Taxon Appearance From Extraction and Amplification Steps Demonstrates the Value of Multiple Controls in Tick Microbiota Analysis

Background: The development of high-throughput sequencing technologies has substantially improved analysis of bacterial community diversity, composition, and functions. Over the last decade, high-throughput sequencing has been used extensively to identify the diversity and composition of tick microbial communities. However, a growing number of studies are warning about the impact of contamination brought along the different steps of the analytical process, from DNA extraction to amplification. In low biomass samples, e.g., individual tick samples, these contaminants may represent a large part of the obtained sequences, and thus generate considerable errors in downstream analyses and in the interpretation of results. Most studies of tick microbiota either do not mention the inclusion of controls during the DNA extraction or amplification steps, or consider the lack of an electrophoresis signal as an absence of contamination. In this context, we aimed to assess the proportion of contaminant sequences resulting from these steps. We analyzed the microbiota of individual Ixodes ricinus ticks by including several categories of controls throughout the analytical process: homogenization, DNA extraction, and DNA amplification. Results: Controls yielded a significant number of sequences (1, 126–13, 198 mean sequences, depending on the control category). Some operational taxonomic units (OTUs) detected in these controls belong to genera reported in previous tick microbiota studies. In this study, these OTUs accounted for 50.9% of the total number of sequences in our samples, and were considered contaminants. Contamination levels (i.e., the percentage of sequences belonging to OTUs identified as contaminants) varied with tick instar and sex: 76.3% of nymphs and 75% of males demonstrated contamination over 50%, while most females (65.7%) had rates lower than 20%. Contamination mainly corresponded to OTUs detected in homogenization and extraction reagent controls, highlighting the importance of carefully controlling these steps. Conclusion: Here, we showed that contaminant OTUs from sample laboratory processing steps can represent more than half the total sequence yield in sequencing runs, and lead to unreliable results when characterizing tick microbial communities. We thus strongly advise the routine use of negative controls in tick microbiota studies, and more generally in studies involving low biomass samples

Temporal patterns in Ixodes ricinus microbial communities: an insight into tick-borne microbe interactions

Background: Ticks transmit pathogens of medical and veterinary importance and are an increasing threat to human and animal health. Assessing disease risk and developing new control strategies requires identifying members of the tick-borne microbiota as well as their temporal dynamics and interactions. Methods: Using high-throughput sequencing, we studied the Ixodes ricinus microbiota and its temporal dynamics. 371 nymphs were monthly collected during three consecutive years in a peri-urban forest. After a Poisson lognormal model was adjusted to our data set, a principal component analysis, sparse network reconstruction, and differential analysis allowed us to assess seasonal and monthly variability of I. ricinus microbiota and interactions within this community. Results: Around 75% of the detected sequences belonged to five genera known to be maternally inherited bacteria in arthropods and to potentially circulate in ticks: Candidatus Midichloria, Rickettsia, Spiroplasma, Arsenophonus and Wolbachia. The structure of the I. ricinus microbiota varied over time with interannual recurrence and seemed to be mainly driven by OTUs commonly found in the environment. Total network analysis revealed a majority of positive partial correlations. We identified strong relationships between OTUs belonging to Wolbachia and Arsenophonus, evidence for the presence of the parasitoid wasp Ixodiphagus hookeri in ticks. Other associations were observed between the tick symbiont Candidatus Midichloria and pathogens belonging to Rickettsia. Finally, more specific network analyses were performed on TBP-infected samples and suggested that the presence of pathogens belonging to the genera Borrelia, Anaplasma and Rickettsia may disrupt microbial interactions in I. ricinus. Conclusions: We identified the I. ricinus microbiota and documented marked shifts in tick microbiota dynamics over time. Statistically, we showed strong relationships between the presence of specific pathogens and the structure of the I. ricinus microbiota. We detected close links between some tick symbionts and the potential presence of either pathogenic Rickettsia or a parasitoid in ticks. These new findings pave the way for the development of new strategies for the control of ticks and tick-borne diseases. [MediaObject not available: see fulltext.] © 2021, The Author(s)

Anisotropic Superparamagnetism of Monodispersive Cobalt-Platinum Nanocrystals

Based on the high-temperature organometallic route (Sun et al. Science 287, 1989 (2000)), we have synthesized powders containing CoPt_3 single crystals with mean diameters of 3.3(2) nm and 6.0(2) nm and small log-normal widths sigma=0.15(1). In the entire temperature range from 5 K to 400 K, the zero-field cooled susceptibility chi(T) displays significant deviations from ideal superparamagnetism. Approaching the Curie temperature of 450(10) K, the deviations arise from the (mean-field) type reduction of the ferromagnetic moments, while below the blocking temperature T_b, chi(T) is suppressed by the presence of energy barriers, the distributions of which scale with the particle volumes obtained from transmission electron microscopy (TEM). This indication for volume anisotropy is supported by scaling analyses of the shape of the magnetic absorption chi''(T,omega) which reveal distribution functions for the barriers being also consistent with the volume distributions observed by TEM. Above 200 K, the magnetization isotherms M(H,T) display Langevin behavior providing 2.5(1) mu_B per CoPt_3 in agreement with reports on bulk and thin film CoPt_3. The non-Langevin shape of the magnetization curves at lower temperatures is for the first time interpreted as anisotropic superparamagnetism by taking into account an anisotropy energy of the nanoparticles E_A(T). Using the magnitude and temperature variation of E_A(T), the mean energy barriers and 'unphysical' small switching times of the particles obtained from the analyses of chi''(T,omega) are explained. Below T_b hysteresis loops appear and are quantitatively described by a blocking model, which also ignores particle interactions, but takes the size distributions from TEM and the conventional field dependence of E_A into account.Comment: 12 pages with 10 figures and 1 table. Version accepted for publication in Phys. Rev. B . Two-column layou

Deciphering the connectivity structure of biological networks using MixNet

<p>Abstract</p> <p>Background</p> <p>As biological networks often show complex topological features, mathematical methods are required to extract meaningful information. Clustering methods are useful in this setting, as they allow the summary of the network's topology into a small number of relevant classes. Different strategies are possible for clustering, and in this article we focus on a model-based strategy that aims at clustering nodes based on their connectivity profiles.</p> <p>Results</p> <p>We present MixNet, the first publicly available computer software that analyzes biological networks using mixture models. We apply this method to various networks such as the <it>E. coli </it>transcriptional regulatory network, the macaque cortex network, a foodweb network and the <it>Buchnera aphidicola </it>metabolic network. This method is also compared with other approaches such as module identification or hierarchical clustering.</p> <p>Conclusion</p> <p>We show how MixNet can be used to extract meaningful biological information, and to give a summary of the networks topology that highlights important biological features. This approach is powerful as MixNet is adaptive to the network under study, and finds structural information without any a priori on the structure that is investigated. This makes MixNet a very powerful tool to summarize and decipher the connectivity structure of biological networks.</p