Streptococcus pneumoniae is responsible for 240 000–460 000 deaths in children under 5 years of age each year. Accurate identification of pneumococcal serotypes is important for tracking the distribution and evolution of serotypes following the introduction of effective vaccines. Recent efforts have been made to infer serotypes directly from genomic data but current software approaches are limited and do not scale well. Here, we introduce a novel method, SeroBA, which uses a k-mer approach. We compare SeroBA against real and simulated data and present results on the concordance and computational performance against a validation dataset, the robustness and scalability when analysing a large dataset, and the impact of varying the depth of coverage on sequence-based serotyping. SeroBA can predict serotypes, by identifying the cps locus, directly from raw whole genome sequencing read data with 98 % concordance using a k-mer-based method, can process 10 000 samples in just over 1 day using a standard server and can call serotypes at a coverage as low as 15–21×. SeroBA is implemented in Python3 and is freely available under an open source GPLv3 licence from: https://github.com/sanger-pathogens/seroba

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In rhinoceroses, lameness is an occasionally seen symptom primarily caused by lesions affecting the feet and interdigital space. A 3-year-old male Greater one-horned rhinoceros developed a progressive, severe movement disorder of the right hind limb with subsequent death. The pathological analysis diagnosed a severe, retroperitoneal abscess and chronic thrombosis of the right iliac artery. Streptococci detected in the abscess were further identified as Streptococcus dysgalactiae subspecies equisimilis by culture and molecular techniques. The identical isolate was also identified in a vaginal swab of the dam. The list of differential diagnoses for lameness in rhinoceroses must be expanded by processes affecting other than the extremities per se.