Biology subjects

Buchner, D.

Publications and source records attributed to Buchner, D..

11 recordsLinked to original sources

bioRxiv2026

Charting the insect biodiversity of Crete: insights from a pilot metabarcoding survey

Among eukaryotes, insects are by far the most diverse organisms on Earth, yet their global decline threatens ecosystem stability. Understanding local and regional biodiversity patterns is critical for conservation planning, ecosystem management, and predicting responses to environmental change, but traditional surveys for assessing insect diversity (e.g., manual collection, morphological identification, and counting) are highly labor-intensive, time-consuming, and often require rare or simply unavailable dedicated taxonomic expertise. DNA metabarcoding offers an efficient, high-resolution alternative to assess insect communities. Here, we report on the first insect metabarcoding survey on Crete that spans two years of sample collection between 2021 and 2023 from a small area in Southern Central Crete in the context of a citizen science project. A total of 29 samples yielded 10,865 Exact Sequence Variants (ESVs), 10,516 of which were assigned to insects, covering 988 species, 900 genera, and 227 families across 14 orders. A comparison with the existing observation records reveals 406 potential newly-observed species and an estimated 690 unclassified species, indicating substantial cryptic diversity. Our results demonstrate that even small-scale sampling can unravel substantial insect diversity and highlight critical gaps in barcode reference databases. Our study demonstrates how DNA metabarcoding can accelerate biodiversity discovery and monitoring in understudied regions.

ecology↗

bioRxiv2026

Disentangling mitochondrial copy number variation and PCR amplification bias in DNA metabarcoding

DNA metabarcoding is a central tool in biodiversity research and monitoring, producing detailed taxa lists with comparatively little time and effort. One of its limitations, however, is the lack of quantitative data on biomass or abundance. This limitation has two main reasons: 1) DNA template copy number variation and 2) primer-induced PCR amplification bias. Many metabarcoding markers are mitochondrial and mitochondrial DNA copy numbers vary in animal tissues, potentially decoupling sequence counts from biomass. Additionally, primer mismatches can lead to taxon-specific amplification biases, for which PCR cycle calibration has been proposed as a solution. To mechanistically study both effects, we constructed and analyzed mock communities of different arthropod species. We combined digital PCR and COI metabarcoding to quantify relationships between biomass, mitochondrial copy number, and metabarcoding reads. Mitochondrial DNA copy numbers per biomass varied strongly within and among the different taxa. Metabarcoding reads did not reflect input mitochondrial DNA copies without a correction. Attempts to correct for amplification bias via PCR cycle calibration failed as read proportions remained stable across cycles. We therefore mathematically derived an approach to estimate relative amplification bias and initial mitochondrial DNA copy numbers in a sample based on a non-exponential amplification bias model and demonstrate its applicability. Still, the detected high variation in mitochondrial copy numbers and derived prerequisites necessary to calculate amplification efficiencies and mitochondrial copy numbers limit the practical application. Our study highlights fundamental constraints of quantitative metabarcoding and underscores the need for additional methodological approaches for quantitative insights while delivering essential conceptual insights.

molecular biology↗

bioRxiv2025

Environmental DNA metabarcoding of invertebrate-incubated water supports WFD-compliant and animal-friendly bioassessment with added trait insights

Environmental (eDNA) metabarcoding is recently being considered for bioassessment under the Water Framework Directive (WFD). While tissue-based ("bulk") metabarcoding of macroinvertebrates produces comparable ecological status class values to morphology-based methods, eDNA-based metabarcoding often includes DNA signals from upstream sites, limiting its site-specificity. A promising alternative involves the incubation of locally collected invertebrates in water, followed by eDNA metabarcoding of the incubated water. In this study, we tested the suitability of two different approaches of the incubation strategy for ecological status assessment under the WFD. The first approach uses conventional multi-habitat sampling (MH) for the collection of the local macroinvertebrates and the second natural substrate exposures (NSEs) that are actively colonised. Using metabarcoding of the incubated water from both approaches (MH/NSE eDNA), we compared community composition, trait diversity and the derived ecological status classes (ESCs) to the local signal reference (MH/NSE bulk DNA) and the regional signal reference (stream water eDNA). For both approaches, community and trait composition were highly congruent between the incubated water and bulk samples. Trait composition did not differ between MH and NSE samples or among NSE types (wood-leaf vs. gravel). However, we detected small-scale spatial differences in the trait composition between NSEs placed at different flow regimes (pool vs. riffle). ESCs derived from all approaches (MH/NSE incubated water eDNA, MH/NSE bulk DNA and stream water eDNA) were highly similar and consistent with those from morpho-taxonomic assessments. Our findings support the incubation strategy using the conventional MH sampling as the most suitable approach for a minimally invasive, site-specific stream bioassessment within the context of the WFD.

ecology↗

bioRxiv2024

Multiple stressor effects on organic carbon degradation and microbial community composition in urban river sediments in a mesocosm experiment

Microorganisms in river sediments are the primarily responsible organisms for the turnover of dissolved organic carbon (DOC) in these systems and therefore are key players for river ecosystem functioning. Rivers are increasingly threatened by multiple stressors such as salinization and temperature rise, but little is known about how microbial DOC-degradation responds to these stressors and whether this function recovers after stressor release. Here, we investigated the direct and indirect effects of salinity and temperature increase and decrease on microbial communities and their ability to degrade DOC in river sediments using the outdoor experimental mesocosm system ExStream. Composition of sediment microbial communities was determined at the end of acclimatization, stressor, and recovery phase using 16S rRNA gene sequencing. At the same time points, DOC degradation rates were quantified in additional microcosm incubations based on isotopic changes of CO2 with the help of reverse stable isotope labelling. Our results showed that raising the salinity by 154.1 mg Cl- L-1 and temperature by 3.5 {degrees}C did not affect DOC degradation during the stressor phase but significantly increased DOC degradation in the recovery phase after stressors were released. Likewise, microbial community composition stayed constant during acclimation and stressor phase, but became more diverse in the recovery phase. The results indicate that microbial community composition and functioning were resistant towards both stressors, but responded to stressor release due to indirect effects of stressor increase and release on the riverine food web. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/602289v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1074eccorg.highwire.dtl.DTLVardef@c634a1org.highwire.dtl.DTLVardef@a96182org.highwire.dtl.DTLVardef@40ae8e_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Effects of temperature and salinity on microbial degradation of bacterial necromass in urban river sediments in outdoor mesocosm experiments

Microorganisms play a key role in the functioning of healthy river ecosystems because they consume carbon and nutrients from dead biomass derived from algae and other higher organisms, or "necromass", to feed it back into the food web. This so-called microbial loop is known to be substantial in aquatic systems, but it is so far unknown to which extent microorganisms perform self-recycling, i.e. recycling of necromass derived from microorganisms, and how this process is affected by multiple stressors such as increased temperature and salinity. In this study, we investigated microbial self-recycling in the sediment of the urban river Boye within a food-web context before, during, and after a period of increased temperature and salinity using the outdoor flow-through mesocosm system "ExStream". Rates of self-recycling were measured in additional microcosms with sediment and water from ExStream as an increase in 13CO2-concentration over time resulting from the microbial degradation of 13C-labelled microbial necromass, which was offered either in the form of intact but dead Escherichia coli cells, or lysed E. coli cells. The results showed that microbial self-recycling was highest in the first days of incubation suggesting that microbial necromass is an easily biodegradable carbon source. Increased salinity had no effect, but increased temperature or temperature and salinity strongly increased the rate of whole cell-necromass recycling compared to the unstressed control, while it had no effect on lysed cell-necromass recycling. After stressor removal, rates of self-recycling were not distinguishable from the unstressed control, showing the resilience of this community function. The compositions of the necromass-degrading communities were highly similar and little affected by stressor increase or release but changed during the course of the experiment. This indicated that both necromass types stimulated growth of the same organisms and that stressor levels were rather low for microorganisms and dominated by the effects of the seasonal variation in the Boye. The study suggests that microbial communities in urban rivers exposed to moderate levels of multiple anthropogenic stressors will be rather stressor-resistant and show fast recovery of community functioning.

microbiology↗

bioRxiv2024

Assessment of microphytobenthos communities in the Kinzigcatchment using photosynthesis-related traits, digital light microscopy and 18S-V9 amplicon sequencing

Microalgae form an essential group of benthic organisms that respond swiftly to environmental changes. They are widely used as bioindicators of anthropogenic stressors in freshwater ecosystems. We aimed to assess the responses of microalgae communities to multiple environmental stressors in the Kinzig River catchment, home to a long-term ecological monitoring site, in Germany. We used a photosynthetic biomass proxy alongside community composition of diatoms assessed by digital light microscopy, and of microalgae by 18S-V9 amplicon sequencing, to characterise microalgae at 19 sampling sites scattered across the catchment. Our results revealed significant effects of physical and chemical factors on microalgae biomass and community compositions. We found that conductivity, water temperature and pH were the most important factors affecting microalgae community composition, as observed in both microscopy and amplicon analysis. In addition to these three variables, the effect of total phosphate on all microalgae, together with water discharge on the diatom (Bacillariophyta) communities, as assessed by amplicon analysis, may reveal taxon-specific variations in the ecological responses of different microalgal groups. Our results highlighted the complex relationship between various environmental variables and microalgae biomass and community composition. Further investigations, involving the collection of time series data, are required to fully understand the underlying biotic and abiotic parameters that influence these microalgae communities.

ecology↗

bioRxiv2024

Complex compositional and cellular response of river sediment microbiomes to multiple anthropogenic stressors

Rivers face constant anthropogenic stressors, resulting in significant changes in microbial community composition. What remains unclear is whether these changes render the microbiome better adapted to the stressed environment. Here, by subjecting 64 river-connected mesocosms to multiple stressors, we show that sediment microbiomes of small lowland rivers are highly sensitive to lowered flow velocity resulting in substantially altered community compositions not fully capable of compensating for the stressor effect within two weeks albeit having stable functions encoded in metagenomes. Transcriptomics revealed a systematic heat shock response in the community and a highly active, previously unknown anaerobic key stone species with great metabolic versatility. Increases in temperature (+3.5 {degrees}C) or salinity (+0.5 mS/cm) were outcompeted by lowered flow and elicited only minor responses at community or transcriptomic level with, e.g., upregulation of the photosystem of chloroplasts. Following a two-week recovery period, transcriptomic stress responses vanished completely compared to control mesocosms, exemplifying the river microbiomes resilience. We conclude that, given the complex community responses at both the cellular and compositional level, maintaining natural river flow is vital to preventing energy loss and reduced microbiome activity in river sediments.

ecology↗

bioRxiv2023

German-wide Malaise trap metabarcoding estimates over 33,000 insect species

Mitigating ongoing losses of insects and their key functions (e.g., pollination) requires accurately tracking large-scale and long-term community changes. However, doing so has been notoriously hindered by uniquely high insect species diversity that requires prohibitively high investments of time, funding, and taxonomic expertise. Here, we show that these concerns can be addressed through a comprehensive, scalable and cost-efficient DNA metabarcoding workflow. We use 1,815 samples from 75 Malaise traps across Germany from 2019 and 2020 to demonstrate how metabarcoding can be incorporated into large-scale insect monitoring networks for less than 50 {euro} per sample, including supplies, labor and maintenance. With on average 1.4M sequence reads per sample we uncovered 10,803 validated insect species, of which 83.9% were represented by a single OTU. We estimated another 21,403 plausible species, which likely either lack a reference barcode or are undescribed. The total of 31,846 species is similar to the number of insect species known for Germany ([~]35,500). Because Malaise traps capture only a subset of insects, our approach identified many species likely unknown from Germany or new to science. Our reproducible workflow ([~]80% OTU-similarity among years) provides a blueprint for large-scale biodiversity monitoring of insects and other biodiversity components in near real time.

ecology↗

bioRxiv2022

Predicting environmental stressor levels with machine learning: a comparison between amplicon sequencing, metagenomics, and total RNA sequencing based on taxonomically assigned data

BackgroundMicrobes are increasingly (re)considered for environmental assessments because they are powerful indicators for the health of ecosystems. The complexity of microbial communities necessitates powerful novel tools to derive conclusions for environmental decision-makers, and machine learning is a promising option in that context. While amplicon sequencing is typically applied to assess microbial communities, metagenomics and total RNA sequencing (herein summarized as omics-based methods) can provide a more holistic picture of microbial biodiversity at sufficient sequencing depths. Despite this advantage, amplicon sequencing and omics-based methods have not yet been compared for taxonomy-based environmental assessments with machine learning. In this study, we applied 16S and ITS-2 sequencing, metagenomics, and total RNA sequencing to samples from a stream mesocosm experiment that investigated the impacts of two aquatic stressors, insecticide and increased fine sediment deposition, on stream biodiversity. We processed the data using similarity clustering and denoising (only applicable to amplicon sequencing) as well as multiple taxonomic levels, data types, feature selection, and machine learning algorithms and evaluated the stressor prediction performance of each generated model for a total of 1,536 evaluated combinations of taxonomic datasets and data-processing methods. ResultsSequencing and data-processing methods had a substantial impact on stressor prediction. While omics-based methods detected much more taxa than amplicon sequencing, 16S sequencing outperformed all other sequencing methods in terms of stressor prediction based on the Matthews Correlation Coefficient. However, even the highest observed performance for 16S sequencing was still only moderate. Omics-based methods performed poorly overall, but this was likely due to insufficient sequencing depth. Data types had no impact on performance while feature selection significantly improved performance for omics-based methods but not for amplicon sequencing. ConclusionAmplicon sequencing might be a better candidate for machine-learning-based environmental stressor prediction than omics-based methods, but the latter require further research at higher sequencing depths to confirm this conclusion. More sampling could improve stressor prediction performance, and while this was not possible in the context of our study, thousands of sampling sites are monitored for routine environmental assessments, providing an ideal framework to further refine the approach for possible implementation in environmental diagnostics.

genomics↗

bioRxiv2020

Improved freshwater macroinvertebrate detection from eDNA through minimized non-target amplification

DNA metabarcoding of freshwater communities typically relies on PCR amplification of a fragment of the mitochondrial cytochrome c oxidase (COI) gene with degenerate primers. The advantage of COI is its taxonomic resolution and the availability of an extensive reference database. However, when universal primers are used on environmental DNA (eDNA) isolated from stream water, macroinvertebrate read and OTU numbers are typically "watered down", i.e. diluted, compared to whole specimen bulk samples due to greater co-amplification of abundant non-target taxa such as algae and bacteria. Because stream macroinvertebrate taxa are of prime importance for regulatory biomonitoring, more effective ways to capture their diversity via eDNA isolated from water are important. In this study, we aimed to improve macroinvertebrate assessment from eDNA by minimizing non-target amplification. Therefore, we generated data using universal primers BF2/BR2 throughout 15 months from a German Long-Term Ecological Research (LTER) site, the River Kinzig, to identify most abundant non-target taxa. Based on these data, we designed a new reverse primer (EPTDr2n) with 3-specificity towards macrozoobenthic taxa and validated its specificity in silico together with universal forward primer fwhF2 using available data from GenBank and BOLD. We then performed in vitro tests using 20 eDNA samples taken in the Kinzig catchment. We found that the percentage of target reads was much higher for the new primer combination compared to two universal macrozoobenthic primer pairs, BF2/BR2 and fwhF2/fwhR2n (>99 % vs. 21.4 % and 41.25 %, respectively). Likewise, number of detected macroinvertebrate taxa was substantially higher (351 vs. 46 and 170, respectively) and exceeded the number of 257 taxa identified by expert taxonomists at nearby sites across two decades of sampling. While few taxa such as Turbellaria were not detected, we show that the optimized primer avoids the dilution problem and thus significantly improves macroinvertebrate detection for bioassessment and -monitoring.

ecology↗

bioRxiv2019

The proteome of small urinary extracellular vesicles after kidney transplantation as an indicator of renal cellular biology and a source for markers predicting outcome

Kidney transplantation is the preferred renal replacement therapy available. Yet, the biological processes during and after kidney transplantation and how they translate into the overall functional graft outcome are insufficiently understood. Recent developments in the field of extracellular vesicle research allow the deeper exploitation of this non-invasive source. We separated small urinary extracellular vesicles (suEVs) throughout the course of living donor kidney transplantation. SuEVs were collected longitudinally from both the donor and the recipient in 22 living donor kidney transplantations. Unbiased proteomic analysis revealed specific temporal patterns of suEV proteins indicative of the cellular processes involved in the allografts response after transplantation with proteins playing a role in complement activation being among the most dynamically regulated components. Using a leave-one-out cross validation model, we identified potential prognostic markers of kidney function at 1 year after transplantation. One of the proteins identified - phosphoenol pyruvate carboxykinase (PCK2) - could be confirmed in an independent validation cohort of another 22 donor-recipient pairs using targeted mass spectrometry. This study sheds the light on early molecular processes during the course of kidney transplantation and shows the future potential of suEVs as a source of biomarkers in this setting. The data set is provided as a unique resource directly accessible through an online tool that allows dynamic interrogation of this first comprising suEV proteome atlas after kidney transplantation. One Sentence SummaryThis study represents the first atlas of the proteomic changes in small urinary extracellular vesicles throughout living donor kidney transplantation identifying PCK2 abundance as a biomarker for renal function 12 months after transplantation

molecular biology↗