Microbial composition analyses by 16S rRNA sequencing: A proof of concept approach to provenance determination of archaeological ochre

Microbial genome (Illumina MiSeq) sequencing of drinking water treatment residuals to evaluate compatibility with environmental applications

The clarification of drinking water leads to the production of large quantities of water treatment residuals (WTRs). DNA was extracted from six WTR samples collected from water treatment plants within the UK to compare their bacterial communities and examine whether factors such as coagulant usage (aluminium versus iron salt), the type of water source (reservoir or river), or leachable chemical composition influence these communities. Bacterial 16S variable region 4 (V4) was amplified and sequenced using Illumina MiSeq sequencing. The most abundant phyla in WTR samples were Proteobacteria, Actinobacteria, Bacteroidetes, Acidobacteria, and Firmicutes, collectively representing 92.77-97.8% of the total bacterial sequences. Statistical analysis of microbial profiles indicated that water source played a significant role in microbial community structure, diversity, and richness, however coagulant type did not. PERMANOVA analysis showed that no single chemical variable (pH, organic matter, or extractable element concentration) influenced microbial composition significantly; however, canonical correspondence analysis of WTR microbiomes yielded a model using all these variables that could be used to explain variations in microbial community structures of WTRs (p < 0.05). No common, potentially toxic cyanobacteria, or related pathogens of concern were found. Analysis with PICRUSt showed that WTRs all had similar predicted microbial functional profiles. Overall, the results indicate that WTRs analysed in this study are unlikely to pose any threat to soil microbial community structure when applied to land as a soil conditioner or enhancer and may help to enhance the soil microbial community.

Geographic source estimation using airborne plant environmental DNA in dust

Information obtained from the analysis of dust, particularly biological particles such as pollen, plant parts, and fungal spores, has great utility in forensic geolocation. As an alternative to manual microscopic analysis of dust components, we developed a pipeline that utilizes the airborne plant environmental DNA (eDNA) in settled dust to estimate geographic origin. Metabarcoding of settled airborne eDNA was used to identify plant species whose geographic distributions were then derived from occurrence records in the USGS Biodiversity in Service of Our Nation (BISON) database. The distributions for all plant species identified in a sample were used to generate a probabilistic estimate of the sample source. With settled dust collected at four U.S. sites over a 15-month period, we demonstrated positive regional geolocation (within 600 km² of the collection point) with 47.6% (20 of 42) of the samples analyzed. Attribution accuracy and resolution was dependent on the number of plant species identified in a dust sample, which was greatly affected by the season of collection. In dust samples that yielded a minimum of 20 identified plant species, positive regional attribution was achieved with 66.7% (16 of 24 samples). For broader demonstration, citizen-collected dust samples collected from 31 diverse U.S. sites were analyzed, and trace plant eDNA provided relevant regional attribution information on provenance in 32.2% of samples. This showed that analysis of airborne plant eDNA in settled dust can provide an accurate estimate regional provenance within the U.S., and relevant forensic information, for a substantial fraction of samples analyzed.

Microbial community types and signature-like soil bacterial patterns from fortified prehistoric hills of Thuringia (Germany)

16S rRNA profiling has been applied for the investigation of bacterial communities of surface soil samples from forest-covered areas of ten prehistorical ramparts from different parts of Thuringia. Besides the majority bacterial types that are present in all samples, there could be identified bacteria that are highly abundant in some places and absent or low abundant in others. These differences are mainly related to the acidity of substrate and distinguish the communities of lime stone hills from soils of sand/quartzite and basalt hills. Minority components of bacterial communities show partially large differences that cannot be explained by the pH of the soil or incidental effects, only. They reflect certain relations between the communities of different places and could be regarded as a kind of signature-like patterns. Such relations had also been found in a comparison of the data from ramparts with formerly studied 16S rRNA profiling from an iron-age burial field. The observations are supporting the idea that a part of the components of bacterial communities from soil samples reflect their ecological history and can be understood as the “ecological memory” of a place. Probably such memory effects can date back to prehistoric times and might assist in future interpretations of archaeological findings on the prehistoric use of a place, on the one hand. On the other hand, the genetic profiling of soils of prehistoric places contributes to the evaluation of anthropogenic effects on the development of local soil bacterial diversity.