Microbial planktonic communities are the basis of food webs in aquatic ecosystems since they contribute substantially to primary production and nutrient recycling. Network analyses of DNA metabarcoding data sets emerged as a powerful tool to untangle the complex ecological relationships among the key players in food webs. In this study, we evaluated co‐occurrence networks constructed from time‐series metabarcoding data sets (12 months, biweekly sampling) of protistan plankton communities in surface layers (epilimnion) and bottom waters (hypolimnion) of two temperate deep lakes, Lake Mondsee (Austria) and Lake Zurich (Switzerland). Lake Zurich plankton communities were less tightly connected, more fragmented and had a higher susceptibility to a species extinction scenario compared to Lake Mondsee communities. We interpret these results as a lower robustness of Lake Zurich protistan plankton to environmental stressors, especially stressors resulting from climate change. In all networks, the phylum Ciliophora contributed the highest number of nodes, among them several in key positions of the networks. Associations in ciliate‐specific subnetworks resembled autecological species‐specific traits that indicate adaptions to specific environmental conditions. We demonstrate the strength of co‐occurrence network analyses to deepen our understanding of plankton community dynamics in lakes and indicate biotic relationships, which resulted in new hypotheses that may guide future research in climate‐stressed ecosystems.
Species of the ciliate genus Urotricha are key players in freshwater plankton communities. In the pelagial of lakes, about 20 urotrich species occur throughout an annual cycle, some of which play a pivotal role in aquatic food webs. For example, during the phytoplankton spring bloom, they consume a remarkable proportion of the algal production. In ecological studies, urotrich ciliates are usually merely identified to genus rank and grouped into size classes. This is unsatisfying considering the distinct autecological properties of individual species and their specific spatial and temporal distribution patterns. As a basis for future research, we characterized in detail four common urotrich morphotypes, i.e., specimens identified as U. furcata and tentatively as U. agilis, U. pseudofurcata, and U. castalia, using state-of-the-art methods. We used an integrative polyphasic approach, in which morphological studies (in vivo observation, silver staining methods, scanning electron microscopy) were linked with a molecular approach exploiting four different gene fragments as taxonomic DNA barcodes with different resolution potential (SSU rDNA, ITS-1, ITS-2, hypervariable V4 and V9 regions of the SSU rDNA). We shed light on the diversity of urotrich ciliates as well as on their global distribution patterns, and annual cycles. Additionally, we coupled individual species occurrences and environmental parameters, and subsequently modeled the distribution and occurrence, using logistic regressions. Furthermore, for one strain putatively identified as U. castalia, we ascertained the optimal cultivation media and food preferences. Thereby, our comprehensive view on these important freshwater ciliates that frequently occur in environmental high throughput sequencing datasets worldwide will allow future studies to better exploit protistan plankton data from lakes.
Ciliates of the genus Urotricha are widely distributed and occur in almost any freshwater body. Thus far, almost all species have been described from morphology only. Here, we applied an integrative approach on the morphology, molecular phylogeny and biogeography of two species isolated from high mountain lakes in the Central Alps, Austria. As these remote lakes are known to have water temperatures <15 °C, our hypothesis was that these urotrichs might prefer ‘cold’ environments. We studied the morphological details from living and silver-stained individuals, and their molecular sequences (ribosomal operon, ITS), and screened available datasets for their biogeography. The two Urotricha species resembled morphological features of several congeners. An accurate species assignment was difficult due to several overlapping characteristics. However, we tentatively attributed the investigated species to Urotricha nais and Urotricha globosa. The biogeographic analyses revealed their occurrence in Europe, Africa and Asia, and no correlations to (cold) temperatures were found. Our findings suggest that these two urotrichs, originating from two cold and remote habitats, are probably cryptic species well adapted to their harsh environment.
The direct conversion of adult human skin fibroblasts (FBs) into induced neurons (iNs) represents a useful technology to generate donor-specific adult-like human neurons. Disease modeling studies rely on the consistently efficient conversion of relatively large cohorts of FBs. Despite the identification of several small molecular enhancers, high-yield protocols still demand addition of recombinant Noggin. To identify a replacement to circumvent the technical and economic challenges associated with Noggin, we assessed dynamic gene expression trajectories of transforming growth factor-β signaling during FB-to-iN conversion. We identified ALK2 (ACVR1) of the bone morphogenic protein branch to possess the highest initial transcript abundance in FBs and the steepest decline during successful neuronal conversion. We thus assessed the efficacy of dorsomorphin homolog 1 (DMH1), a highly selective ALK2-inhibitor, for its potential to replace Noggin. Conversion media containing DMH1 (+DMH1) indeed enhanced conversion efficiencies over basic SMAD inhibition (tSMADi), yielding similar βIII-tubulin (TUBB3) purities as conversion media containing Noggin (+Noggin). Furthermore, +DMH1 induced high yields of iNs with clear neuronal morphologies that are positive for the mature neuronal marker NeuN. Validation of +DMH1 for iN conversion of FBs from 15 adult human donors further demonstrates that Noggin-free conversion consistently yields iN cultures that display high βIII-tubulin numbers with synaptic structures and basic spontaneous neuronal activity at a third of the cost.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.