Microbial community structures are shaped by geochemical factors and their interactions with the lithosphere, hydrosphere, and atmosphere through the processes of chemical mobilisation and mineralisation. High-altitude wetlands and salt flats in the central Andes are characterised by pronounced physicochemical gradients and extreme climatic conditions, representing hotspots of microbial diversity. We here hypothesise about the existence of direct relationships between the local microbiology and the climate cyclicity variables based on meteorological and biogeochemical patterns that develop over a short time scale (five years). We have here analysed the interactions between hydrometeorological and biogeochemical variables and the microbial communities of the Salar de Huasco. These results were obtained by correlating 16S cDNA and DNA gene Illumina sequences with meteorological/satellite data collected both at monitoring stations and by remote sensing between the years 2015 and 2020. The precipitation levels and flooded areas (i.e., areas covered and/or saturated with permanent water) detected in the Salar de Huasco revealed a marked hydric cyclicity that correlated seasonally with intra-annual wet and dry seasons. Overall, at this site, wet periods occurred from December to April, and dry periods from May to November. Meteorological variables such as solar radiation, air temperature, relative humidity, wind speed, atmospheric pressure, and wind direction were well-defined, showing a potential association with the hydrogeology of the area, which is directly related to the wetlands' flooded areas. Finally, the microbial presence and potentially active microbial communities were determined through the sequencing of the 16S gene (DNA and cDNA, respectively), this were associated with climatic seasonality and spatially distributed physical and chemical heterogeneity. Other non-local inter-annual scale processes, such as El Niño-Southern Oscillation (ENSO) events, modify the physical and chemical context of the wetland, thus forming unique ecological niches in the Andean Mountains.

Hydrothermal systems are ideal to understand how microbial communities cope with challenging conditions. Lirima, our study site, is a polyextreme, high-altitude, hydrothermal ecosystem located in the Chilean Andean highlands. Herein, we analyze the benthic communities of three nearby springs in a gradient of temperature (42–72 °C represented by stations P42, P53, and P72) and pH, and we characterize their microbial diversity by using bacteria 16S rRNA (V4) gene metabarcoding and 16S rRNA gene clone libraries (bacteria and archaea). Bacterial clone libraries of P42 and P53 springs showed that the community composition was mainly represented by phototrophic bacteria (Chlorobia, 3%, Cyanobacteria 3%, at P42; Chlorobia 5%, and Chloroflexi 5% at P53), Firmicutes (32% at P42 and 43% at P53) and Gammaproteobacteria (13% at P42 and 29% at P53). Furthermore, bacterial communities that were analyzed by 16S rRNA gene metabarcoding were characterized by an overall predominance of Chloroflexi in springs with lower temperatures (33% at P42), followed by Firmicutes in hotter springs (50% at P72). The archaeal diversity of P42 and P53 were represented by taxa belonging to Crenarchaeota, Diapherotrites, Nanoarchaeota, Hadesarchaeota, Thaumarchaeota, and Euryarchaeota. The microbial diversity of the Lirima hydrothermal system is represented by groups from deep branches of the tree of life, suggesting this ecosystem as a reservoir of primitive life and a key system to study the processes that shaped the evolution of the biosphere.

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.

Contamination with exogenous DNA presents a significant challenge in ancient DNA (aDNA) studies of single organisms. Failure to address contamination from microbes, reagents, and present-day sources can impact the interpretation of results. Although field and laboratory protocols exist to limit contamination, there is still a need to accurately distinguish between endogenous and exogenous data computationally. Here, we propose a workflow to reduce exogenous contamination based on a metagenomic classifier. Unlike previous methods that relied exclusively on DNA sequencing reads mapping specificity to a single reference genome to remove contaminating reads, our approach uses Kraken2-based filtering before mapping to the reference genome. Using both simulated and empirical shotgun aDNA data, we show that this workflow presents a simple and efficient method that can be used in a wide range of computational environments—including personal machines. We propose strategies to build specific databases used to profile sequencing data that take into consideration available computational resources and prior knowledge about the target taxa and likely contaminants. Our workflow significantly reduces the overall computational resources required during the mapping process and reduces the total runtime by up to ~94%. The most significant impacts are observed in low endogenous samples. Importantly, contaminants that would map to the reference are filtered out using our strategy, reducing false positive alignments. We also show that our method results in a negligible loss of endogenous data with no measurable impact on downstream population genetics analyses.

The Gippsland Lakes is the largest estuarine system in Australia. Over the last 2 centuries, this unique aquatic ecosystem has suffered substantial modifications mostly associated with anthropogenic impacts, including the creation in 1889 of an artificial channel to the ocean after European arrival, creating chronic salinisation in the system. However, the biological impacts of this historic shift are unclear. Here, we use shotgun metagenomics of environmental DNA from historical sediments of Lake King and Lake Victoria to detect ancient microbial DNA and track past ecological changes in prokaryotic communities. Sedimentary prokaryotic communities changed with core depth, organic matter levels and European arrival. Specifically, we observed an increase in sulfate‐reducing bacteria (e.g., Desulfobacterales) and organic matter enrichment in the upper layers of the sediment cores of the Gippsland Lakes, which could reflect a period of eutrophication caused by higher rates of organic deposition and marine intrusion post‐European arrival. However, while some species presented authentic ancient DNA signals, the shifts in community composition probably reflect changes in indigenous sediment‐dwelling microorganisms in response to geochemical changes of the sediment. Overall, these observations suggest that historic waterway management practices may influence microbial systems today and that sedimentary microbial communities can change in response to both natural biogeochemical dynamics along the depth profile and past environmental conditions.

Terrestrial hydrothermal systems provide a window for studying the biogeochemical interactions that occur in hot and gas-rich ecosystems resembling the conditions found in early life on Earth. The biogeochemical dynamics of the Andean hydrothermal systems in the Atacama Desert area are still understudied. Thus, we aimed to characterize the taxonomic composition and genomic potential of nitrogen transformations in a microbial community inhabiting a high-altitude hydrothermal system on the Altiplano Plateau of the Chilean Andes. Specifically, we sampled sediment and microbial mats in three ponds with water temperatures ranging from 42 to 64 °C. We found a high prevalence of photoheterotrophs, with differences in taxonomic composition and gene abundance between the microbial communities found in the sediment and microbial mats. Changes in physicochemical conditions, such as temperature and pH, and the concentrations of CO₂, CH₄ and Mn accounted for the variability in the microbial community structure. Our results indicated an enrichment of N-related genes associated with nitrate reduction, denitrification, and ammonia assimilation, suggesting a metabolically versatile community using nitrate, nitrite, and gaseous nitrogen species to assimilate ammonia into their biomass. This study contributes to our understanding of the taxonomy and functional microbial dynamics in a high-altitude thermal system, where ammonia assimilation is potentially critical for biomass formation, and particular environmental conditions favor adaptations to maintain biogeochemical cycles.