We report the viscosity of semidilute solutions of a bacterially synthesized polysaccharide a partially deacetylated poly-N-acetylglucosamine as measured by micro-rheology. This polymer, commonly called polysaccharide intercellular adhesin (PIA), is synthesized by Staphylococcal strains; it is a principal component of the biofilms of these bacteria. We show that the concentration-dependent viscosity of PIA at a pH in which it is associated can be predicted using the Heo-Larson equation for entangled polymers [J. Rheol. 2005, 49 (5), 1117-1128], if the molecular parameters of the equation are measured in its associated state. This agreement is consistent with PIA adopting a concentration-dependent scaling of the viscosity that is dominated by entanglements and intermolecular associations, as described in the theory of Rubinstein and Semenov [Macromolecules 2001, 34 (4), 1058-1068]. The zero-shear specific viscosity, eta(sp), measured in the concentration range, c(PIA) = 0.1-13 wt %, scales as eta(sp) similar to c(PIA)(1.27 +/- 0.15) up to an entanglement concentration, c(e) = 3.2 wt,. %, after which lisp eta(sp) similar to c(PIA)(4.25 +/- 0.30) In the presence of urea, a known disruptor of associations, these scaling shifts to eta(sp) similar to c(PIA)(1.02 +/- 0.2) and eta(sp) similar to c(PIA)(2.57 +/- 0.6), respectively; no shift in c(e) is observed. The urea effect is consistent with an associative contribution to viscosity in the aqueous solution case. The invariance of c(e) suggests that the rheology of this polymer solvent system also includes an entanglement contribution. With independent estimates of the PIA weight-average molar mass, M-w, entanglement molecular weight, M-e, hydrodynamic radius, R-H, and excluded volume, nu, we use the Heo-Larson equation to predict eta(sp) as a function of c(PIA). With the use of parameters from the associated state particularly the hydrodynamic radius we find good agreement between the model and data for aqueous PIA solutions. This study offers a means to predict the rheology of associating polysaccharides using correlations for nonassociating polymers adjusted with minimal a priori data from their associated state.