that can prevent EMT or promote MET are relatively less understood. ResultsHere, by integrating bulk and spatial transcriptomic data analysis from cell lines and patient samples, with mechanism-based dynamical modelling, we identify IRF6 as a factor that strongly associates with an epithelial phenotype and is often inhibited during EMT. In vitro experiments in multiple cancer cell lines demonstrate the progression to a mesenchymal phenotype upon IRF6 knock-down, suggesting a role as an inhibitor of EMT. Finally, we observe that IRF6 expression levels correlates with worse patient survival in a subset of solid tumour types. ConclusionOur integrated computational-experimental systems-level analysis suggests that IRF6 is frequently downregulated during EMT and can also prevent the progression towards a complete EMT, underscoring its role as an MET stabilizing factor.

Respiratory infectious diseases are among the leading causes of global morbidity and mortality and remain a major public health concern. Progress in understanding early host-pathogen interactions has been hampered by the limited physiological relevance of existing experimental systems. Different models mimicking the human respiratory epithelium have been developed to study viral infections in vitro, such as tridimensional (3D) tissue models and organoids. However, many lack key features of human tissue architecture, particularly the lamina propria or immune cells. To address these limitations, we established an immunocompetent 3D model of the human respiratory mucosa by combining nasal epithelial cells isolated from nasal brushings, fibroblasts from mid-turbinate nasal biopsies, and macrophages derived from blood monocytes. These cells were sequentially seeded into collagen-chitosan scaffolds, resulting in a reconstructed respiratory mucosa closely resembling the in vivo nasal tissues. To further confirm the physiological relevance of the model, we infected it with influenza A virus. The mucosa model supported viral replication in the epithelium and consequently showed increased secretion of inflammatory cytokines and upregulation of type I interferon related genes, enabling the monitoring of early antiviral innate immune responses in a physiologically relevant context.

Cell mechanics can serve as an important biomarker for cell state and phenotype, such as metastatic ability. While some molecular mechanisms underlying cell mechanical properties have been investigated through targeted analyses, a genome-wide study of human genes and gene networks that modulate cell biophysical properties has not been attempted. In this work, we combined a microfluidic stiffness-based sorting device with a genome-scale CRISPR knockout (GeCKO) screen in order to investigate the effect of individual gene knockouts on cell stiffening and cell softening across the entire protein-coding genome. We processed approximately 150 million Cas9-expressing ovarian cancer cells that had been transduced with a library of 76,000 single guide RNAs (sgRNAs) against the 19,000 protein-coding genes in the genome. The cells were sorted into 5 mechanical subsets. We identified 7 gene knockouts that were significantly depleted in the softer subsets and over 700 gene knockouts that were significantly enriched in the stiffer subsets. Of these significant genes of interest, we selected 3 genes that were highly expressed in our ovarian cancer cell line with greater than 100-fold enrichment in the stiff outlet and resulted in significant changes in ovarian cancer patient survival. These genes, PIK3R4, CCDC88A, and GSK3B, when knocked out result in a significant and predicted increase in cell stiffness. This study is the first to explore the relation between human gene expression and cell mechanics at the genome-scale to generate datasets at the intersection between cell genotype, mechanotype, and phenotype for metastatic cancer cells. The method could also be applied to study the effect of genes on other biophysical cell processes as well as for identifying pathways for the control of cellular mechanics across many cell types.

Discovering proteins that modulate receptor activity remains a key challenge in the field of protein design and engineering. Traditionally, identifying proteins that interact with receptors often relies on binding as a selection criterion, yielding limited information about the function of discovered binders in a library, including the ability to activate or block signaling cascades associated with the receptor of interest. As a result, extensive downstream characterization is required to assess the biological relevance of discovered binders. To address this issue, we have developed a high-throughput screening system to screen dimeric mammalian receptors using yeast surface display. We demonstrate the programmed dimerization of the extracellular domains of mammalian receptors in yeast via engineered induction pathways, thereby enabling receptor expression and the secretion of associated native cytokines. This surface expression of the involved subunits for the protein receptor and cytokine-induced dimerization activity indicates that the receptor has been activated and is expected to trigger a DNA-driven signaling cascade within a mammalian cell. This system provides a modular platform technology that advances existing yeast-display systems, demonstrating the effectiveness of these high-throughput platforms for screening the function of mammalian receptors. This work is expected to provide a rapid, cost-effective approach to the molecular discovery of novel biologics for targeting dimeric mammalian receptors.

Mutant Insulin Induced Diabetes of Youth (MIDY) is an established porcine model caused by the INSC94Y mutation, which results in misfolded insulin, leading to severe {beta}-cell loss and hyperglycemia. Understanding disease pathophysiology is critical for identifying biomarkers and therapeutic targets, and animal models play a key role in this process. In this study, we re-analyzed published transcriptomic and proteomic data from the MIDY model using advanced multi-omics approaches and our in-house SurfacOmics tool. This integrative analysis identified ADAMTS17 as a novel biomarker, suggesting a potential association in diabetes-associated immune dysfunction and delayed wound healing through ECM-immune interplay.

Osteoarthritis (OA) is a multifactorial joint disease driven by complex interactions among chondrocytes, osteoblasts, fibroblasts, and immune cells across cartilage, bone, and synovial tissues. Conventional monoculture systems are unable to capture this crosstalk, limiting their physiological relevance. Building on our previously established joint-on-a-chip platform, this study evaluated multicellular communication and assessed whether a microfluidic co-culture provides a more realistic representation of joint inflammation compared with monoculture models. Two configurations were established: a healthy, low-inflammation model containing M0 macrophages and an OA-like, high-inflammation model with M1 macrophages. In healthy models, co-culture significantly increased MMP-1 ([~]4-fold), MMP-3 ([~]15-fold), TIMP-2 ([~]5-fold), IL-6 ([~]6-fold), and IL-8 ([~]5-fold) relative to monoculture, indicating that endogenous signaling initiates basal matrix remodeling and inflammatory pathways. In disease models, M1-driven co-culture elevated MMP-10 ([~]300-fold) and MMP-13 ([~]60-fold), along with TIMP-2 ([~]5-fold), compared with monoculture, reflecting amplified catabolic activation. Direct comparison of disease versus healthy co-culture revealed additional increases in MMP-10 ([~]55-fold), MMP-13 ([~]95-fold), MCP-1 ([~]1.6-fold), MMP-1 ([~]1.6-fold), MMP-3 ([~]1.8-fold), TIMP-1 ([~]1.4-fold), and TIMP-2 ([~]1.5-fold), representing a macrophage-mediated shift from homeostasis to OA-like pathology. However, neither IL-1 nor TNF, each a key inflammatory mediator of OA, differed measurably between healthy and disease models under either monoculture or co-culture conditions. Thus, the microfluidic joint inflammation-on-a-chip model presented here more faithfully recapitulates the pathogenic MMP profile of OA than monoculture systems, but it does not yet fully recapitulate the pathogenic inflammatory environment of OA.

Extracellular matrix (ECM) remodeling is essential for adaptation to changing mechanical demands, yet the mechanisms linking altered strain to functional outcomes remain poorly understood. This study aimed to define molecular and cellular programs driving the adaptation of tendon to increased (exercise) and decreased (disuse) strain. Male murine flexor tendon explants were cultured in incubator-housed tensile bioreactors and subjected to step changes in cyclic strain. After acclimation at 1% cyclic strain, exercise tendons experienced a step increase to 5% strain, while disuse tendons underwent stress deprivation. Increased strain produced significant mechanical adaptations, including increased elastic modulus and failure stress. Multiscale analyses of matrix organization, tissue composition, protein synthesis, signaling factors, and proteolytic activity revealed the mechanisms underlying these adaptations. Exercise-induced functional improvements were linked to an anabolic remodeling program characterized by TGF-{beta} and IL-6 signaling, small leucine-rich proteoglycan expression, MMP suppression, and enhanced collagen alignment. These findings indicate that regulators of matrix organization and turnover, beyond synthesis alone, are critical for functional adaptation. In contrast, mechanical unloading reduced collagen synthesis and alignment and promoted an MMP-dominant, catabolic phenotype favoring matrix breakdown. This study provides a comprehensive characterization of ECM remodeling, linking defined mechanical perturbations to molecular regulation and emergent structure-function relationships. These findings identify targetable mediators of adaptive remodeling and establish a framework for future studies of maladaptive ECM changes in aging, injury, and disease.

In gene editing, CRISPR/Cas approaches are often limited by off-target effects. In in vivo approaches involving multiple cell types, off-targets may result from unintended targeting of the wrong cells. In this work, we propose a solution to this limitation by using a transcribed intron of the target gene as an endogenous trigger (intron triggers) for a novel conditional guide RNA (intcgRNA). In vitro, intcgRNAs were responsive to the presence of the trigger. As a proof-of-concept, the human IL2 receptor subunit gamma gene (IL2RG) was then targeted using both the intcgRNA and the corresponding conventional crRNA in two cell lines: the lymphocytic HPB-ALL cell line, where IL2RG is highly expressed, and the epithelial HeLa cell line, where it is not. Sanger sequencing revealed that the crRNA and intcgRNA Cas9 complexes edited IL2RG with similar efficiency in HPB-ALL, whereas only the crRNA edited IL2RG in HeLa. This shows that intcgRNA avoids targeting unwanted cells that do not express the target gene, which is particularly relevant for in vivo targeting. The triggers of choice for conditional guides have been microRNAs, but as short intronic RNAs are far more diverse, trigger introns could become biomarkers of cell identity that improve the precision of CRISPR-based manipulations in vivo. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=83 SRC="FIGDIR/small/714022v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1ae60cdorg.highwire.dtl.DTLVardef@1556c03org.highwire.dtl.DTLVardef@1264a0dorg.highwire.dtl.DTLVardef@c7d47d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Pseudomonas putida strain KT2440 is a crucial model organism for synthetic biology and bioengineering applications, yet there currently exists no comprehensive metabolomics database comparable to those available for other model organisms. This gap hinders the use of untargeted metabolomics for exploratory analyses in this system. We developed the P. putida metabolome reference database (PPMDB v1) to address this limitation by consolidating metabolite information from multiple sources and expanding coverage through computational predictions. The database was constructed by curating metabolites from BioCyc, BiGG, and other literature sources, then computationally expanding this collection using BioTransformer environmental transformation predictions to generate additional predicted metabolites. We enhanced the databases utility for molecular annotation in metabolomics studies by incorporating analytical properties including collision cross-sections, tandem mass spectra, and gas-phase infrared spectra. These analytical properties were gathered from existing measurement data or predicted using computational tools. We further augmented the database through inclusion of reaction information and pathway annotations, facilitating biological interpretation of metabolomics data. This publicly available resource fills a critical gap in P. putida research infrastructure, supporting metabolite annotation and biological interpretation in untargeted metabolomics studies and enabling in-depth exploratory analyses of this important synthetic biology platform at the molecular level. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/713193v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@c8828forg.highwire.dtl.DTLVardef@1f3a5c5org.highwire.dtl.DTLVardef@1084535org.highwire.dtl.DTLVardef@1f7ca4a_HPS_FORMAT_FIGEXP M_FIG C_FIG