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)

Response of ocean ecosystems to climate warming

Author Posting. © American Geophysical Union, 2004. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 18 (2004): GB3003, doi:10.1029/2003GB002134.We examine six different coupled climate model simulations to determine the ocean biological response to climate warming between the beginning of the industrial revolution and 2050. We use vertical velocity, maximum winter mixed layer depth, and sea ice cover to define six biomes. Climate warming leads to a contraction of the highly productive marginal sea ice biome by 42% in the Northern Hemisphere and 17% in the Southern Hemisphere, and leads to an expansion of the low productivity permanently stratified subtropical gyre biome by 4.0% in the Northern Hemisphere and 9.4% in the Southern Hemisphere. In between these, the subpolar gyre biome expands by 16% in the Northern Hemisphere and 7% in the Southern Hemisphere, and the seasonally stratified subtropical gyre contracts by 11% in both hemispheres. The low-latitude (mostly coastal) upwelling biome area changes only modestly. Vertical stratification increases, which would be expected to decrease nutrient supply everywhere, but increase the growing season length in high latitudes. We use satellite ocean color and climatological observations to develop an empirical model for predicting chlorophyll from the physical properties of the global warming simulations. Four features stand out in the response to global warming: (1) a drop in chlorophyll in the North Pacific due primarily to retreat of the marginal sea ice biome, (2) a tendency toward an increase in chlorophyll in the North Atlantic due to a complex combination of factors, (3) an increase in chlorophyll in the Southern Ocean due primarily to the retreat of and changes at the northern boundary of the marginal sea ice zone, and (4) a tendency toward a decrease in chlorophyll adjacent to the Antarctic continent due primarily to freshening within the marginal sea ice zone. We use three different primary production algorithms to estimate the response of primary production to climate warming based on our estimated chlorophyll concentrations. The three algorithms give a global increase in primary production of 0.7% at the low end to 8.1% at the high end, with very large regional differences. The main cause of both the response to warming and the variation between algorithms is the temperature sensitivity of the primary production algorithms. We also show results for the period between the industrial revolution and 2050 and 2090.J. L. Sarmiento and R. Slater were supported by the NOAA Office of Global Programs grant NA56GP0439 to the Carbon Modeling Consortium for model development and by NSF grant OCE00973166 for model and observational interpretations as part of the JGOFS Synthesis and Modeling Project. R. Barber was supported by NSF grant OCE 0136270 as part of the JGOFS Synthesis and Modeling Project. S. Doney and J. Kleypas wish to thank the Community Climate System Model science team and the Climate Simulation Laboratory at NCAR and acknowledge support from NOAA-OGP grant NOAA-NA96GP0360S. Spall is funded through the UK Department for Environment, Food and Rural Affairs contract PECD 7/12/37

Development of a new version of the Liverpool Malaria Model. II. Calibration and validation for West Africa

<p>Abstract</p> <p>Background</p> <p>In the first part of this study, an extensive literature survey led to the construction of a new version of the <it>Liverpool Malaria Model </it>(LMM). A new set of parameter settings was provided and a new development of the mathematical formulation of important processes related to the vector population was performed within the LMM. In this part of the study, so far undetermined model parameters are calibrated through the use of data from field studies. The latter are also used to validate the new LMM version, which is furthermore compared against the original LMM version.</p> <p>Methods</p> <p>For the calibration and validation of the LMM, numerous entomological and parasitological field observations were gathered for West Africa. Continuous and quality-controlled temperature and precipitation time series were constructed using intermittent raw data from 34 weather stations across West Africa. The meteorological time series served as the LMM data input. The skill of LMM simulations was tested for 830 different sets of parameter settings of the undetermined LMM parameters. The model version with the highest skill score in terms of entomological malaria variables was taken as the final setting of the new LMM version.</p> <p>Results</p> <p>Validation of the new LMM version in West Africa revealed that the simulations compare well with entomological field observations. The new version reproduces realistic transmission rates and simulated malaria seasons are comparable to field observations. Overall the new model version performs much better than the original model. The new model version enables the detection of the epidemic malaria potential at fringes of endemic areas and, more importantly, it is now applicable to the vast area of malaria endemicity in the humid African tropics.</p> <p>Conclusions</p> <p>A review of entomological and parasitological data from West Africa enabled the construction of a new LMM version. This model version represents a significant step forward in the modelling of a weather-driven malaria transmission cycle. The LMM is now more suitable for the use in malaria early warning systems as well as for malaria projections based on climate change scenarios, both in epidemic and endemic malaria areas.</p

A Multi-Host Agent-Based Model for a Zoonotic, Vector-Borne Disease. A Case Study on Trypanosomiasis in Eastern Province, Zambia

Background: This paper presents a new agent-based model (ABM) for investigating T. b. rhodesiense human African trypanosomiasis (rHAT) disease dynamics, produced to aid a greater understanding of disease transmission, and essential for development of appropriate mitigation strategies. Methods: The ABM was developed to model rHAT incidence at a fine spatial scale along a 75 km transect in the Luangwa Valley, Zambia. The method offers a complementary approach to traditional compartmentalised modelling techniques, permitting incorporation of fine scale demographic data such as ethnicity, age and gender into the simulation. Results: Through identification of possible spatial, demographic and behavioural characteristics which may have differing implications for rHAT risk in the region, the ABM produced output that could not be readily generated by other techniques. On average there were 1.99 (S.E. 0.245) human infections and 1.83 (S.E. 0.183) cattle infections per 6 month period. The model output identified that the approximate incidence rate (per 1000 person-years) was lower amongst cattle owning households (0.079, S.E. 0.017), than those without cattle (0.134, S.E. 0.017). Immigrant tribes (e.g. Bemba I.R. = 0.353, S.E.0.155) and school-age children (e.g. 5–10 year old I.R. = 0.239, S.E. 0.041) were the most at-risk for acquiring infection. These findings have the potential to aid the targeting of future mitigation strategies. Conclusion: ABMs provide an alternative way of thinking about HAT and NTDs more generally, offering a solution to the investigation of local-scale questions, and which generate results that can be easily disseminated to those affected. The ABM can be used as a tool for scenario testing at an appropriate spatial scale to allow the design of logistically feasible mitigation strategies suggested by model output. This is of particular importance where resources are limited and management strategies are often pushed to the local scale. © 2016 Alderton et al

A new vision of ocean biogeochemistry after a decade of the Joint Global Ocean Flux Study (JGOFS)

The Joint Global Ocean Flux Study (JGOFS) has completed a decade of intensive process and time-series studies on the regional and temporal dynamics of biogeochemical processes in five diverse ocean basins. Its field program also included a global survey of dissolved inorganic carbon (DIC) in the ocean, including estimates of the exchange of carbon dioxide (CO2) between the ocean and the atmosphere, in cooperation with the World Ocean Circulation Experiment (WOCE). This report describes the principal achievements of JGOFS in ocean observations, technology development and modelling. The study has produced a comprehensive and high-quality database of measurements of ocean biogeochemical properties. Data on temporal and spatial changes in primary production and CO2 exchange, the dynamics of of marine food webs, and the availability of micronutrients have yielded new insights into what governs ocean productivity, carbon cycling and export into the deep ocean, the set of processes collectively known as the "biological pump." With large-scale, high-quality data sets for the partial pressure of CO2 in surface waters as well for other DIC parameters in the ocean and trace gases in the atmosphere, reliable estimates, maps and simulations of air-sea gas flux, anthropogenic carbon and inorganic carbon export are now available. JGOFS scientists have also obtained new insights into the export flux of particulate and dissolved organic carbon (POC and DOG), the variations that occur in the ratio of elements in organic matter, and the utilization and remineralization of organic matter as it falls through the ocean interior to the sediments. JGOFS scientists have amassed long-term data on temporal variability in the exchange of CO2 between the ocean and atmosphere, ecosystem dynamics, and carbon export in the oligotrophic subtropical gyres. They have documented strong links between these variables and large-scale climate patterns such as the El Nino-Southern Oscillation (ENSO) or the North Atlantic Oscillation (NAO). An increase in the abundance of organisms that fix free nitrogen (N-2) and a shift in nutrient limitation from nitrogen to phosphorus in the subtropical North Pacific provide evidence of the effects of a decade of strong El Ninos on ecosystem structure and nutrient dynamics. High-quality data sets, including ocean-color observations from satellites, have helped modellers make great strides in their ability to simulate the biogeochemical and physical constraints on the ocean carbon cycle and to extend their results from the local to the regional and global scales. Ocean carbon-cycle models, when coupled to atmospheric and terrestrial models, will make it possible in the future to predict ways in which land and ocean ecosystems might respond to changes in climate