A synthetic system for asymmetric cell division in Escherichia coli.

We describe a synthetic genetic circuit for controlling asymmetric cell division in Escherichia coli in which a progenitor cell creates a differentiated daughter cell while retaining its original phenotype. Specifically, we engineered an inducible system that can bind and segregate plasmid DNA to a single position in the cell. Upon cell division, colocalized plasmids are kept by one and only one of the daughter cells. The other daughter cell receives no plasmid DNA and is irreversibly differentiated from its sibling. In this way, we achieved asymmetric cell division through asymmetric plasmid partitioning. We then used this system to achieve physical separation of genetically distinct cells by tying motility to differentiation. Finally, we characterized an orthogonal inducible circuit that enables the simultaneous asymmetric partitioning of two plasmid species, resulting in cells that have four distinct differentiated states. These results point the way toward the engineering of multicellular systems from prokaryotic hosts.

Tunable Dynamics in a Multistrain Transcriptional Pulse Generator.

One challenge in synthetic biology is the tuning of regulatory components within gene circuits to elicit a specific behavior. This challenge becomes more difficult in synthetic microbial consortia since each strain's circuit must function at the intracellular level and their combination must operate at the population level. Here we demonstrate that circuit dynamics can be tuned in synthetic consortia through the manipulation of strain fractions within the community. To do this, we construct a microbial consortium comprised of three strains of engineered Escherichia coli that, when cocultured, use homoserine lactone-mediated intercellular signaling to create a multistrain incoherent type-1 feedforward loop (I1-FFL). Like naturally occurring I1-FFL motifs in gene networks, this engineered microbial consortium acts as a pulse generator of gene expression. We demonstrate that the amplitude of the pulse can be easily tuned by adjusting the relative population fractions of the strains. We also develop a mathematical model for the temporal dynamics of the microbial consortium. This model allows us to identify population fractions that produced desired pulse characteristics, predictions that were confirmed for all but extreme fractions. Our work demonstrates that intercellular gene circuits can be effectively tuned simply by adjusting the starting fractions of each strain in the consortium.

A de novo matrix for macroscopic living materials from bacteria.

Engineered living materials (ELMs) embed living cells in a biopolymer matrix to create materials with tailored functions. While bottom-up assembly of macroscopic ELMs with a de novo matrix would offer the greatest control over material properties, we lack the ability to genetically encode a protein matrix that leads to collective self-organization. Here we report growth of ELMs from Caulobacter crescentus cells that display and secrete a self-interacting protein. This protein formed a de novo matrix and assembled cells into centimeter-scale ELMs. Discovery of design and assembly principles allowed us to tune the composition, mechanical properties, and catalytic function of these ELMs. This work provides genetic tools, design and assembly rules, and a platform for growing ELMs with control over both matrix and cellular structure and function.

Engineering High-Yield Biopolymer Secretion Creates an Extracellular Protein Matrix for Living Materials.

The bacterial extracellular matrix forms autonomously, giving rise to complex material properties and multicellular behaviors. Synthetic matrix analogues can replicate these functions but require exogenously added material or have limited programmability. Here, we design a two-strain bacterial system that self-synthesizes and structures a synthetic extracellular matrix of proteins. We engineered Caulobacter crescentus to secrete an extracellular matrix protein composed of an elastin-like polypeptide (ELP) hydrogel fused to supercharged SpyCatcher [SC(-)]. This biopolymer was secreted at levels of 60 mg/liter, an unprecedented level of biomaterial secretion by a native type I secretion apparatus. The ELP domain was swapped with either a cross-linkable variant of ELP or a resilin-like polypeptide, demonstrating this system is flexible. The SC(-)-ELP matrix protein bound specifically and covalently to the cell surface of a C. crescentus strain that displays a high-density array of SpyTag (ST) peptides via its engineered surface layer. Our work develops protein design guidelines for type I secretion in C. crescentus and demonstrates the autonomous secretion and assembly of programmable extracellular protein matrices, offering a path forward toward the formation of cohesive engineered living materials.IMPORTANCE Engineered living materials (ELM) aim to mimic characteristics of natural occurring systems, bringing the benefits of self-healing, synthesis, autonomous assembly, and responsiveness to traditional materials. Previous research has shown the potential of replicating the bacterial extracellular matrix (ECM) to mimic biofilms. However, these efforts require energy-intensive processing or have limited tunability. We propose a bacterially synthesized system that manipulates the protein content of the ECM, allowing for programmable interactions and autonomous material formation. To achieve this, we engineered a two-strain system to secrete a synthetic extracellular protein matrix (sEPM). This work is a step toward understanding the necessary parameters to engineering living cells to autonomously construct ELMs.

Functional and postural recovery after bilateral or unilateral total hip arthroplasty.

One-stage bilateral total hip arthroplasty (THA) implies similar complication rate and hospitalization time to unilateral THA, but no studies have evaluated the functional and postural recovery in these patients. The aim of this study was to assess short-term functional and postural recovery in patients after one-stage bilateral or unilateral THA. Forty patients undergoing bilateral (n = 20) or unilateral (n = 20) THA were assessed by Timed Up and Go (TUG), Numeric Rating Scale (NRS), Tampa Scale of Kinesiophobia (TSK) and Body Weight Distribution Symmetry Index (BWDSI) during stand-to-sit (STS). Centre of Pressure (CoP) parameters and BWDSI during standing with eyes open (EO) and closed (EC) were also assessed. Data were collected one day before surgery, at three and seven days. No between-group differences were found for TUG, NRS and TSK at any time-point, showing similar mobility, pain and fear of movement in both groups. BWDSI during STS (P = 0.001) and standing (OE P = 0.007; CE P = 0.012) revealed differences over time in favor of patients with bilateral THA, who showed better symmetry in weight distribution. Shorter CoP path length was observed during standing in patients with unilateral THA (OE P = 0.023; CE P = 0.018), who mainly used their non-affected limb to maintain balance.

Gait analysis in patients after bilateral versus unilateral total hip arthroplasty.

BACKGROUND: Gait abnormalities were reported in patients after total hip arthroplasty (THA). One-stage bilateral THA was introduced for bilateral hip pathologies, showing similar clinical and surgical outcome to unilateral procedure. However, no studies analyze the gait features after bilateral THA surgery compared to unilateral THA. RESEARCH QUESTION: Are there differences in gait characteristics between bilateral and unilateral THA patients and are there differences between these cases and asymptomatic age-matched healthy subjects? METHODS: In this prospective observational study, thirty-five patients with bilateral (n = 18) or unilateral THA (n = 17) and twenty asymptomatic age-matched volunteers were studied. Participants underwent three-dimensional gait analysisin order to detect gait spatial-temporal and kinematic (Gait Variable Score - GVS) parameters. Mobility (Timed Up and Go - TUG), fear of movement (Tampa Scale of Kinesiophobia - TSK) and pain during walking (Numeric Rating Scale - NRS) were also assessed. Patients were evaluated the day before surgery and at seven days, whereas healthy subjects underwent a single evaluation. ANOVA was used to assess differences between the three groups at each time-point and within-group differences in bilateral and unilateral groups. RESULTS: At baseline, no differences between the two groups of patients were found. As expected, their gait spatial-temporal and kinematic parameters and functional variables were impaired with respect to healthy subjects, both before and after surgery. After surgery, GVS Pelvic-TILT closer to normative values, longer stance and shorter swing phases were found in bilateral cases compared to unilateral patients. Moreover, a higher NRS score was found in bilateral patients, whereas TUG and TSK revealed no differences between the two groups of patients. SIGNIFICANCE: The current findings, focusing on short-term effectiveness of bilateral THA, could assist physiotherapists in selecting the best ambulation training and an appropriate rehabilitation approach immediately after surgery.

Computational strategies for a system-level understanding of metabolism.

Cell metabolism is the biochemical machinery that provides energy and building blocks to sustain life. Understanding its fine regulation is of pivotal relevance in several fields, from metabolic engineering applications to the treatment of metabolic disorders and cancer. Sophisticated computational approaches are needed to unravel the complexity of metabolism. To this aim, a plethora of methods have been developed, yet it is generally hard to identify which computational strategy is most suited for the investigation of a specific aspect of metabolism. This review provides an up-to-date description of the computational methods available for the analysis of metabolic pathways, discussing their main advantages and drawbacks. In particular, attention is devoted to the identification of the appropriate scale and level of accuracy in the reconstruction of metabolic networks, and to the inference of model structure and parameters, especially when dealing with a shortage of experimental measurements. The choice of the proper computational methods to derive in silico data is then addressed, including topological analyses, constraint-based modeling and simulation of the system dynamics. A description of some computational approaches to gain new biological knowledge or to formulate hypotheses is finally provided.