**Background:** Poultry meat is the most consumed protein source globally, but chicken carcasses harbor pathogens such as Salmonella spp., pathogenic Escherichia coli, Campylobacter spp., Clostridium perfringens, and Listeria monocytogenes, as well as spoilage organisms like Lactobacillus, Lactococcus, Leuconostoc, and Pseudomonas. Traditional culture-based methods detect only about 0.1% of bacteria and are limited by stress factors, biofilm formation, and viable but non-culturable states. Next-generation sequencing, particularly 16S rRNA amplicon profiling, offers a more comprehensive view of microbial communities. Processing water in abattoirs provides a low-cost, non-invasive sampling matrix to monitor contamination. This study aimed to characterize the structure and diversity of the microbiome throughout the broiler slaughter process using 16S rRNA amplicon sequencing and to evaluate contamination at each processing step.
**Methods:** Processing water samples were collected from a large-scale Australian abattoir at four points: inside the scalding tub (n=3), at the inside–outside-carcass-wash (IOCW) drain (n=3), inside the chilling unit (n=3), and at evisceration drains (n=3). Additionally, feather samples (n=3) from the plucking machine and three post-chill broiler chickens (n=9) were collected. Sampling was performed once monthly in February, March, and April. Samples were chilled (5–8°C) and transported to the laboratory within 24 hours. For culture-based analysis, samples were serially diluted and incubated on selective media for Campylobacter spp. (ISO10272-2:2006), L. monocytogenes (ISO 11290-1:2010), Salmonella spp. (ISO 6579-1:2017), and E. coli (ISO 3811). For 16S rRNA amplicon sequencing, DNA was extracted using the Wizard Genomic DNA Purification Kit, and the V3-V4 hypervariable region was amplified using 341F-806R primers on the Illumina MiSeq platform. Bioinformatic analysis was performed using Dada2 (version 1.26.0) for denoising and ASV identification, with taxonomy assigned using the silva nr99 v138.1 database. Alpha diversity was assessed using Chao1, Shannon, and Simpson metrics; beta diversity was analyzed using non-metric multidimensional scaling (nMDS) based on Bray-Curtis and Jaccard dissimilarities. Heatmaps were generated using Pheatmap (1.0.12) with Spearman's rank correlation clustering.
**Key Results:** A total of 11,042 ASVs were identified. From these, 7,910 ASVs (7,855 bacteria and 55 archaea/parasites) were present in the post-chill carcass rinsate. The dominant phyla on post-chill carcasses were Firmicutes (60.02%), Proteobacteria (22.68%), Bacteroidota (11.16%), Actinobacteriota (1.38%), and Desulfobacterota (1.20%). The relative abundance of Firmicutes decreased during defeathering (47.89% decrease) and evisceration (24.66% decrease), increased during carcass wash (31.74% increase), decreased during chilling (8.27% decrease), and increased on post-chill carcasses (32.60% increase). The most abundant genera on post-chill carcasses were Anoxybacillus (38.84%), Megamonas (5.57%), Lactobacillus (3.89%), Unclassified Lachnospiraceae (2.57%), and Tepidimicrobium (1.75%) within Firmicutes; Dechloromonas (5.54%), Unclassified Enterobacteriaceae (2.90%), Yersinia (2.74%), Gallibacterium (2.51%), and Acinetobacter (1.20%) within Proteobacteria; and Unclassified Prevotellaceae (1.53%), Bacteroides (1.04%), and Williamwhitmania (0.68%) within Bacteroidota. Salmonella and Listeria were not detected by either culture or sequencing. Campylobacter was abundant in processing water samples, including chillers, suggesting non-culturable forms. Culture-based results showed the highest E. coli and Campylobacter counts in carcass washer and evisceration drain water, with the lowest counts in post-chill carcass rinsate. Alpha diversity analysis revealed a significant effect of sampling point on the Shannon index (one-factor ANOVA p < 0.001; Kruskal-Wallis chi-squared = 11.867, p = 0.037), while sampling month had no significant impact (p = 0.937; Kruskal-Wallis chi-squared = 0.348, p = 0.840). Beta diversity analysis using PERMANOVA on Bray-Curtis dissimilarities showed significant differences between processing points (p = 0.010) but not between months (p = 0.410), confirmed by Jaccard's model (processing point p = 0.001; month p = 0.344). Spearman's correlation indicated that the microbial communities at defeathering and chilling had the highest association with those in the post-chill carcass rinsate.
**Clinical Implications:** This study demonstrates that 16S rRNA amplicon sequencing of processing water provides a comprehensive food safety surveillance tool capable of detecting non-culturable and injured bacteria throughout the slaughter process. The microbial community present during defeathering may serve as an indicator of eventual carcass contamination and shelf life. Chilling waters represent a critical point for assessing cross-contamination and redistribution of microorganisms during immersion chilling. The steady increase in bacterial diversity from scalding through chilling identifies these steps as hotspots for contamination. The persistence of Firmicutes (particularly Anoxybacillus) and the survival of Gram-negative Proteobacteria and Bacteroidota through processing underscores the need for targeted interventions at defeathering and chilling to reduce contamination and improve poultry meat safety.