Skarlupka, J. H. | Search bioRxiv

bioRxiv2025

Patterns of Microbial Succession and Niche Differentiation Across Depth and Age in a Landfill Have Implications for Management Strategies

Despite microorganisms being primarily responsible for landfill material decomposition, limited characterization has been performed across both landfill depth and age. Here, we investigated the microbial communities and physicochemical parameters in two active and two closed landfill wells from surface to bottom, as well as fill dirt and leachate at a sanitary landfill near Madison, Wisconsin, USA. Amplicon community sequencing fungi, bacteria and archaea revealed distinct microbial community structures across landfill sites. The observed patterns of microbial community succession by depth and age mirror the known phases of the landfill life cycle. Younger surface samples were dominated by aerobic fungi, which transitioned to fermentative bacteria and methanogenic archaea in older, deeper, layers. Simultaneously, high species richness was preserved across landfill ages, while reduced evenness at specific depths support spatial niche differentiation. In conjunction with the lack of trends found for physicochemical parameters by depth, this supports niche differentiation driven by the highly heterogenous waste inputs. This study provides the first comprehensive vertical profile of bacterial, fungal, and archaeal communities across landfill depths and ages, highlighting the influence of these parameters on physicochemical factors and microbial distribution within landfills. These results have implications for improving landfill management, including renewable gas energy production, minimizing emissions, and increasing degradation rates.

microbiology↗

bioRxiv2020

Validating the use of bovine buccal sampling as a proxy for the rumen microbiota using a time course and random forest classification approach

Analysis of the cow microbiome, as well as host genetic influences on the establishment and colonization of the rumen microbiota, is critical for development of strategies to manipulate ruminal function toward more efficient and environmentally friendly milk production. To this end, the development and validation of noninvasive methods to sample the rumen microbiota at a large-scale is required. Here, we further optimized the analysis of buccal swab samples as a proxy for direct microbial samples of the rumen of dairy cows. To identify an optimal time for sampling, we collected buccal swab and rumen samples at six different time points relative to animal feeding. We then evaluated several biases in these samples using a machine learning classifier (random forest) to select taxa that discriminate between buccal swab and rumen samples. Differences in the Simpsons diversity, Shannons evenness and Bray-Curtis dissimilarities between methods were significantly less apparent when sampling was performed prior to morning feeding (P<0.05), suggesting that this time point was optimal for representative sampling. In addition, the random forest classifier was able to accurately identify non-rumen taxa, including 10 oral and feed-associated taxa. Two highly prevalent (> 60%) taxa in buccal and rumen samples had significant variance in absolute abundance between sampling methods, but could be qualitatively assessed via regular buccal swab sampling. This work not only provides new insights into the oral community of ruminants, but further validates and refines buccal swabbing as a method to assess the rumen microbiota in large herds. IMPORTANCEThe gastrointestinal tract of ruminants harbors a diverse microbial community that coevolved symbiotically with the host, influencing its nutrition, health and performance. While the influence of environmental factors on rumen microbes is well-documented, the process by which host genetics influences the establishment and colonization of the rumen microbiota still needs to be elucidated. This knowledge gap is due largely to our inability to easily sample the rumen microbiota. There are three common methods for rumen sampling but all of them present at least one disadvantage, including animal welfare, sample quality, labor, and scalability. The development and validation of non-invasive methods, such as buccal swabbing, for large-scale rumen sampling is needed to support studies that require large sample sizes to generate reliable results. The validation of buccal swabbing will also support the development of molecular tools for the early diagnosis of metabolic disorders associated with microbial changes in large herds.

microbiology↗