Residual soil DNA extraction increases the discriminatory power between samples

pH-Related Changes in Soil Bacterial Communities in the Sanjiang Plain, Northeast China

Soil bacteria are crucial components of terrestrial ecosystems, playing an important role in soil biogeochemical cycles. Although bacterial community diversity and composition are regulated by many abiotic and biotic factors, how soil physiochemical properties impact the soil bacteria community diversity and composition in wetland ecosystems remains largely unknown. In this study, we used high-throughput sequencing technology to investigate the diversity and composition of a soil bacterial community, as well as used the structural equation modeling (SEM) method to investigate the relationships of the soil's physicochemical properties (i.e., soil pH, soil organic carbon (SOC), total nitrogen (TN), ammonium nitrogen (NH4+N), electrical conductivity (EC) and nitrate nitrogen (NO3-N)), and soil bacterial community structures in three typical wetland sites in the Sanjiang Plain wetland. Our results showed that the soil physicochemical properties significantly changed the α and β-diversity of the soil bacteria communities, e.g., soil TN, NH4+N, NO3-N, and SOC were the main soil factors affecting the soil bacterial α-diversity. The soil TN and pH were the key soil factors affecting the soil bacterial community. Our results suggest that changes in soil pH indirectly affect soil bacterial communities by altering the soil nitrogenous nutrient content.

Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data

Taxonomic profiling of ancient metagenomic samples is challenging due to the accumulation of specific damage patterns on DNA over time. Although a number of methods for metagenome profiling have been developed, most of them have been assessed on modern metagenomes or simulated metagenomes mimicking modern metagenomes. Further, a comparative assessment of metagenome profilers on simulated metagenomes representing a spectrum of degradation depth, from the extremity of ancient (most degraded) to current or modern (not degraded) metagenomes, has not yet been performed. To understand the strengths and weaknesses of different metagenome profilers, we performed their comprehensive evaluation on simulated metagenomes representing human dental calculus microbiome, with the level of DNA damage successively raised to mimic modern to ancient metagenomes. All classes of profilers, namely, DNA-to-DNA, DNA-to-protein, and DNA-to-marker comparison-based profilers were evaluated on metagenomes with varying levels of damage simulating deamination, fragmentation, and contamination. Our results revealed that, compared to deamination and fragmentation, human and environmental contamination of ancient DNA (with modern DNA) has the most pronounced effect on the performance of each profiler. Further, the DNA-to-DNA (e.g., Kraken2, Bracken) and DNA-to-marker (e.g., MetaPhlAn4) based profiling approaches showed complementary strengths, which can be leveraged to elevate the state-of-the-art of ancient metagenome profiling.

A Case Study for the Recovery of Authentic Microbial Ancient DNA from Soil Samples

High Throughput DNA Sequencing (HTS) revolutionized the field of paleomicrobiology, leading to an explosive growth of microbial ancient DNA (aDNA) studies, especially from environmental samples. However, aDNA studies that examine environmental microbes routinely fail to authenticate aDNA, examine laboratory and environmental contamination, and control for biases introduced during sample processing. Here, we surveyed the available literature for environmental aDNA projects—from sample collection to data analysis—and assessed previous methodologies and approaches used in the published microbial aDNA studies. We then integrated these concepts into a case study, using shotgun metagenomics to examine methodological, technical, and analytical biases during an environmental aDNA study of soil microbes. Specifically, we compared the impact of five DNA extraction methods and eight bioinformatic pipelines on the recovery of microbial aDNA information in soil cores from extreme environments. Our results show that silica-based methods optimized for aDNA research recovered significantly more damaged and shorter reads (<100 bp) than a commercial kit or a phenol−chloroform method. Additionally, we described a stringent pipeline for data preprocessing, efficiently decreasing the representation of low-complexity and duplicated reads in our datasets and downstream analyses, reducing analytical biases in taxonomic classification.

Effects of biodegradable film mulching on bacterial diversity in soils

The spread of biodegradable plastic films (BDFs) not only increases grain yield but also reduces environmental pollution from plastic film to a large extent. Soil microbes are considered to be involved in biodegradation processes. However, the study of microbe diversity in soil mulched with biodegradable plastic film remains limited. Here, we compared the diversity of microbes between soils with biodegradable film and nonbiodegradable film (NBDF) mulch. The results showed that BDFs affected total C, P and NH₄⁺-N, especially organism C content, as well as microbe species richness (ACE; Chao1) and diversity (Simpson index; Shannon index). In terms of dominant phyla and genera, BDFs and NBDF can influence the abundance of disparate species. Furthermore, BDFs could also contribute to improving the richness of the important functional bacterial groups in soil, e.g., Pedomicrobium and Comamonas, both of which are involved in the degradation of plastic residues in soil. Finally, we found that BDFs improved the transformation of nitrogen by significantly increasing the abundances of Nitrobacter and Nitrospira. Our results highlight the impact of BDF mulch on the abundance of functional bacteria in the soil.

The Requirement of Genetic Diagnostic Technologies for Environmental Surveillance of Antimicrobial Resistance

Antimicrobial resistance (AMR) is threatening modern medicine. While the primary cost of AMR is paid in the healthcare domain, the agricultural and environmental domains are also reservoirs of resistant microorganisms and hence perpetual sources of AMR infections in humans. Consequently, the World Health Organisation and other international agencies are calling for surveillance of AMR in all three domains to guide intervention and risk reduction strategies. Technologies for detecting AMR that have been developed for healthcare settings are not immediately transferable to environmental and agricultural settings, and limited dialogue between the domains has hampered opportunities for cross-fertilisation to develop modified or new technologies. In this feature, we discuss the limitations of currently available AMR sensing technologies used in the clinic for sensing in other environments, and what is required to overcome these limitations.

Variability of indoor fungal microbiome of green and non-green low-income homes in Cincinnati, Ohio

"Green" housing is designed to use low-impact materials, increase energy efficiency and improve occupant health. However, little is known about the indoor mycobiome of green homes. The current study is a subset of a multicenter study that aims to investigate the indoor environment of green homes and the respiratory health of asthmatic children. In the current study, the mycobiome in air, bed dust and floor dust was compared between green (study site) and non-green (control site), low-income homes in Cincinnati, Ohio. The samples were collected at baseline (within four months following renovation), and 12months after the baseline at the study site. Parallel sample collection was conducted in non-green control homes. Air samples were collected by PM2.5 samplers over 5-days. Bed and floor dust samples were vacuumed after the air sampling was completed. The DNA sample extracts were analyzed using ITS amplicon sequencing. Analysis indicated that there was no clear trend in the fungal communities between green and non-green homes. Instead, fungal community differences were greatest between sample types - air, bed, and floor. Microbial communities also changed substantially between sampling intervals in both green and non-green homes for all sample types, potentially indicating that there was very little stability in the mycobiomes. Research gaps remain regarding how indoor mycobiome fluctuates over time. Longer follow-up periods might elucidate the effect of green renovation on microbial load in buildings.