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Background: The causative agent of Chagas disease, Trypanosoma cruzi, and its nonpathogenic relative, Trypanosoma rangeli, are transmitted by haematophagous triatomines and undergo a crucial ontogenetic phase in the insect’s intestine. In the process, the parasites interfere with the host immune system as well as the microbiome present in the digestive tract potentially establishing an environment advantageous for development. However, the coherent interactions between host, pathogen and microbiota have not yet been elucidated in detail. We applied a metagenome shotgun sequencing approach to study the alterations in the microbiota of Rhodnius prolixus, a major vector of Chagas disease, after exposure to T. cruzi and T. rangeli focusing also on the functional capacities present in the intestinal microbiome of the insect.
Results: The intestinal microbiota of R. prolixus was dominated by the bacterial orders Enterobacterales, Corynebacteriales, Lactobacillales, Clostridiales and Chlamydiales, whereas the latter conceivably originated from the blood used for pathogen exposure. The anterior and posterior midgut samples of the exposed insects showed a reduced overall number of organisms compared to the control group. However, we also found enriched bacterial groups after exposure to T. cruzi as well as T rangeli. While the relative abundance of Enterobacterales and Corynebacteriales decreased considerably, the Lactobacillales, mainly composed of the genus Enterococcus, developed as the most abundant taxonomic group. This applies in particular to vectors challenged with T. rangeli and at early timepoints after exposure to vectors challenged with T. cruzi. Furthermore, we were able to reconstruct four metagenome-assembled genomes from the intestinal samples and elucidate their unique metabolic functionalities within the triatomine microbiome, including the genome of a recently described insect symbiont, Candidatus Symbiopectobacterium, and the secondary metabolites producing bacteria Kocuria spp.
Conclusions: Our results facilitate a deeper understanding of the processes that take place in the intestinal tract of triatomine vectors during colonisation by trypanosomal parasites and highlight the influential aspects of pathogen-microbiota interactions. In particular, the mostly unexplored metabolic capacities of the insect vector’s microbiome are clearer, underlining its role in the transmission of Chagas disease.
Mosquito breeding sites are complex aquatic environments with wide microbial diversity and physicochemical parameters that can change over time during the development of immature insect stages. Changes in biotic and abiotic conditions in water can alter life-history traits of adult mosquitos but this area remains understudied. Here, using microbial genomic and metabolomics analyses, we explored the metabolites associated with Aedes aegypti breeding sites as well as the potential contribution of Klebsiella sp., symbiotic bacteria highly associated with mosquitoes. We sought to address whether breeding sites have a signature metabolic profile and understand the metabolite contribution of the bacteria in the aquatic niches where Ae. aegypti larvae develop. An analysis of 32 mosquito-associated bacterial genomes, including Klebsiella, allowed us to identify gene clusters involved in primary metabolic pathways. From them, we inferred metabolites that could impact larval development (e.g., spermidine), as well as influence the quality assessment of a breeding site by a gravid female (e.g., putrescine), if produced by bacteria in the water. We also detected significant variance in metabolite presence profiles between water samples representing a decoupled oviposition event (oviposition by single females and manually deposited eggs) versus a control where no mosquito interactions occurred (PERMANOVA: p < 0.05; R2 = 24.64% and R2 = 30.07%). Five Klebsiella metabolites were exclusively linked to water samples where oviposition and development occurred. These data suggest metabolomics can be applied to identify compounds potentially used by female Ae. aegypti to evaluate the quality of a breeding site. Elucidating the physiological mechanisms by which the females could integrate these sensory cues while ovipositing constitutes a growing field of interest, which could benefit from a more depurated list of candidate molecules.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
Trypanosoma cruzi, the causative agent of Chagas disease (American trypanosomiasis), colonizes the intestinal tract of triatomines. Triatomine bugs act as vectors in the life cycle of the parasite and transmit infective parasite stages to animals and humans. Contact of the vector with T. cruzi alters its intestinal microbial composition, which may also affect the associated metabolic patterns of the insect. Earlier studies suggest that the complexity of the triatomine fecal metabolome may play a role in vector competence for different T. cruzi strains. Using high-resolution mass spectrometry and supervised machine learning, we aimed to detect differences in the intestinal metabolome of the triatomine Rhodnius prolixus and predict whether the insect had been exposed to T. cruzi or not based solely upon their metabolic profile. We were able to predict the exposure status of R. prolixus to T. cruzi with accuracies of 93.6%, 94.2% and 91.8% using logistic regression, a random forest classifier and a gradient boosting machine model, respectively. We extracted the most important features in producing the models and identified the major metabolites which assist in positive classification. This work highlights the complex interactions between triatomine vector and parasite including effects on the metabolic signature of the insect.
Trypanosoma cruzi, the causative agent of Chagas disease, colonizes the gut of triatomine insects, including Rhodnius prolixus. It is believed that this colonization upsets the microbiota that are normally present, presumably switching the environment to one more favorable for parasite survival. It was previously thought that one particular bacterium, Rhodococcus rhodnii, was essential for insect survival due to its ability to produce vital B-complex vitamins. However, these bacteria are not always identified in great abundance in studies on R. prolixus microbiota. Here we sequenced the microbiota of the insect anterior midgut using shotgun metagenomic sequencing in order to obtain a high-resolution snapshot of the microbes inside at two different time points and under two conditions; in the presence or absence of parasite and immediately following infection, or three days post-infection. We identify a total of 217 metagenomic bins, and recovered one metagenome-assembled genome, which we placed in the genus Dickeya. We show that, despite Rhodococcus being present, it is not the only microbe capable of synthesizing B-complex vitamins, with the genes required for biosynthesis present in a number of different microbes. This work helps to gain a new insight into the microbial ecology of R. prolixus.
Monte Carlo simulations and n-p differential scattering data measured with Proton Recoil Telescopes
(2020)
The neutron-induced fission cross section of 235U, a standard at thermal energy and between 0.15 MeV and 200 MeV, plays a crucial role in nuclear technology applications. The long-standing need of improving cross section data above 20 MeV and the lack of experimental data above 200 MeV motivated a new experimental campaign at the n_TOF facility at CERN. The measurement has been performed in 2018 at the experimental area 1 (EAR1), located at 185 m from the neutron-producing target (the experiment is presented by A. Manna et al. in a contribution to this conference). The 235U(n,f) cross section from 20 MeV up to about 1 GeV has been measured relative to the 1H(n,n)1H reaction, which is considered the primary reference in this energy region. The neutron flux impinging on the 235U sample (a key quantity for determining the fission events) has been obtained by detecting recoil protons originating from n-p scattering in a C2H4 sample. Two Proton Recoil Telescopes (PRT), consisting of several layers of solid-state detectors and fast plastic scintillators, have been located at proton scattering angles of 25.07° and 20.32°, out of the neutron beam. The PRTs exploit the ΔE-E technique for particle identification, a basic requirement for the rejection of charged particles from neutron-induced reactions in carbon. Extensive Monte Carlo simulations were performed to characterize proton transport through the different slabs of silicon and scintillation detectors, to optimize the experimental set-up and to deduce the efficiency of the whole PRT detector. In this work we compare measured data collected with the PRTs with a full Monte Carlo simulation based on the Geant-4 toolkit.
Bacteria of the genera Photorhabdus and Xenorhabdus produce a plethora of natural products to support their similar symbiotic lifecycles. For many of these compounds, the specific bioactivities are unknown. One common challenge in natural product research when trying to prioritize research efforts is the rediscovery of identical (or highly similar) compounds from different strains. Linking genome sequence to metabolite production can help in overcoming this problem. However, sequences are typically not available for entire collections of organisms. Here we perform a comprehensive metabolic screening using HPLC-MS data associated with a 114-strain collection (58 Photorhabdus and 56 Xenorhabdus) from across Thailand and explore the metabolic variation among the strains, matched with several abiotic factors. We utilize machine learning in order to rank the importance of individual metabolites in determining all given metadata. With this approach, we were able to prioritize metabolites in the context of natural product investigations, leading to the identification of previously unknown compounds. The top three highest-ranking features were associated with Xenorhabdus and attributed to the same chemical entity, cyclo(tetrahydroxybutyrate). This work addresses the need for prioritization in high-throughput metabolomic studies and demonstrates the viability of such an approach in future research.
A point mutation in the Ncr1 signal peptide impairs the development of innate lymphoid cell subsets
(2018)
NKp46 (CD335) is a surface receptor shared by both human and mouse natural killer (NK) cells and innate lymphoid cells (ILCs) that transduces activating signals necessary to eliminate virus-infected cells and tumors. Here, we describe a spontaneous point mutation of cysteine to arginine (C14R) in the signal peptide of the NKp46 protein in congenic Ly5.1 mice and the newly generated NCRB6C14R strain. Ly5.1C14R NK cells expressed similar levels of Ncr1 mRNA as C57BL/6, but showed impaired surface NKp46 and reduced ability to control melanoma tumors in vivo. Expression of the mutant NKp46C14R in 293T cells showed that NKp46 protein trafficking to the cell surface was compromised. Although Ly5.1C14R mice had normal number of NK cells, they showed an increased number of early maturation stage NK cells. CD49a+ILC1s were also increased but these cells lacked the expression of TRAIL. ILC3s that expressed NKp46 were not detectable and were not apparent when examined by T-bet expression. Thus, the C14R mutation reveals that NKp46 is important for NK cell and ILC differentiation, maturation and function.