Abstract
A computational method has been developed to distinguish the Klebsiella species serotypes to aid in outbreak surveillance. A reliability score (estimated based on the accuracy of a specific K-type prediction against the dataset of 141 distinct K-types) average (ARS) that reflects the specificity between the Klebsiella species capsular polysaccharide biosynthesis and surface expression proteins, and their K-types has been established. ARS indicates the following order of potency in accurate serotyping: Wzx (ARS = 98.5%),Wzy (ARS = 97.5%),WbaP (ARS = 97.2%),Wzc (ARS = 96.4%),Wzb (ARS = 94.3%),WcaJ (ARS = 93.8%),Wza (ARS = 79.9%) and Wzi (ARS = 37.1%). Thus, Wzx, Wzy and WbaP can give more reliable K-typing compared with other proteins. A fragment-based approach has further increased the Wzi ARS from 37.1% to 80.8%. The efficacy of these 8 proteins in accurate K-typing has been confirmed by a rigorous testing and the method has been automated as K-PAM ( www.iith.ac.in/K-PAM/ ). Testing also indicates that the use of multiple genes/proteins helps in reducing the K-type multiplicity, distinguishing the K-types that have identical K-locus (like KN3 and K35) and identifying the ancestral serotypes of Klebsiella spp. K-PAM has the facilities to O-type using Wzm (ARS = 85.7%) and Wzt (ARS = 85.7%) and identifies the hypervirulent Klebsiella species by the use of rmpA, rmpA2, iucA, iroB and peg-344 marker genes. Yet another highlight of the server is the repository of the modeled 11 O- and 79 K- antigen 3D structures.