Study finds Listeria changes sped up analysis process

Researchers have described how the rollout of Listeria sequencing to states in Australia led to an overall decline in turnaround times.

A study published in Emerging Infectious Diseases saw scientists assess turnaround times in the national Listeria monocytogenes genomic surveillance system before and after decentralized sequencing. They found a reduction in median time from sample collection to the issuing of a national genomic surveillance report from 32 to 26 days, despite sample numbers doubling in 2022 and 2023. 

In Australia, invasive listeriosis is recorded in the National Notifiable Diseases Surveillance System (NNDSS). Public health monitoring is managed by OzFoodNet, the national foodborne disease surveillance network.

In 2010, the National Enhanced Listeriosis Surveillance System (NELSS) was established to collate epidemiological data from cases and molecular lab data from isolates. The National Listeria Reference Laboratory (NLRL), based at the Microbiological Diagnostic Unit Public Health Laboratory (MDU PHL) in Victoria, was then tasked with providing national molecular characterization of all referred Listeria monocytogenes samples. In July 2015, the NLRL started routine whole genome sequencing (WGS) for all referred samples and, after a 12-month trial, it became the preferred typing method.

Australia’s eight jurisdictions lead their own public health activities, including pathogen genomics. MDU PHL continued WGS for Victoria. Queensland, New South Wales, South Australia, and Western Australia became responsible for Listeria monocytogenes WGS during 2018 to 2023. The Northern Territory, Australian Capital Territory, and Tasmania still refer samples to the NLRL.

Samples from listeriosis notifications and relevant positive food and environmental samples are forwarded to public health laboratories (PHLs) in each state for confirmation, and PHLs then refer sequences or isolates to the NLRL for genomic analysis.

Initial increase in turnaround times

The study included all Listeria monocytogenes samples referred to the NLRL for sequencing and Listeria monocytogenes sequences referred by PHLs during 2016 to 2023. Timeliness of the genomic surveillance system was assessed by using data including when a sample was collected, the date it was sequenced, and the date the NLRL issued a genomics report.

During 2016 to 2023, Australia had 545 listeriosis cases, and yearly infections ranged from 43 to 89. Researchers included 543 sequences from 508 cases in the study. They also included 418 sequences of Listeria cultured from food and 243 from environmental samples. The timeliness analysis included 1,165 samples. Samples from New South Wales and Victoria made up 65 percent of the dataset.

Scientists found a pattern of pre–COVID–19 pandemic improvements but a statistically significant increase in turnaround times in 2020 and 2021 compared with previous years, before time reductions in 2022 and 2023. Timeliness of genomic data availability went from a median of 32 days in 2016 to 26 days in 2023. The overall median end-to-end processing time was lower in 2022 and 2023 despite an increase in samples.

For the previous analysis method, the median time from notification to data availability to NELSS during 2010 to 2013 was 50 days.

Victoria maintained median turnaround times of 24 to 27 days. New South Wales had larger variations in times of 24 to 42 days, and higher upper limits of 60 to 70 days. Queensland, South Australia, and Western Australia showed increased turnaround times immediately after transitioning to referring sequence data instead of isolates.

Findings show that there can be delays in data availability during the establishment of decentralized sequencing processes, but disruptions can be resolved as the capacity matures.

Delays were mainly observed in the referral of sequences to the NLRL. Researchers said this could be because transitions coincided with the COVID-19 pandemic or because of variability in the software and processes for referrals.

“We believe the reductions we report are associated with use and increased capacity of automated robotics workflows for WGS; accelerated establishment of strong WGS capacity during the COVID-19 pandemic; replacement of a physical sample transport step, and potential batching of samples for courier transport, with electronic data transfer,” said scientists.

Although WGS has improved the ability to detect and characterize outbreaks, its effectiveness in reducing case numbers depends on public health actions, effective control of persistent contamination sources, and improvements in food safety protocols and compliance.

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Source: https://www.foodsafetynews.com/2025/05/study-finds-listeria-changes-sped-up-analysis-process/