Refine
Document Type
- Article (8)
Language
- English (8)
Has Fulltext
- no (8)
Is part of the Bibliography
- no (8)
Keywords
- Metatranscriptomics (2)
- 18S (1)
- Algae (1)
- Coarse perticulate organic matter (1)
- Enzyme activity (1)
- Freshwater ecosystem health (1)
- Fungi (1)
- Illumina (1)
- Macroinvertebrates (1)
- Mesocosm (1)
Institute
Assessing the response of an urban stream ecosystem to salinization under different flow regimes
(2024)
Abstract
Urban streams are exposed to a variety of anthropogenic stressors. Freshwater salinization is a key stressor in these ecosystems that is predicted to be further exacerbated by climate change, which causes simultaneous changes in flow parameters, potentially resulting in non-additive effects on aquatic ecosystems. However, the effects of salinization and flow velocity on urban streams are still poorly understood as multiple-stressor experiments are often conducted at pristine rather than urban sites. Therefore, we conducted a mesocosm experiment at the Boye River, a recently restored stream located in a highly urbanized area in Western Germany, and applied recurrent pulses of salinity along a gradient (NaCl, 9 h daily of +0 to +2.5 mS/cm) in combination with normal and reduced current velocities (20 cm/s vs. 10 cm/s). Using a comprehensive assessment across multiple organism groups (macroinvertebrates, eukaryotic algae, fungi, parasites) and ecosystem functions (primary production, organic-matter decomposition), we show that flow velocity reduction has a pervasive impact, causing community shifts for almost all assessed organism groups (except fungi) and inhibiting organic-matter decomposition. Salinization affected only dynamic components of community assembly by enhancing invertebrate emigration via drift and reducing fungal reproduction. We caution that the comparatively small impact of salt in our study can be due to legacy effects from past salt pollution by coal mining activities >30 years ago. Nevertheless, our results suggest that urban stream management should prioritize the continuity of a minimum discharge to maintain ecosystem integrity. Our study exemplifies a holistic approach for the assessment of multiple-stressor impacts on streams, which is needed to inform the establishment of a salinity threshold above which mitigation actions must be taken.
Rivers face constant anthropogenic stress, resulting in significant changes in microbial community composition. What remains unclear is whether stream microbiomes exhibit distinct resilience patterns in composition and/or activity upon exposure to different stressors. By subjecting 64 river-connected mesocosms to multiple stressors, we show that sediment microbiomes of small lowland rivers are highly sensitive to low flow velocity. This stress results in altered community compositions incapable of mitigating the applied stressor within a two-week timeframe despite functional stability (inferred via metagenomics). Transcriptomics revealed a systematic heat shock response in the community and a highly active, metabolically versatile, uncharacterized anaerobic keystone species. Increases in temperature (+ 3.5°C) or salinity (+ 0.5 mS/cm) elicited minor responses at community and transcriptomic levels (e.g., upregulation of photosystems). Following a two-week recovery, transcriptomic-inferred stress responses vanished completely, underscoring the river microbiome resilience. Given the complex community responses observed at the activity and compositional levels, we conclude that maintaining natural river flow is vital to preventing energy loss and reduced microbiome activity in river sediments.
Significant progress in high-throughput analytical techniques has paved the way for novel approaches to integrating data sets from different compartments. This study leverages nontarget screening (NTS) via liquid chromatography-high-resolution mass spectrometry (LC-HRMS), a crucial technique for analyzing organic micropollutants and their transformation products, in combination with biological indicators. We propose a combined multivariate data processing framework that integrates LC-HRMS-based NTS data with other high-throughput data sets, exemplified here by 18S V9 rRNA and full-length 16S rRNA gene metabarcoding data sets. The power of data fusion is demonstrated by systematically evaluating the impact of treated wastewater (TWW) over time on an aquatic ecosystem through a controlled mesocosm experiment. Highly compressed NTS data were compiled through the implementation of the region of interest-multivariate curve resolution-alternating least-squares (MCR-ALS) method, known as ROIMCR. By integrating ANOVA-simultaneous component analysis with structural learning and integrative decomposition (SLIDE), the innovative SLIDE-ASCA approach enables the decomposition of global and partial common, as well as distinct variation sources arising from experimental factors and their possible interactions. SLIDE-ASCA results indicate that temporal variability explains a much larger portion of the variance (74.6%) than the treatment effect, with both contributing to global shared space variation (41%). Design structure benefits include enhanced interpretability, improved detection of key features, and a more accurate representation of complex interactions between chemical and biological data. This approach offers a greater understanding of the natural and wastewater-influenced temporal patterns for each data source, as well as reveals associations between chemical and biological markers in an exemplified perturbed aquatic ecosystem.
The decomposition of organic matter is essential for sustaining the health of freshwater ecosystems by enabling nutrient recycling, sustaining food webs, and shaping habitat conditions, which collectively enhance ecosystem resilience and productivity. Bacteria and fungi play a crucial role in this process by breaking down coarse particulate organic matter (CPOM), such as leaf litter, into nutrients available for other organisms. However, the specific contribution of bacteria and their functional interactions with fungi in freshwater sediments have yet to be thoroughly explored. In the following study, we enriched organic matter through the addition of alder (Alnus glutinosa) leaves into artificial stream channels (AquaFlow mesocosms). We then investigated enzyme expression, metabolic pathways, and community composition of fungi and bacteria involved in the degradation of CPOM through metatranscriptomics and amplicon sequencing. Enzymes involved in the degradation of lignin, cellulose, and hemicellulose were selectively upregulated with increased organic matter. Analysis of ITS and 16S rRNA gene sequences revealed that during decomposition, fungal communities were predominantly composed of Basidiomycota and Ascomycota, while bacterial communities were largely dominated by Pseudomonadota and Bacteroidota. The similar gene expression patterns of CPOM degradation related enzymes observed between bacteria and fungi indicate potential functional interaction between these microbial groups. This correlation in enzyme expression may indicate that bacteria and fungi are jointly involved in the breakdown of coarse particulate organic matter, potentially through mutualistic interaction. This study uncovers the specific enzymatic activities of bacteria and fungi and the importance of microbial interactions in organic matter decomposition, revealing their central role in facilitating nutrient cycling and maintaining the ecological health and stability of freshwater ecosystems.
Abstract
Understanding intricate microbial interactions in the environment is crucial. This is especially true for the relationships between nutrients and bacteria, as phosphorus, nitrogen and organic carbon availability are known to influence bacterial population dynamics. It has been suggested that low nutrient conditions prompt the evolutionary process of genome streamlining. This process helps conserve scarce nutrients and allows for proliferation. Genome streamlining is associated with genomic properties such as %GC content, genes encoding sigma factors, percent coding regions, gene redundancy, and functional shifts in processes like cell motility and ATP binding cassette transporters, among others. The current study aims to unveil the impact of nutrition on the genome size, %GC content, and functional properties of pelagic freshwater bacteria. We do this at finer taxonomic resolutions for many metagenomically characterized communities. Our study confirms the interplay of trophic level and genomic properties. It also highlights that different nutrient types, particularly phosphorus and nitrogen, impact these properties differently. We observed a covariation of functional traits with genome size. Larger genomes exhibit enriched pathways for motility, environmental interaction, and regulatory genes. ABC transporter genes reflect the availability of nutrients in the environment, with small genomes presumably relying more on metabolites from other organisms. We also discuss the distinct strategies different phyla adopt to adapt to oligotrophic environments. The findings contribute to our understanding of genomic adaptations within complex microbial communities.
ABSTRACT
Advancements in sequencing technologies have revolutionized environmental research, leading to a superior understanding of ecosystem functions. In recent years, high-throughput sequencing techniques evolved from short-read Illumina sequencing to long-read Oxford Nanopore Technologies (ONT) sequencing. While Illumina still dominates the sequencing market and offers high accuracy with low error rates, it is limited by shorter read lengths. ONT provides much longer reads, allowing for greater taxonomic resolution but at the cost of higher error rates. Since existing comparative amplicon analyses deal almost exclusively with prokaryotes, it is uncertain if ONT can serve as a reliable alternative to Illumina regarding protistic metabarcoding approaches. Therefore, this study focuses on comparing error rates, taxonomic classification accuracy, and the community composition of sequences obtained from Illumina and ONT sequencing of the 18S V9 rRNA gene region as well as the full-length 18S rRNA gene from sediment samples. In addition, the applicability of the recently updated Natrix2 amplicon processing pipeline for both sequencing approaches was evaluated. While higher error rates were observed for ONT reads, especially for short reads, the full-length ONT 18S sequences achieved greater taxonomic classification accuracy down to the species level. Illumina V9 sequencing, by contrast, provided reliable classification only down to the phylum level. An analysis of community compositions revealed significant taxonomic differences between the sequencing approaches, with ONT identifying more subtle responses of species to external influences. Nevertheless, the basic community patterns were detectable with all sequencing approaches. To conclude, this study showed for the first time that particularly full-length 18S ONT sequencing can serve as a reliable alternative to Illumina V9 sequencing for protist analysis and may even outperform Illumina depending on the specific research objectives.
The discharge of treated wastewater (TWW) into freshwater ecosystems poses a significant impact on microbial communities, particularly protists, which play a crucial role in nutrient cycling and ecosystem stability. While the ecological effects of TWW on microbial diversity have been studied, understanding the functional responses of protist communities remains limited. This study employs metatranscriptomics to unravel the temporal dynamics of protist community functions in response to TWW exposure. Using mesocosm experiment, water samples were analyzed over a ten-day period to monitor shifts in metabolic pathways and community interactions. Our results indicate that processed metatranscriptomic data, focusing on treatment-significant pathways, is more sensitive than traditional methods, such as meta-barcoding, and non-target screening, in detecting wastewater-induced perturbations. Early exposure to TWW significantly altered expression of pathways associated with signal transduction and environmental interaction, while general metabolic pathways showed resilience. Over time, the protist community showed signs of adaptation with expression levels stabilizing towards the end of the experiment. This study underscores the importance of focussing on functional shifts rather than just taxonomic changes for assessing wastewater impacts on freshwater ecosystems. Our findings advocate for the use of metatranscriptomics as a robust indicator for TWW detection, aiding in development of targeted environmental management strategies.
NGS Detects Extensive Genomic Alterations in Survivors of Irradiated Normal Human Fibroblast Cells
(2024)
Abstract
It is thought that cells surviving ionizing radiation exposure repair DNA double-strand breaks (DSBs) and restore their genomes. However, the recent biochemical and genetic characterization of DSB repair pathways reveals that only homologous recombination (HR) can function in an error-free manner and that the non-homologous end joining (NHEJ) pathways canonical NHEJ (c-NHEJ), alternative end joining (alt-EJ), and single-strand annealing (SSA) are error-prone, and potentially leave behind genomic scars and altered genomes. The strong cell cycle restriction of HR to S/ G2 phases and the unparalleled efficiency of c-NHEJ throughout the cell cycle, raise the intriguing question as to how far a surviving cell reaches after repairing the genome back to its pre-irradiation state. Indeed, there is evidence that the genomes of cells surviving radiation treatment harbor extensive genomic alterations. To directly investigate this possibility, we adopted next-generation sequencing (NGS) technologies and tested a normal human fibroblast cell line, 82-6 hTert, after exposure up to 6 Gy. Cells were irradiated and surviving colonies expanded and the cells frozen. Sequencing analysis using the Illumina sequencing platform and comparison with the unirradiated genome detected frequent genomic alterations in the six investigated radiation survivor clones, including translocations and large deletions. Translocations detected by this analysis and predicted to generate visible cytogenetic alterations were frequently (three out of five) confirmed using mFISH cytogenetic analysis. PCR analysis of selected deletions also confirmed seven of the ten examined. We conclude that cells surviving radiation exposure tolerate and pass to their progeny a wide spectrum of genomic alterations. This recognition needs to be integrated into the interpretation of biological results at all endpoints, as well as in the formulation of mathematical models of radiation action. NGS analysis of irradiated genomes promises to enhance molecular cytogenetics by increasing the spectrum of detectable genomic alterations and advance our understanding of key molecular radiobiological effects and the logic underpinning DSB repair. However, further developments in the technology will be required to harness its full potential.

