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Single-molecule approaches provide enormous insight into the dynamics of biomolecules, but adequately sampling distributions of states and events often requires extensive sampling. Although emerging experimental techniques can generate such large datasets, existing analysis tools are not suitable to process the large volume of data obtained in high-throughput paradigms. Here, we present a new analysis platform (DISC) that accelerates unsupervised analysis of single-molecule trajectories. By merging model-free statistical learning with the Viterbi algorithm, DISC idealizes single-molecule trajectories up to three orders of magnitude faster with improved accuracy compared to other commonly used algorithms. Further, we demonstrate the utility of DISC algorithm to probe cooperativity between multiple binding events in the cyclic nucleotide binding domains of HCN pacemaker channel. Given the flexible and efficient nature of DISC, we anticipate it will be a powerful tool for unsupervised processing of high-throughput data across a range of single-molecule experiments. 

Eutrophication of inland waters is expected to increase the frequency and severity of harmful algal blooms (HABs). Toxin-production associated with HABs has negative effects on human health and aquatic ecosystem functioning. Despite evidence that flagellates can ingest toxin-producing cyanobacteria, interactions between members of the microbial loop are underestimated in our understanding of the food web and algal bloom dynamics. Physical and allelopathic interactions between a mixotrophic flagellate (Cryptomonas sp.) and two strains of a cyanobacteria (Microcystis aeruginosa) were investigated in a full-factorial experiment in culture. The maximum population growth rate of the mixotroph (0.25 day−1) occurred during incubation with filtrate from toxic M. aeruginosa. Cryptomonas was able to ingest toxic and non-toxic M. aeruginosa at maximal rates of 0.5 and 0.3 cells day−1, respectively. The results establish that although Cryptomonas does not derive benefits from co-incubation with M. aeruginosa, it may obtain nutritional supplement from filtrate. We also provide evidence of a reduction in cyanotoxin concentration (microcystin-LR) when toxic M. aeruginosa is incubated with the mixotroph. Our work has implications for “trophic upgrading” within the microbial food web, where cyanobacterivory by nanoflagellates may improve food quality for higher trophic levels and detoxify secondary compounds. 

Abstract Spatial synchrony is defined by related fluctuations through time in population abundances measured at different locations. The degree of relatedness typically declines with increasing distance between sampling locations. Standard approaches for assessing synchrony assume isotropy in space and uniformity across timescales of analysis, but it is now known that spatial variability and timescale structure in population dynamics are common features. We tested for spatial and timescale structure in the patterns of synchrony of freshwater plankton in Kentucky Lake, U.S.A. We also evaluated whether different mechanisms may drive synchrony and its spatial structure on different timescales. Using wavelet techniques and matrix regression, we analyzed phytoplankton biomass and abundances of seven zooplankton taxa at 16 locations sampled from 1990 to 2015. We found that zooplankton abundances and phytoplankton biomass exhibited synchrony at multiple timescales. Timescale structure in the potential mechanisms of synchrony was revealed primarily through networks of relationships among zooplankton taxa, which differed by timescale. We found substantial interspecific variability in geographic structures of synchrony and their causes: all mechanisms we considered strongly explained geographic structure in synchrony for at least one species, while Euclidean distance between sampling locations was generally less well supported than more mechanistic explanations. Geographic structure in synchrony and its underlying mechanisms also depended on timescale for a minority of the taxa tested. Overall, our results show substantial and complex but interpretable variation in structures of synchrony across three variables: space, timescale, and taxon. It seems likely these aspects of synchrony are important general features of freshwater systems.