Proper wound healing necessitates both coagulation (the formation of a blood clot) and fibrinolysis (the dissolution of a blood clot). A thrombus resistant to clot dissolution can obstruct blood flow, leading to vascular pathologies. This study seeks to understand the mechanisms by which individual fibrin fibers, the main structural component of blood clots, are cleared from a local volume during fibrinolysis. We observed 2-D fibrin networks during lysis by plasmin, recording the clearance of each individual fiber. We found that, in addition to transverse cleavage of fibers, there were multiple other pathways by which clot dissolution occurred, including fiber bundling, buckling, and collapsing. These processes are all influenced by concentration of plasmin utilized in lysis. The network fiber density influenced the kinetics and distribution of these pathways. Individual cleavage events often resulted in large morphological changes in network structure, suggesting that the inherent tension in fibers played a role in fiber clearance. Using images before and after a cleavage event to measure fiber lengths, we estimated that fibers are strained ~23% beyond their equilibrium length during polymerization. To understand the role of fiber tension in fibrinolysis we modeled network clearance under differing amounts of fiber polymerized strain (prestrain). The comparison of experimental and model data indicated that fibrin tension enables 35% more network clearance due to network rearrangements after individual cleavage events than would occur if fibers polymerized in a non-tensed state. Our results highlight many characteristics and mechanisms of fibrin breakdown, which have implications on future fibrin studies, our understanding of the fibrinolytic process, and the development of thrombolytic therapies.

Fibrin forms the structural scaffold of blood clots and has great potential for biomaterial applications. Creating recombinant expression systems of fibrinogen, fibrin’s soluble precursor, would advance the ability to construct mutational libraries that would enable structure–function studies of fibrinogen and expand the utility of fibrin as a biomaterial. Despite these needs, recombinant fibrinogen expression systems, thus far, have relied on the time-consuming creation of stable cell lines. Here we present tests of a transient fibrinogen expression system that can rapidly generate yields of 8–12 mg/L using suspension HEK Expi293TM cells. We report results from two different plasmid systems encoding the fibrinogen cDNAs and two different transfection reagents. In addition, we describe a novel, affinity-based approach to purifying fibrinogen from complex media such as human plasma. We show that using a high-affinity peptide which mimics fibrin’s knob ‘A’ sequence enables the purification of 50–75% of fibrinogen present in plasma. Having robust expression and purification systems of fibrinogen will enable future studies of basic fibrin(ogen) biology, while paving the way for the ubiquitous use of fibrin as a biomaterial.

biochemistry is computationally predictable. Partial Order Optimum Likelihood (POOL) is a machine learning method developed by us to predict residues important for function, using the 3D structure of the query protein. The input features to POOL are based on computed electrostatic and chemical properties from THEMATICS. These input features are effectively measures of the strength of coupling between protonation events. POOL is used to predict the residues important for catalysis and ligand binding. Typical predicted catalytic sites are characterized by networks of strongly coupled protonation states; these networks impart the necessary electrostatic and proton-transfer properties to the active residues in the first layer around the reacting substrate molecule(s). Most often these networks include first-, second-, and sometimes third-layer residues. POOL-predicted, multi-layer active sites with significant participation by distal residues have been verified experimentally by single-point sitedirected mutagenesis and kinetics assays for multiple examples, including human phosphoglucose isomerase, human PARK2 (an E3 ubiquitin ligase), and E. coli ornithine transcarbamoylase. Mechanisms for the effects of diseaseassociated mutations, and implications for personalized medicine, are discussed.