Molecular epidemiology of the pertussis epidemic in Washington State in 2012

Abstract

Although pertussis disease is vaccine preventable, Washington State experienced a substantial rise in pertussis incidence beginning in 2011. By June 2012, the reported cases reached 2,520 (37.5 cases per 100,000 residents), a 1,300% increase compared with the same period in 2011. We assessed the molecular epidemiology of this statewide epidemic using 240 isolates collected from case patients reported from 19 of 39 Washington counties during 2012 to 2013. The typing methods included pulsed-field gel electrophoresis (PFGE), multilocus variable number tandem repeat analysis (MLVA), multilocus sequence typing (MLST), and pertactin gene (prn) mutational analysis. Using the scheme PFGE-MLVA-MLST-prn mutations-Prn deficiency, the 240 isolates comprised 65 distinct typing profiles. Thirty-one PFGE types were found, with the most common types, CDC013 (n = 51), CDC237 (n = 44), and CDC002 (n = 42), accounting for 57% of them. Eleven MLVA types were observed, mainly comprising type 27 (n = 183, 76%). Seven MLST types were identified, with the majority of the isolates typing as prn2-ptxP3-ptxA1-fim3-1 (n = 157, 65%). Four different prn mutations accounted for the 76% of isolates exhibiting pertactin deficiency. PFGE provided the highest discriminatory power (D = 0.87) and was found to be a more powerful typing method than MLVA and MLST combined (D = 0.67). This study provides evidence for the continued predominance of MLVA 27 and prn2-ptxP3-ptxA1 alleles, along with the reemergence of the fim3-1 allele. Our results indicate that the Bordetella pertussis population causing this epidemic was diverse, with a few molecular types predominating. The PFGE, MLVA, and MLST profiles were consistent with the predominate types circulating in the United States and other countries. For prn, several mutations were present in multiple molecular types.

FIG 1

Map of the geographic distribution of cases with and without isolates collected in 2012. Cases were mapped by ZIP Code of residence. Squares represent the locations of case patients with isolates for whom the ZIP Codes and PFGE profiles are known (n = 233), with the color corresponding to the PFGE profile of the isolate. Gray circles represent the locations of cases without isolates but with the ZIP Code known (n = 4,681). The symbols are placed only within the ZIP Code and do not correspond to the actual location of each case patient's residence.

FIG 2

Minimum spanning tree based on PFGE. A binary coefficient was used for clustering. Each circle in the tree represents a different PFGE type, and the type number is indicated within or near the circle. The size of the circle indicates the number of isolates with the particular PFGE type. The lines connecting the circles represent the number of band differences between connecting PFGE types. Heavy solid lines connecting two PFGE types denote types differing by a single band, thin solid lines connect types that differ by two bands, and dotted lines indicate types differing by three or more bands. Each color represents a different MLVA-MLST (prn-ptxP-ptxA-fim3)-prn genotype profile, as indicated in the key. Shadows around circles indicate PFGE types that are closely related based on banding patterns.

FIG 3

Minimum spanning tree based on MLVA. A categorical coefficient was used for clustering. Each circle in the tree represents a different MLVA type, and the type number is indicated within the circle. The size of the circle indicates the number of isolates with the particular MLVA type. Solid lines connecting circles represent 1 VNTR difference between connecting MLVA types, while dotted lines represent 2 VNTR differences. Each color represents a different MLST type, as indicated in the key.