Emergent digital bio-computation through spatial diffusion and engineered bacteria.

Biological computing is a promising field with potential applications in biosafety, environmental monitoring, and personalized medicine. Here we present work on the design of bacterial computers using spatial patterning to process information in the form of diffusible morphogen-like signals. We demonstrate, mathematically and experimentally, that single, modular, colonies can perform simple digital logic, and that complex functions can be built by combining multiple colonies, removing the need for further genetic engineering. We extend our experimental system to incorporate sender colonies as morphogen sources, demonstrating how one might integrate different biochemical inputs. Our approach will open up ways to perform biological computation, with applications in bioengineering, biomaterials and biosensing. Ultimately, these computational bacterial communities will help us explore information processing in natural biological systems.

Circulating microbiome in patients with portal hypertension.

Portal hypertension (PH) in liver cirrhosis leads to increased gut permeability and the translocation of bacteria across the gut-liver axis. Microbial DNA has recently been detected in different blood compartments; however, this phenomenon has not been thoroughly analyzed in PH. This study aimed to explore circulating bacterial DNA signatures, inflammatory cytokines, and gut permeability markers in different blood compartments (peripheral and hepatic veins) of patients with cirrhosis and PH. The 16S rRNA blood microbiome profiles were determined in 58 patients with liver cirrhosis and 46 control patients. Taxonomic differences were analyzed in relation to PH, liver function, inflammatory cytokines, and gut permeability markers. Circulating plasma microbiome profiles in patients with cirrhosis were distinct from those of the controls and were characterized by enrichment of Comamonas, Cnuella, Dialister, Escherichia/Shigella, and Prevotella and the depletion of Bradyrhizobium, Curvibacter, Diaphorobacter, Pseudarcicella, and Pseudomonas. Comparison of peripheral and hepatic vein blood compartments of patients with cirrhosis did not reveal differentially abundant taxa. Enrichment of the genera Bacteroides, Escherichia/Shigella, and Prevotella was associated with severe PH (SPH) in both blood compartments; however, circulating microbiome profiles could not predict PH severity. Escherichia/Shigella and Prevotella abundance was correlated with IL-8 levels in the hepatic vein. In conclusion, we demonstrated a distinct circulating blood microbiome profile in patients with cirrhosis, showing that specific bacterial genera in blood are marginally associated with SPH, Model for End-Stage Liver Disease score, and inflammation biomarkers; however, circulating microbial composition failed to predict PH severity.

Baseline Interleukin-6 and -8 predict response and survival in patients with advanced hepatocellular carcinoma treated with sorafenib monotherapy: an exploratory post hoc analysis of the SORAMIC trial.

PURPOSE: To explore the potential correlation between baseline interleukin (IL) values and overall survival or objective response in patients with hepatocellular carcinoma (HCC) receiving sorafenib. METHODS: A subset of patients with HCC undergoing sorafenib monotherapy within a prospective multicenter phase II trial (SORAMIC, sorafenib treatment alone vs. combined with Y90 radioembolization) underwent baseline IL-6 and IL-8 assessment before treatment initiation. In this exploratory post hoc analysis, the best cut-off points for baseline IL-6 and IL-8 values predicting overall survival (OS) were evaluated, as well as correlation with the objective response. RESULTS: Forty-seven patients (43 male) with a median OS of 13.8 months were analyzed. Cut-off values of 8.58 and 57.9 pg/mL most effectively predicted overall survival for IL-6 and IL-8, respectively. Patients with high IL-6 (HR, 4.1 [1.9-8.9], p < 0.001) and IL-8 (HR, 2.4 [1.2-4.7], p = 0.009) had significantly shorter overall survival than patients with low IL values. Multivariate analysis confirmed IL-6 (HR, 2.99 [1.22-7.3], p = 0.017) and IL-8 (HR, 2.19 [1.02-4.7], p = 0.044) as independent predictors of OS. Baseline IL-6 and IL-8 with respective cut-off values predicted objective response rates according to mRECIST in a subset of 42 patients with follow-up imaging available (IL-6, 46.6% vs. 19.2%, p = 0.007; IL-8, 50.0% vs. 17.4%, p = 0.011). CONCLUSION: IL-6 and IL-8 baseline values predicted outcomes of sorafenib-treated patients in this well-characterized prospective cohort of the SORAMIC trial. We suggest that the respective cut-off values might serve for validation in larger cohorts, potentially offering guidance for improved patient selection.