Genomic Surveillance of Listeria monocytogenes in Argentina: Analysis of Cases and Isolates, 2023-2024

In vulnerable individuals, Listeria monocytogenes can cause invasive listeriosis, a severe foodborne infection with 20-30% mortality. Case notification to the National Health Surveillance System (SNVS) combined with whole-genome sequencing (WGS) enhances surveillance and source identification. This study evaluated listeriosis cases and the genomic relationships of isolates in Argentina identified from 2023 to 2024.

All twenty-five consecutive cases of listeriosis, a nationally notifiable disease, along with their corresponding isolates referred to the National Reference Laboratory between 2023 and 2024, were analyzed. The patients' demographic data, medical history, and outcomes were obtained from the SNVS. The sequence types (STs), clonal complexes (CCs), and relationships between the isolates were determined through WGS using the Nextera XT DNA library preparation kit and the Illumina MiSeq Platform.

Women comprised 60% of the cases and men comprisedd 40%. The patient's medical history was documented in 56% of cases, including whether they were pregnant (n=9), non-HIV-immunocompromised (n=4), or transplant recipients (n=1). Fetal loss occurred in 33.3% of pregnancies. The isolation sites included the blood (n=13), cerebrospinal fluid (n=6), and placenta (n=6). The outcomes were unknown in 60% of cases, while patients were cured/improved in 24% and died in 16%. Four genomic clusters were identified: three associated with hypervirulent CC1 (ST1) and one with CC59 (ST59). Two clusters, CC1 (n=5) and CC59 (n=3), were identified in three provinces. No food sources were identified.

The low amount of documented outcomes (40%) and missing medical history (44%) highlight the need for strengthened SNVS notification to better understand the disease burden and identify key populations at risk. Genomic clusters were detected without food source identification. Incorporating food surveys and systematic isolate referral will improve our consumption pattern knowledge and allow for epidemiological investigations for source identification.