A 16S rRNA gene-based analysis of microbial communities in compost-bedded pack barns from dairy farms in Argentina

13 Microbial communities play a central role in compost -bedded pack (CBP) systems by driving 14 organic matter decomposition and nutrient cycling. The objective of this study was to characterize 15 and compare the bacterial community structure of CBP from two dairy farms in Córdoba, 16 Argentina, using 16S rRNA gene sequencing. Two CBP systems were evaluated: Martin Bono 17 (MB; 30 months in operation) and Angela Teresa (AT; 20 months). The MB system was 18 established on natural soil without bedding addition and included concrete feed alleys, whereas 19 AT was initiated with peanut shell bedding and lacked concrete alleys. In both systems, compost 20 was tilled twice daily. Two samples per farm were collected at a depth of 30 cm during winter 21 2019. Raw Illumina reads were processed using the DADA2 pipeline, including quality filtering, 22 error modeling, denoising, and chimera removal. A total of four samples yielded 2,503 amplicon 23 sequence variants (ASVs), with approximately 76% of reads retained after filtering and chimera 24 removal, indicating high -quality sequencing data. Taxonomic analysis revealed that bacterial 25 communities in both systems were dominated by phyla typically associated with compost 26 environments, including Actinobacteriota, Proteobacteria, and Firmicutes. Differences in relative 27 abundance between systems suggested shifts in community composition associated with 28 management conditions. 29 30 Key words: compost-bedded pack barns, 16S rRNA, microbiome, nitrifying bacteria, dairy 31 systems 32 33 34 35 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.04.716490doi: bioRxiv preprint

36 Compost-bedded pack (CBP) systems are increasingly adopted in dairy production due to 37 their benefits in animal welfare, cow comfort, and manure management efficiency (Biasato et al., 38 2019; Black et al., 2013). In these systems, microbial communities play a central role in organic 39 matter decomposition, heat generation, and nutrient cycling, driving the biological processes that 40 sustain compost functionality (Insam and de Bertoldi, 2007 ; Sánchez-Monedero et al., 2001 ). 41 Nitrogen transformations mediated by microorganisms are critical for maintaining compost 42 quality and environmental sustainability, as they regulate ammonia volatilization, nitrate 43 formation, and overall nitrogen balance (Kumar et al., 2025). 44 The structure and function of microbial communities in CBP systems are strongly influenced 45 by management factors such as bedding material, aeration, moisture content, stocking density, 46 and system age (Black et al., 2013 ; Endres and Barberg, 2007 ). These variables shape 47 physicochemical conditions within the pack, thereby affecting microbial activity, diversity, and 48 metabolic pathways. Among microbial functional groups, nitrifying bacteria are of particular 49 interest, as they mediate the oxidation of ammonia to nitrite and nitrate, playing a key role in 50 nitrogen cycling and influencing nitrogen losses through volatilization and leaching (Kowalchuk 51 and Stephen, 2001; Prosser et al., 2007). 52 Previous studies have reported the presence of highly diverse microbial communities in 53 composting environments, including taxa associated with organic matter degradation and nutrient 54 transformations (Kumar et al., 2025 ; Palaniveloo et al., 2020 ). However, limited information is 55 available on how CBP management practices specifically influence the abundance and diversity 56 of nitrifying bacteria in dairy production systems. This represents an important knowledge gap, 57 given the relevance of nitrogen cycling for both compost efficiency and environmental impact. 58 Advances in high-throughput sequencing technologies, particularly 16S rRNA gene amplicon 59 sequencing, have enabled detailed characterization of microbial communities and their potential 60 functional roles in complex environments such as compost -bedded packs (Callahan et al., 2016; 61 Knight et al., 2018 ). These approaches allow for the identification of key microbial taxa and 62 provide insights into how management practices shape microbiome composition. 63 The objective of this study was to characterize and compare the bacterial community structure 64 of CBP systems from two dairy farms in Córdoba, Argentina, with particular emphasis on 65 nitrifying bacteria, using 16S rRNA gene sequencing. 66

67 Study sites and sampling 68 Two compost -bedded pack (CBP) dairy systems located in Córdoba, Argentina, were 69 evaluated: Martin Bono (MB; 30 months in operation) and Angela Teresa (AT; 20 months). The 70 MB system was established on natural soil without bedding addition and included concrete feed 71 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.04.716490doi: bioRxiv preprint alleys, whereas AT was initiated with peanut shell bedding and lacked concrete alleys. In both 72 systems, compost was tilled twice daily. 73 Sampling was conducted during winter (July 2019). Two samples were collected from each 74 CBP system at a depth of approximately 30 cm, resulting in a total of four samples (AT1, AT2, 75 MB1, and MB2). 76 DNA extraction and sequencing 77 Soil samples were first lyophilized to facilitate handling and homogenization due to their 78 sticky consistency. Subsequently, dried samples were homogenized in a high-speed mixer (High-79 speed Universal Disintegrator, Pro-Lab Diagnosis) and DNA extraction was performed using the 80 microbiome DNA purification kit PureLink™ (ThermoFisher) and subjected to 16S rRNA gene 81 amplicon sequencing using Illumina technology (INDEAR, Argentina) , following standard 82 protocols for microbiome characterization (Caporaso et al., 2012). Paired-end reads were obtained 83 and merged prior to downstream analysis. 84 Bioinformatic processing 85 Raw sequence data were initially processed in Geneious Prime (version 2025.1.3), where 86 trimming and quality filtering were performed to remove low -quality reads and adapter 87 sequences. Subsequently, the filtered reads were analyzed using the DADA2 pipeline in R 88 (Callahan et al., 2016 ). This included error rate learning, sequence denoising, and inference of 89 amplicon sequence variants (ASVs). Chimeric sequences were identified and removed using a 90 consensus-based approach. 91 After processing, a total of 2,503 amplicon sequence variants ( ASVs) were obtained across 92 four samples, with approximately 76% of reads retained after filtering and chimera removal. 93 Taxonomic classification of ASVs was performed using the SILVA reference database (v138.1) 94 (Quast et al., 2013), assigning taxonomy across multiple levels, including phylum and genus. 95 Statistical and ecological analysis 96 Microbial community analyses were conducted using the (McMurdie and Holmes, 2013 ) . 97 Relative abundance of taxa was calculated and visualized at the phylum level. Alpha diversity 98 was assessed using the Shannon index (Shannon, 1948). Beta diversity was evaluated using Bray–99 Curtis dissimilarity (Bray and Curtis, 1957), and principal coordinate analysis (PCoA) was used 100 to visualize differences in community structure between systems. 101 Nitrifying bacteria were identified based on taxonomic assignment at the genus level, 102 focusing on Nitrosomonas, Nitrosococcus, and Nitrobacter. Differences in abundance and 103 diversity between systems were evaluated descriptively due to the limited number of replicates. 104 Additionally, genera associated with mastitis -related pathogens, including Staphylococcus, 105 Streptococcus, Corynebacterium, and Escherichia, were specifically examined to assess potential 106 sanitary risks. 107

108 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.04.716490doi: bioRxiv preprint Microbial diversity and community structure 109 Alpha diversity, estimated using the Shannon index, showed slightly higher values in MB 110 compared to AT samples (Figure 1). However, these differences were not statistically significant 111 (Wilcoxon test, p = 0.33), likely due to the limited number of replicates. Despite this, MB samples 112 consistently exhibited higher diversity values, suggesting a trend toward increased microbial 113 complexity. 114 115 Figure 1. Shannon diversity index of bacterial communities in compost -bedded pack systems 116 (AT and MB). Boxplots represent alpha diversity values for each system. No significant 117 differences were observed between groups (Wilcoxon test, p = 0.33). 118 Beta diversity analysis based on Bray –Curtis dissimilarity revealed a clear separation 119 between AT and MB samples (Figure 2) , indicating distinct microbial community structures 120 between systems. Replicates clustered according to treatment, supporting the reproducibility of 121 the observed patterns. 122 123 Figure 2. Principal coordinate analysis (PCoA) based on Bray –Curtis dissimilarity showing 124 differences in bacterial community structure between compost -bedded pack systems (AT and 125 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.04.716490doi: bioRxiv preprint MB). Each point represents one sample, and colors indicate system type. The first principal 126 coordinate explains 78.5% of the variation. 127 Mastitis-associated genera 128 Genera associated with mastitis -related pathogens were detected in both systems, including 129 Corynebacterium, Pseudomonas, and Staphylococcus (Figure 3). 130 AT samples were dominated by Corynebacterium, with only minor contributions from other 131 genera. In contrast, MB samples showed a more balanced composition, with increased relative 132 abundance of Pseudomonas and detectable levels of Staphylococcus. These results suggest 133 differences in the potential sanitary profile between systems. 134 135 Figure 3. Relative abundance of mastitis -associated genera ( Corynebacterium, Pseudomonas, 136 Staphylococcus) in AT and MB samples. 137 Nitrifying bacteria 138 Nitrifying bacteria were detected at the genus level, including Nitrosomonas and 139 Nitrosococcus (Figure 4) . These taxa were present in both systems, although their relative 140 abundance appeared higher and more consistent in MB samples, suggesting enhanced nitrogen 141 cycling potential in this system. 142 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.04.716490doi: bioRxiv preprint 143 Figure 4. Relative abundance of nitrifying bacteria ( Nitrosomonas and Nitrosococcus) across 144 samples from both CBP systems. 145 Functional microbial groups 146 Analysis of key functional genera associated with compost processes revealed marked 147 differences between systems (Figure 5). AT samples were largely dominated by Pseudomonas, 148 indicating a simpler functional structure. In contrast, MB samples displayed a broader functional 149 diversity, including the presence of Mycobacterium and Streptomyces, in addition to nitrifying 150 bacteria such as Nitrosomonas. 151 The exclusive detection of Mycobacterium in MB samples further highlights differences in 152 environmental conditions and microbial niches between systems. Overall, these findings suggest 153 a more complex and functionally diverse microbial community in MB. 154 155 156 Figure 5. Relative abundance of selected functional genera associated with compost processes 157 (Mycobacterium, Nitrosomonas, Pseudomonas, Streptomyces) in AT and MB systems. 158 Community abundance patterns 159 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.04.716490doi: bioRxiv preprint Heatmap analysis of the most abundant genera revealed distinct community patterns between 160 systems (Figure 6). AT samples exhibited a more homogeneous microbial profile, with higher 161 relative abundance of Corynebacterium, whereas MB samples showed a more heterogeneous 162 distribution of taxa, including increased representation of several genera associated with compost 163 processes. These patterns further support differences in microbial structure between CBP systems. 164 165 Figure 6. Heatmap showing the relative abundance of the most abundant bacterial genera across 166 samples. Color intensity represents relative abundance, highlighting differences in microbial 167 composition and heterogeneity between AT and MB systems. 168

169 The present study provides a first 16S rRNA gene -based characterization of microbial 170 communities in compost -bedded pack (CBP) barns from dairy farms in Córdoba, Argentina. 171 Although based on a limited number of samples, the results show that bacterial community 172 composition differed clearly between the two evaluated systems, suggesting that management 173 conditions, bedding characteristics, and system configuration can strongly influence microbial 174 structure in CBP environments. 175 Both systems were dominated by phyla commonly associated with composting and organic 176 matter degradation, including Actinobacteriota, Proteobacteria, and Firmicutes. This is consistent 177 with the biological function of CBP systems, where microbial activity supports decomposition, 178 heat generation, and nutrient turnover (Insam and de Bertoldi, 2007 ; Tiquia et al., 2002 ). The 179 separation observed in the Bray –Curtis PCoA indicates that, despite the shared productive 180 context, each barn harbored a distinct bacterial assemblage. The close clustering of replicates 181 within each farm further supports the consistency of the microbial profiles detected. 182 The MB system showed a tendency toward higher alpha diversity and a broader distribution 183 of taxa compared with AT. This pattern may reflect the combined influence of longer operational 184 time, absence of initial bedding addition, and the presence of concrete feed alleys, all of which 185 may affect moisture gradients, organic matter inputs, and aeration dynamics (Endres and Barberg, 186 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.04.716490doi: bioRxiv preprint 2007; Endres and Janni, 2008 ). In compost -based systems, greater microbial diversity is often 187 associated with increased functional redundancy and process stability, which may be 188 advantageous for maintaining compost performance under variable environmental conditions 189 (Allison and Martiny, 2008; Shade et al., 2012). However, because of the small sample size, these 190 differences should be interpreted cautiously. 191 Particular attention was given to nitrifying bacteria because of their relevance to nitrogen 192 transformations in compost systems. Genera such as Nitrosomonas and Nitrosococcus were 193 detected in both farms, but their abundance appeared greater and more consistent in MB. This 194 suggests that microbial processes linked to ammonia oxidation may be favored under the 195 environmental and management conditions present in that system. Since nitrogen cycling is a 196 central component of compost quality and environmental performance, these differences may 197 have practical implications for ammonia retention, nitrate formation, and overall nutrient 198 dynamics in CBP barns (Kowalchuk and Stephen, 2001 ; Sánchez-Monedero et al., 2001 ). 199 Nonetheless, functional activity was inferred only from taxonomic composition, and future 200 studies should incorporate direct measurements of nitrogen transformation rates or functional 201 genes involved in nitrification. 202 The detection of genera associated with mastitis -related pathogens, including 203 Staphylococcus, Streptococcus, Corynebacterium, and Escherichia, also highlights the sanitary 204 relevance of microbial monitoring in these systems. Although 16S rRNA sequencing does not 205 allow confirmation of pathogenic strains or viability, the presence and relative abundance of these 206 genera suggest that CBP management may influence microbial groups with potential relevance 207 to udder health (Bradley, 2002; Smith et al., 1985). Differences between systems may therefore 208 reflect not only composting performance but also distinct sanitary profiles linked to bedding 209 composition, moisture, and aeration 210 This study has some limitations that should be acknowledged. The analysis was based on 211 only four samples collected at a single time point during winter, which limits statistical power 212 and prevents evaluation of seasonal dynamics. In addition, taxonomic inference from 16S rRNA 213 amplicons provides limited functional resolution (Janda and Abbott, 2007; Knight et al., 2018 ). 214 Even so, the results offer a useful initial description of microbial community patterns in Argentine 215 CBP systems and identify management -associated differences that merit deeper investigation. 216 Future work should include a larger number of farms, repeated sampling over time, and 217 integration of physicochemical variables such as temperature, moisture, pH, and nitrogen forms 218 to better explain microbial shifts and their functional consequences. 219 In conclusion, the bacterial communities of the two CBP systems differed in both composition 220 and inferred functional potential. The MB system showed higher diversity and a greater 221 representation of nitrifying bacteria, suggesting that barn design and management history may 222 shape key microbial processes in compost-bedded pack environments. These findings contribute 223 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.04.716490doi: bioRxiv preprint to a better understanding of microbiological dynamics in dairy CBP systems and may support 224 future improvements in compost management, nutrient cycling, and animal health. 225 226 227 228 229 230 231 232 233 234 235 236 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.04.716490doi: bioRxiv preprint Author contributions 237 Conceptualization, L.P., methodology, J.M., C.P. and L.P.; formal analysis, J.M., C.P. and L.P.; 238 investigation, J.M.; C.P. and L.P.; resources, J.M. and L.P.; data curation, L.P.; writing—original 239 draft preparation, L.P.; writing, review and editing, L.P.; visualization, L.P.; supervision, J.M. and 240 L.P.; project administration, J.M. and L.P.; funding acquisition, J.M. and L.P. All authors have 241 read and agreed to the published version of the manuscript. 242 Conflicts of interest 243 The authors declare there are no conflicts of interest 244 Acknowledgments 245 Leopoldo Palma gratefully acknowledges the Spanish Ministry of Science, Innovation, and 246 Universities, the Spanish State Research Agency, and the European Union for funding his Ramón 247 y Cajal contract (grant ref. RYC2023-043507-I). 248 Data availability 249 The raw sequencing reads have been deposited in the NCBI Sequence Read Archive (SRA) under 250 BioProject accession PRJNA1449009, with associated BioSample accession numbers XXX. 251 252 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted April 4, 2026. ; https://doi.org/10.64898/2026.04.04.716490doi: bioRxiv preprint

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