npj Biofilms and Microbiomes

Pancreatic ductal adenocarcinoma (PDAC) harbors a distinct intratumoral microbiome. Yet rigorous characterization of its composition is hampered by pervasive environmental and procedural contamination. Sources of contamination have not been thoroughly explored, and the methods of decontamination have not been sufficiently evaluated in a benchmarking manner. We systematically collected >300 negative control (NCT) samples comprising paraffin from formalin-fixed paraffin-embedded (FFPE) samples, lysis buffer and sterile water over a period of four years processed by different laboratory persons (LP). All samples were sequenced using full-length 16S rRNA gene sequencing with Oxford-Nanopore Technologies. We benchmarked four decontamination methods (restrictive filtering, decontam, SCRuB, and the Nejman et al.-derived (Nj) pipeline) against fresh-frozen tumor samples (FF) from LSL-KrasG12D/+;LSL-Trp53R172H/+;Pdx-1-Cre (KPC) mice, using the abovementioned contamination assessment to calculate a composite score for the assessment. Further, we validated those methods via technical replicates. Microbial profiles of NCT samples were significantly determined by control type, LP, year and season reflecting complex batch effects. The 15 most abundant contaminants spanned well-characterized environmental taxa and human commensals from the oral cavity. The LP processing samples left a significant microbial trace highly contributing to the batch effect. Decontamination benchmarking demonstrated that the Nj method consistently outperformed alternatives in both composite score and inter-replicate concordance. Application of Nj to fresh frozen PDAC samples substantially reduced contaminant burden while preserving putative tumor-associated signals in FF but not FFPE samples. Our results support the adoption of the Nj decontamination approach for future intratumoral microbiome studies in fresh frozen tumor samples.

Background Microbiome-derived metabolites regulate host physiology, yet bacterial gaseous metabolites remain largely overlooked. Traditionally regarded as fermentation end-products, bacterial gases may act as biologically active mediators of host-microbiome communication. We hypothesized that bile acids regulate bacterial gaseous metabolism and influence host epithelial responses. Methods A high gas-producing clinical Escherichia coli isolate from a patient with moderately severe acute pancreatitis was cultured with selected primary and secondary bile acids. Gas production was assessed by pressure measurements, GC-TCD and GC-MS. Biological activity was evaluated by indirect exposure of Caco-2 and PANC-1 epithelial cells, followed by apoptosis/necrosis assays and whole-transcriptome RNA sequencing. Results Bile acids markedly reshaped bacterial gaseous metabolism. Cholic acid and deoxycholic acid promoted intense gas production, whereas chenodeoxycholic acid almost completely abolished it. Despite minimal apoptosis and necrosis, bacterial gaseous metabolites induced extensive transcriptional remodeling. Caco-2 cells showed stronger responses than PANC-1 cells, particularly to deoxycholic acid-derived gases, involving inflammatory signaling, extracellular matrix remodeling, epithelial plasticity, stress responses, and cancer-associated genes including PTGS2, MMP1, PLAUR, NR4A2, and SERPINE1. PANC-1 cells exhibited a more restricted response involving oxidative stress, proteostasis, and autophagy-associated pathways. Conclusions Our findings indicate that bacterial gases are a previously underrecognized class of microbiome-derived signaling molecules capable of modulating host gene expression independently of direct bacterial contact. We identify a gas-producing microbiome phenotype regulated by bile acid composition, linking microbial metabolism with epithelial signaling. These findings expand the concept of host-microbiome communication and provide a framework for investigating bacterial gaseous metabolites in intestinal and pancreatic diseases.

Microbial communities are dynamic, adaptive ecosystems whose collective behavior emerges from metabolic interactions such as cross-feeding, competition, and cooperation, rather than taxonomic diversity or individual metabolic potential alone. This distinction is clinically significant in the postmenopausal urinary tract, where recurrent urinary tract infections (rUTIs) are associated with complex, persistent infection dynamics including multiple contributing bacterial species. The ability of resident microbial communities to prevent pathogen establishment, known as colonization resistance, is increasingly attributed to the metabolic interactions within the urobiome itself rather than any single resident species. However, current approaches, such as taxonomic profiling and classical differential abundance analysis, can only partially describe the presence or maintenance of such interactions. Consequently, the community-level metabolic architecture determining pathogen resistance remains incompletely understood. To address this gap, we developed PhenoRewire, a network-based framework that quantifies how metabolite co-variation is rewired between biological states using untargeted metabolomics data. We applied this framework to an induced pluripotent stem cell (iPSC) urothelial organoid-derived barrier co-cultured with synthetic urobiome communities as a model of urobiome-pathogen dynamics relevant to rUTIs in two approaches. In an infection model, clinically isolated uropathogens Escherichia coli and Enterococcus faecalis, were co-cultured with a three-member urobiome community consisting of Lactobacillus gasseri, Lactobacillus crispatus, and Gardnerella vaginalis. Here we show how E. coli drove the metabolic reorganization, while E. faecalis amplified it disproportionately. PhenoRewire disentangled the 6-fold metabolic network amplification mediated by E. faecalis as a metabolic facilitator, revealing an emergent urobiome-pathogen co-variation architecture (1,781 vs 227 edges) not recapitulated by either community alone. Moreover, in a six-member urobiome single-strain dropout experiment, we revealed that removal of the sole Actinomycete Winkia anitrata caused significant network collapse (Louvain modularity falls from 0.707 to 0.038), identifying it as the single non-redundant keystone of the community. More broadly, these results demonstrate how untargeted metabolomics co-variation network analysis can be applied to defined synthetic urobiomes in combination with a urothelial host model to elucidate community dynamics. This framework provides a template that can be extended beyond the urobiome to investigate any complex microbial community where ecological behavior remains an open question.

Rinsing-dependent dental hygiene presents a significant public health challenge in water-scarce environments. This study investigated combinations of xylitol (Xyl), chitosan (Chi), glycyrrhizin (Gly), epigallocatechin gallate (EGCG), dicalcium phosphate (DCP), and nano-hydroxyapatite (nHA) on the primary bacteria behind dental caries, S. mutans. These combinations were assessed for markers of dental caries by biofilm reduction, bacterial killing, and acid buffering against S. mutans when applied to an in vitro simulated enamel model using glass bead surfaces for biofilm formation, and gene expression was subsequently examined via RT-qPCR. Separately, mineral retention was also quantified. The EGCG-DCP-Xyl film demonstrated the highest overall efficacy, achieving a significant reduction in biofilm concentration compared to the untreated control and performing similarly in magnitude to the positive toothpaste control. Dead fluorescence staining confirmed that the EGCG-DCP-Xyl film induced the highest rate of non-viable cells, followed by the Chi-Gly film and the Gly-Xyl film. During 10-day pH cycling, the EGCG-DCP-Xyl and DCP-Xyl formulations buffered pH the most, consistently maintaining mean pH levels safely above the demineralization threshold of pH 5.5. The EGCG-DCP-Xyl also optimized mineral stability with the highest retained calcium concentration, significantly outperforming the Chi-Xyl film. At the transcript level, the EGCG-DCP-Xyl film induced substantial downregulation of key virulence genes, yielding decreases in expression for glucosyltransferase B (gtfB), associated with biofilm synthesis, collagen-binding protein (cnm), associated with tissue invasion, and lactate dehydrogenase (ldh), associated with lactic acid production, compared to the untreated control, with effects comparable in magnitude to the positive toothpaste control. This research suggests that targeting bacterial pathways and mineral loss through a portable film may have potential for preventing dental caries, especially in environments where water is limited. However, additional studies are necessary to evaluate real-world effectiveness.

Enterococci are opportunistic pathogens classified by the World Health Organization as high-priority microorganisms. They cause a broad spectrum of infections, and their intrinsic and acquired resistance to antimicrobials makes these infections particularly difficult to treat and eradicate. In Enterococcus faecalis, the most frequently isolated enterococcal pathogen in humans, antimicrobial resistance and innate immune evasion are largely driven by the Enterococcal Polysaccharide Antigen (EPA). This surface polymer underpins key virulence traits, including resistance to host defence mechanisms, reduced susceptibility to multiple classes of antimicrobials, and susceptibility to bacteriophage infection. EPA consists of a rhamnan backbone decorated with strain-specific substituents that are essential for its biological activity. Here, we show that epaB encodes the enzyme responsible for the first committed step in assembling the EPA rhamnan chain. Using NMR spectroscopy, we demonstrate that E. faecalis lacking epaB produces an EPA polymer composed solely of decorations directly anchored to the peptidoglycan, with no detectable rhamnan backbone. The absence of this rhamnan moiety profoundly alters cell wall architecture, as revealed by atomic force microscopy of the mutant cell walls. The epaB mutation also abolishes innate immune evasion and virulence in the zebrafish infection model, while conferring resistance to bacteriophages. Collectively, these findings demonstrate that both the rhamnan backbone and its decorations are required for EPAs full biological activity, establishing the structural and functional interdependence of these two components.

Winogradsky columns are a classic model ecosystem for studying microbial biogeochemistry across steep gradients of oxygen and sulfide. They also remain widely used in microbiology education, introducing generations of students to microbial diversity. Yet, the genomic potential of their microbial communities remains uncharacterized. Here, we applied shotgun metagenomic sequencing to a Winogradsky column community at multiple depths, yielding 20 metagenome-assembled genomes (MAGs) representing diverse, largely uncultivated taxa. Genome-resolved analyses revealed metabolically diverse oxygenic and anoxygenic phototrophs that could potentially contribute to carbon and nitrogen fixation across all layers of the column. Most of these phototrophs also encoded one or more pathways for sulfur oxidation, which we speculated may support both energy conservation and/or sulfide detoxification by these populations. Complex carbon degradation capacity was also widespread across the MAGs, suggestive of the potential for the transformation of the column's amended organic matter (shredded coffee filters) into smaller depolymerization products and, through fermentation, organic acids. Together, these findings reveal how distinct microbial guilds might partition interconnected carbon, sulfur, and nitrogen transformations within redox-stratified systems.

Genetic variation among microbial strains of the same species can profoundly influence their phenotypes, ecological functions, and impacts on human health. Traditionally, the relative abundance of a species has been used to identify associations between the microbiome and disease. However, this approach overlooks intra-species genetic variation and is susceptible to spurious correlations arising from the compositional nature of abundance data and microbial load. Fast, k-mer-based algorithms can now accurately estimate strain-level Average Nucleotide Identity (ANI) in metagenomes. Despite its value as an orthogonal metric for strain-level analysis, methods for conducting ANI-based association studies remain limited. To address this, we developed StrainSpy, a statistical algorithm that identifies associations between containment ANI and variables of interest across a wide range of study designs, including longitudinal and multi-cohort designs. Re-analysis of a study examining gut microbiota recovery in 12 healthy adults following antibiotic exposure revealed novel strain-level associations, including a reduction in strain-level diversity despite species persistence. Applying StrainSpy to a multi-cohort analysis of 3,414 colorectal cancer metagenomes identified novel strain-level associations with colorectal cancer. However, in a separate collection of microbiome-immunotherapy studies, no individual strain was consistently associated across cohorts. Importantly, across both datasets, StrainSpy informed containment ANI-based machine learning models achieved comparable accuracy to traditional abundance-based methods. StrainSpy is publicly available as an R package github.com/gtonkinhill/strainspy.

Intertidal mudflats are low hydrodynamic energy environments hosting microphytobenthic communities that experience strong spatiotemporal variability in light regimes, including changes in spectral quality and light intensity that can lead to cellular photooxidative stress. To cope with these fluctuations, autotrophs exhibit diverse and highly plastic adaptations that are often species-dependent and shaped by their ecological niches. This study investigates photophysiological responses and metabolic remodeling in a diatom assemblage originating from a natural winter microphytobenthic biofilm under contrasting red and blue light intensities. To this end, photosynthetic parameters were monitored alongside changes in lipophilic metabolites, including untargeted lipids and lipophilic pigments. While few metabolites showed temporal remodeling, rapid and contrasting changes were observed within 30 minutes in response to both spectral quality and light intensity. Red light treatments induced broader remodeling of lipophilic metabolites than blue light, whereas blue light appeared to have a greater impact on photosynthetic parameters. Moreover, red light induced xanthophyll-cycle responses comparable to those observed under blue light at equivalent incident intensity. We discuss these metabolic responses in relation to diatom photoadaptive strategies, placing these findings within the intertidal environmental framework. This work further underlines the importance of understanding rapid metabolic plasticity in coping with light fluctuations, providing new insights into the photoregulatory strategies of natural microphytobenthic communities.

Enterococcus faecalis is an opportunistic pathogen and facultative anaerobe that primarily relies on fermentative metabolism to colonize a wide range of aerobic and anaerobic environments. In the presence of exogenous heme, E. faecalis can assemble a minimal electron transport chain consisting of membrane-associated primary dehydrogenases, demethylmenaquinone, and the terminal cytochrome bd oxidase (CydAB). This respiratory chain is thought to generate a proton motive force to drive ATP synthesis via the F-type ATP synthase, thereby improving energy conservation under aerobic conditions. However, a cytosolic NADH oxidase (Nox) also consumes NADH and oxygen, potentially competing with the electron transport chain for reducing equivalents and terminal electron acceptors; but the relative physiological contributions of these two oxygen-reducing pathways remain poorly understood. To define the roles of CydAB and Nox under normoxic and hypoxic conditions, we constructed {Delta}cydAB and {Delta}nox mutants. Real-time, in situ measurements revealed {Delta}cydAB had no significant effect on oxygen utilization while in the {Delta}nox it was significantly reduced; revealing Nox as the major consumer of oxygen. Semi-untargeted metabolomic analysis further revealed oxidase-specific alterations in central metabolism with the {Delta}nox causing pronounced shifts in the ATP and NADH ratios; highlighting Nox as a key determinant of intracellular redox and energy homeostasis. Finally, single-cell fluorescence microscopy showed that membrane potential, a component of proton motive force, was substantially diminished only in the absence of both CydAB and Nox, or the F-type ATP synthase. These findings indicate that the F-type ATP synthase is a major generator of proton motive force, even upon aerobic growth, and demonstrate a complementary role for the electron transport chain and Nox in the bioenergetics of E. faecalis.

Adhesion of cells is the key factor determining functioning of multicellular organisms. Viscoelastic properties of cells can be studied by multiple methods. However, attractiveness of cells or extracellular matrix without the elastic component (dispersive adhesion) is not accessible. We present an extension of force spectrometry technology: the Multivalent Adhesive Probe Atomic Force Microscopy (MAPA) that delivers dispersive adhesion maps of live cells and biosurfaces, and identifies differences unresolved by viscoelastic probing.

Constructing microbial association networks is a common strategy for exploring relationships among taxa in microbiome studies. Although marginal correlation methods are easy to implement and allow formal inference, they can produce spurious edges driven by indirect associations through other taxa. Conditional graphical-modeling methods aim to recover direct associations, but many rely on Gaussian or linear assumptions and often provide limited uncertainty quantification. We propose a conditional, nonparametric approach based on the scaled expected conditional covariance (SEcov). SEcov measures population-level conditional association by residualizing each taxon with respect to the remaining taxa and scaling the resulting expected conditional covariance. The resulting estimator can incorporate flexible machine-learning methods for conditional-mean estimation and admits asymptotic normal inference, enabling p-values and confidence intervals for taxon-pair associations. We demonstrate through simulation studies that our proposed approach improves network recovery relative to other methods, and we illustrate the new method via construction of a co-occurrence network for the vaginal microbiome during pregnancy. IMPORTANCEHigh-throughput sequencing has made it possible to characterize microbial communities at large scale, and network analysis is widely used to summarize relationships among taxa. However, networks based on marginal correlations may include indirect associations, whereas many conditional graphical models rely on assumptions that may be difficult to justify for sparse, zero-inflated, compositional microbiome data. SEcov offers a practical alternative by estimating conditional associations nonparametrically and attaching inferential uncertainty to individual edges. This allows investigators to construct microbiome networks using statistically interpretable evidence for taxon-pair associations, rather than relying solely on arbitrary correlation cutoffs or regularization tuning parameters.

The Bacillus cereus group comprises bacteria of biotechnological interest, but also raises health concerns. Some bacteria in this group are opportunistic human pathogens, mainly causing foodborne gastrointestinal infections. As of today, the presence, sequence variability, or expression of genes encoding toxins or other virulence factors are insufficient to predict the potential of a given isolate to cause the diarrheal form of the disease. To address this limitation, we developed a sandwich ELISA to quantify the NheA and Sphingomyelinase (SMase) proteins in culture supernatants to test them as markers of pathogenic potential. Application of the assay to a collection of B. cereus group isolates revealed that strains associated with food poisoning outbreaks produce significantly more NheA and SMase than those isolated from the environment or from commercial products. Statistical analyses show that the combined quantification of NheA and SMase provides robust discrimination between pathogenic and non-pathogenic (environmental and commercial) profiles. These results demonstrate that the quantitative assessment of both NheA and SMase production can serve as a reliable biomarker for distinguishing diarrheic food poisoning isolates from harmless strains.

Water availability is critical for plants and their microbial communities, including pathogens. The plant pathogen Phytophthora cinnamomi persists in soils with fluctuating moisture, yet cellular responses to water limitation remain poorly understood in Phytophthora and oomycetes more broadly. Although we recently characterized the proteomic response of P. cinnamomi to NaCl-induced osmotic and ionic stress, its response to PEG-mediated water limitation remains poorly understood, leaving a critical gap in our understanding of drought-relevant stress adaptation. Here, we quantified mycelial growth and profiled time-resolved proteome dynamics of P. cinnamomi during polyethylene glycol (PEG-3350)-treatment, simulating moderate water limiting conditions. Treatment with 5% PEG-3350 enhanced radial mycelial growth relative to controls, with no early growth inhibition observed. Label-free proteomics identified 1,097 protein groups, with 880 proteins shared between conditions and an asymmetric abundance profile dominated by decreasing protein abundance over time. Only a small subset of proteins increased, mainly enzymes involved in redox buffering (e.g., thioredoxin and glutaredoxin-like proteins) and mitochondrial/metabolic regulation (e.g., alternative oxidase) and mitochondrial/metabolic regulation. Hierarchical clustering revealed a potential three-phase temporal program: early translational and regulatory remodeling (1-6 HPT), sustained metabolic adjustment (6-12 HPT), and delayed engagement of redox and proteostasis functions (12-24 HPT). Network analysis demonstrated that redox-associated function was integrated throughout this adaptation, with individual clusters further specialized by cofactor preference (NADP- versus NAD-dependent enzymes) and distinct metabolic roles (malate dehydrogenase, CoA-ligase activity). This coordinated, multi-phase reorganization sustained mycelial growth despite moderate osmotic stress, indicating that P. cinnamomi employs active proteomic adaptation rather than passive stress tolerance. These findings reveal the cellular mechanisms underlying drought persistence in this invasive pathogen and suggest molecular targets for disease management under water-limited conditions.

Objective As antimicrobial resistance (AMR) continues to threaten global public health, bacteriophage therapy products (BTPs) offer a promising alternative to conventional antimicrobials. However, translation into routine clinical practice requires best practice standards for manufacturing and quality control to ensure the consistent safety, quality, and reliability of personalised BTPs produced for individual patients or small cohorts. Design A modified Delphi methodology was used to develop consensus statements, engaging experts from Australia's National Bacteriophage Therapy Regulatory Working Group across the fields of clinical microbiology, phage biology, good manufacturing practice (GMP), regulatory science, and government. The process comprised three iterative phases: (1) structured statement development, (2) an anonymous REDCap survey, and (3) a hybrid consensus meeting. The strength of evidence and recommendations was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. Results Consensus was reached on 35 statements to provide best practice manufacture and quality control guidance for BTPs. These statements address requirements for phage identification and characterisation; define the point at which GMP-aligned processes commence for ubiquitous phages; outline quality control expectations for phage active pharmaceutical ingredient (pAPI) production and maintenance of BTP and host cell repositories. Additional guidance covers quality management systems, including documentation, traceability, and governance. Conclusion These consensus statements provide comprehensive best practice recommendations for the manufacture and quality control of BTPs in Australia. By promoting consistent, safe, and quality-assured approaches to personalised BTPs, they aim to facilitate clinical implementation while remaining aligned with existing international pharmacopoeial standards and regulatory frameworks.

Bladder carcinoma in situ (CIS) is a multifocal, non-muscle-invasive disease with a high risk of progression to muscle-invasive cancer. Current management strategies are often guided by genomic profiling of single tumor samples, which incompletely capture tumor heterogeneity and may contribute to treatment failure. In particular, the multifocal nature of CIS raises uncertainty regarding the uniformity of genomic, immunologic, and microenvironmental features across anatomically distinct sites within the same patient. To address this, we performed spatial transcriptomic profiling of CIS-containing tissue from four anatomically distinct sites within a single individual. Unsupervised clustering with marker-based annotation, integrated with metabolic inference, identified epithelial tumor populations alongside stromal, immune, and smooth muscle compartments. While key cellular states were conserved, their spatial organization and relative abundance varied by site. Metabolic analysis further revealed region-specific microenvironments shaped by local cellular architecture. These findings indicate that both cellular composition and metabolic activity are spatially structured. Collectively, these results demonstrate that CIS exhibits significant intra-patient heterogeneity not captured by single-site profiling. These findings require validation in larger cohorts but support multi-region sampling could help improve risk stratification, biomarker development, and prediction of response to intravesical therapies, with potential implications for more personalized treatment strategies.

Background: Spatial organization is increasingly recognized as a key determinant of tumor-immune interactions in head and neck squamous cell carcinoma (HNSCC). The GSE300147 Xenium spatial transcriptomic resource generated by McCord and colleagues established a framework for mapping spatially coordinated T-cell states in HNSCC. However, how tumor-enriched epithelial immune states relate to metabolic, redox, and stress-adaptive transcript programs remains incompletely defined. Methods: A secondary, data-driven reanalysis of GSE300147 was performed, focusing on 17 confirmed HNSCC Xenium sections after exclusion of a non-HNSCC ameloblastoma specimen. A total of 1,148,244 cells were analyzed, including 558,867 EpCAM+ tumor-enriched epithelial cells. Tumor-enriched epithelial cells were classified into Hot, Intermediate, and Cold states using a Composite Hotness framework integrating T-cell inflammatory signature score, checkpoint-associated signaling, CD274 expression, IFN/antigen-presentation signature score (IFN/AP), and tumor-immune proximity. Six metabolic ecosystem states, neighborhood profiling, spatial permutation testing, and an integrated Immune-Metabolic-Redox Ecosystem Score (IMRES) were then applied. Results: Immune activation was spatially heterogeneous across HNSCC sections. Immune-hot tumor-enriched epithelial regions showed not only inflammatory, checkpoint-associated, and antigen-presentation signature scores, but also coordinated metabolic, oxidative-redox, and stress-response transcript programs. IMRES, derived from available immune, metabolic, redox, and stress-response transcript components represented in the Xenium panel, increased progressively from Cold to Intermediate to Hot tumor-enriched epithelial states and was associated with NFE2L2, GDF15, HLA-DRA, CD274, KEAP1, and MDM2. Integrating IMRES with Composite Hotness identified a distinct Hot+IMREShigh ecosystem comprising 106,874 tumor-enriched epithelial cells. This state showed the strongest immune-active and stress-adaptive features and was positioned closer to immune populations than expected by random assignment. An alternative rank-based robustness analysis reproduced the IMRES-associated ecosystem axis and correlated with the original module-based score (Spearman r = 0.597). Conclusions: This secondary reanalysis extends the original spatial T-cell framework by defining a complementary tumor-centered immune-metabolic-redox ecosystem in HNSCC. IMRES provides a transcript-derived framework for identifying Hot+IMREShigh neighborhoods where immune activation, checkpoint signaling, metabolic remodeling, and stress adaptation converge, providing a hypothesis-generating framework for studying immune resistance and therapeutic vulnerability.

Recurrent urinary tract infection represents a substantial unmet public health in women. Local administration of estradiol has been shown to reduce recurrence, however in vitro models of the female urinary tract remain limited and the mechanisms underlying the effects of estradiol are incompletely understood. Here, we describe a novel iPSC organoid differentiation protocol and its application to establish a multilayered transwell barrier culture model. Estradiol treatment resulted in reduced expression of innate antimicrobial peptides and cytokines, together with increased expression of demannosylation pathways. Treatment of transwell cultures with a combination of female sex hormones reduced endogenous CXCL8 signaling, independently of a 24-hour uropathogenic Escherichia coli (UPEC) challenge. To our knowledge, this is the first iPSC organoid-derived model of the urinary tract, which provides a platform for investigating interactions between the urothelium, urobiome and hormonal environment.

Decellularized extracellular matrices (ECMs) are widely used in regenerative medicine, yet current evaluation criteria prioritize cellular removal rather than preservation of the ECM characteristics that govern tissue behavior. Here, we demonstrate that efficient decellularization is achieved across a broad range of chemical conditions, whereas preservation of structurally and biologically relevant ECM components is confined to narrow, tissue-specific windows defined by coupled detergent interactions. Quantitative proteomics revealed that intrinsic ECM composition is strongly associated with tissue-specific susceptibility to decellularization-induced damage and provided molecular context for the distinct preservation responses between tissues. Optimized matrices retained major structural ECM components and supported tissue-specific cellular organization and cell-mediated mechanical reinforcement following cellular repopulation despite uniformly low residual DNA across protocols. Together, these findings support a shift in decellularization quality assessment from DNA-based evaluation toward preservation of biologically relevant ECM and establish a composition-driven strategy for the rational design of regenerative biomaterials with tissue-relevant biological and mechanical properties.

Maintaining a prescribed composition in engineered microbial consortia is difficult because small fitness differences can drive competitive exclusion. We study a two-strain consortium in continuous culture and develop a feedback architecture that regulates composition by selectively slowing the fast strain as a function of the population ratio. At the population level, we derive an idealized ratio-feedback law with a tunable positive coexistence equilibrium. We then propose a biomolecular realization using orthogonal quorum sensing, an sRNA-based ratiometric controller, and a ppGpp-mediated growth actuator. Exploiting the separation between slow population growth and faster intracellular controller dynamics, we use singular perturbation theory to show that, for sufficiently fast controller dynamics, the full implementation model inherits the coexistence equilibrium and its local stability properties from the reduced model. Numerical simulations validate the reduction and show how weaker timescale separation or loss of the assumed molecular regime degrades performance.

The continued emergence of Neisseria gonorrhoeae (Ng) isolates resistant to front-line antibiotics has focused efforts on understanding how alternative therapies, such as the expanded use of gentamicin (Gen), might counteract this global public health problem. Focusing on Gen as a viable alternative antibiotic for the treatment of gonorrheal infections, we previously used RNA-seq to determine if sub-lethal levels of Gen might impact gonococci on a transcriptional level and showed that expression of the putative HicA-HicB toxin-antitoxin (TA) system was increased in response to sub-lethal Gen. Importantly, loss of this TA system resulted in reduction of Ng biofilm formation in a strain specific manner. Focusing on this strain specificity, we found that the CpxR/CpxA two-component system (TCS) influences expression of the hicAB operon independently of HicB autoregulation. We now report that CpxR selectively binds to the hicAB operon to enhance expression of hicAB but does not interfere with binding of HicB to the promoter region. Furthermore, we show that single base pair differences in the intergenic region between hicA and hicB impact regulation by CpxR. Hence, the regulation of the HicAB TA in gonococcal strains is a highly coordinated response that can involve autoregulation by HicB and the CpxRA TCS. We propose that this dual regulatory scheme maximizes the ability of Ng to respond to Gen and hostile environmental conditions.