Elucidating Cd-mediated distinct rhizospheric and in planta ionomic and physio-biochemical responses of two contrasting Zea mays L. cultivars

Cadmium (Cd) in soil–plant system can abridge plant growth by initiating alterations in root zones. Hydroponics and rhizoboxes are useful techniques to monitor plant responses against various natural and/or induced metal stresses. However, soil based studies are considered more appropriate in order to devise efficient food safety and remediation strategies. The present research evaluated the Cd-mediated variations in elemental dynamics of rhizospheric soil together with in planta ionomics and morpho-physio-biochemical traits of two differentially Cd responsive maize cultivars. Cd-sensitive (31P41) and Cd-tolerant (3062) cultivars were grown in pots filled with 0, 20, 40, 60 and 80 µg/kg CdCl₂ supplemented soil. The results depicted that the maize cultivars significantly influenced the elemental dynamics of rhizosphere as well as in planta mineral accumulation under applied Cd stress. The uptake and translocation of N, P, K, Ca, Mg, Zn and Fe from rhizosphere and root cell sap was significantly higher in Cd stressed cv. 3062 as compared to cv. 31P41. In sensitive cultivar (31P41), Cd toxicity resulted in significantly prominent reduction of biomass, leaf area, chlorophyll, carotenoids, protein contents as well as catalase activity in comparison to tolerant one (3062). Analysis of tolerance indexes (TIs) validated that cv. 3062 exhibited advantageous growth and efficient Cd tolerance due to elevated proline, phenolics and activity of antioxidative machinery as compared to cv. 31P41. The cv. 3062 exhibited 54% and 37% less Cd bio-concentration (BCF) and translocation factors (TF), respectively in comparison to cv. 31P41 under highest Cd stress regime. Lower BCF and TF designated a higher Cd stabilization by tolerant cultivar (3062) in rhizospheric zone and its potential use in future remediation plans.     

Modelling the effect of birth and feeding modes on the development of human gut microbiota

The human gut microbiota is transmitted from mother to infant through vaginal birth and breastfeeding. Bifidobacterium, a genus that dominates the infants’ gut, is adapted to breast milk in its ability to metabolize human milk oligosaccharides; it is regarded as a mutualist owing to its involvement in the development of the immune system. The composition of microbiota, including the abundance of Bifidobacteria, is highly variable between individuals and some microbial profiles are associated with diseases. However, whether and how birth and feeding practices contribute to such variation remains unclear. To understand how early events affect the establishment of microbiota, we develop a mathematical model of two types of Bifidobacteria and a generic compartment of commensal competitors. We show how early events affect competition between mutualists and commensals and microbe-host-immune interactions to cause long-term alterations in gut microbial profiles. Bifidobacteria associated with breast milk can trigger immune responses with lasting effects on the microbial community structure. Our model shows that, in response to a change in birth environment, competition alone can produce two distinct microbial profiles post-weaning. Adding immune regulation to our competition model allows for variations in microbial profiles in response to different feeding practices. This analysis highlights the importance of microbe–microbe and microbe–host interactions in shaping the gut populations following different birth and feeding modes.     

The Bio3D packages for structural bioinformatics

Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D‐eddm package supports both experimental and theoretical simulation‐generated structures, is integrated with other methods for dissecting sequence‐structure–function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/ .     

Energy Landscapes of Protein Aggregation and Conformation Switching in Intrinsically Disordered Proteins

The protein folding problem was apparently solved recently by the advent of a deep learning method for protein structure prediction called AlphaFold. However, this program is not able to make predictions about the protein folding pathways. Moreover, it only treats about half of the human proteome, as the remaining proteins are intrinsically disordered or contain disordered regions. By definition these proteins differ from natively folded proteins and do not adopt a properly folded structure in solution. However these intrinsically disordered proteins (IDPs) also systematically differ in amino acid composition and uniquely often become folded upon binding to an interaction partner. These factors preclude solving IDP structures by current machine-learning methods like AlphaFold, which also cannot solve the protein aggregation problem, since this meta-folding process can give rise to different aggregate sizes and structures. An alternative computational method is provided by molecular dynamics simulations that already successfully explored the energy landscapes of IDP conformational switching and protein aggregation in multiple cases. These energy landscapes are very different from those of ‘simple’ protein folding, where one energy funnel leads to a unique protein structure. Instead, the energy landscapes of IDP conformational switching and protein aggregation feature a number of minima for different competing low-energy structures. In this review, I discuss the characteristics of these multifunneled energy landscapes in detail, illustrated by molecular dynamics simulations that elucidated the underlying conformational transitions and aggregation processes.     

Arginine Modulates Carbapenem Deactivation by OXA-24/40 in Acinetobacter baumannii

The resistance of Gram-negative bacteria to β-lactam antibiotics stems mainly from β-lactamase proteins that hydrolytically deactivate the β-lactams. Of particular concern are the β-lactamases that can deactivate a class of β-lactams known as carbapenems. Carbapenems are among the few anti-infectives that can treat multi-drug resistant bacterial infections. Revealing the mechanisms of their deactivation by β-lactamases is a necessary step for preserving their therapeutic value. Here, we present NMR investigations of OXA-24/40, a carbapenem-hydrolyzing Class D β-lactamase (CHDL) expressed in the gram-negative pathogen, Acinetobacter baumannii. Using rapid data acquisition methods, we were able to study the “real-time” deactivation of the carbapenem known as doripenem by OXA-24/40. Our results indicate that OXA-24/40 has two deactivation mechanisms: canonical hydrolytic cleavage, and a distinct mechanism that produces a β-lactone product that has weak affinity for the OXA-24/40 active site. The mechanisms issue from distinct active site environments poised either for hydrolysis or β-lactone formation. Mutagenesis reveals that R261, a conserved active site arginine, stabilizes the active site environment enabling β-lactone formation. Our results have implications not only for OXA-24/40, but the larger family of CHDLs now challenging clinical settings on a global scale.     

Early-phase migration dynamics of Echinococcus multilocularis in two mouse strains showing different infection susceptibilities

The early-phase migration dynamics of Echinococcus multilocularis in the intermediate hosts remain largely unknown. We compared the parasite burden in the intestine, liver and faeces of DBA/2 and C57BL/6 mouse strains using parasite-specific quantitative PCR. Our results indicated that the parasites invaded mainly from the middle segments of the small intestine and completed migration to the liver within 24 h p.i. C57BL/6 mice had lower parasite DNA burdens in the intestine and liver but higher in the faeces than DBA/2 mice, suggesting that parasite invasion of the intestine may be a critical stage regulating susceptibility to E. multilocularis infection in mice.     

Modeling Cumulative Effects of Climate and Development on Moose,Wolf, and Caribou Populations

Wildlife models focused solely on a single strong influence (e.g., habitat components, wildlife harvest) are limited in their ability to detect key mechanisms influencing population change. Instead, we propose integrated modeling in the context of cumulative effects assessment using multispecies population dynamics models linked to landscape-climate simulation at large spatial and temporal scales. We developed an integrated landscape and population simulation model using ALCES Online as the model-building platform, and the model accounted for key ecological components and relationships among moose (Alces alces), grey wolves (Canis lupus nubilus), and woodland caribou (Rangifer tarandus caribou) in northern Ontario, Canada. We simulated multiple scenarios over 5 decades (beginning 2020) to explore sensitivity to climate change and land use and assessed effects at multiple scales. The magnitude of effect and the relative importance of key factors (climate change, roads, and habitat) differed depending on the scale of assessment. Across the full extent of the study area (654,311km² [ecozonal scale]), the caribou population declined by 26% largely because of climate change and associated predator-prey response, which led to caribou range recession in the southern part of the study area. At the caribou range scale (108,378 km²), which focused on 2 herds in the northern part of the study area, climate change led to a 10% decline in the population and development led to an additional 7% decline. At the project scale (8,331 km²), which was focused more narrowly on the landscape surrounding 4 proposed mines, the caribou population declined by 29% largely in response to simulated development. Given that observed caribou population dynamics were sensitive to the cumulative effects of climate change, land use, interspecific interactions, and scale, insights from the analysis might not emerge under a less complex model. Our integrated modeling framework provides valuable support for broader regional assessments, including estimation of risk to caribou and Indigenous food security, and for developing and evaluating potential caribou recovery strategies. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.     

Identifying conversion efficiency as a key mechanism underlying food webs adaptive evolution: a step forward,or backward?

Body size or mass is one of the main factors underlying food webs structure. A large number of evolutionary models have shown that indeed, the adaptive evolution of body size (or mass) can give rise to hierarchically organised trophic levels with complex between and within trophic interactions. However, these models generally make strong arbitrary assumptions on how traits evolve, casting doubts on their robustness. In particular, biomass conversion efficiency is always considered independent of the predator and prey size, which contradicts with the literature. In this paper, we propose a general model encompassing most previous models which allows to show that relaxing arbitrary assumptions gives rise to unrealistic food webs. We then show that considering biomass conversion efficiency dependent on species size is certainly key for food webs adaptive evolution because realistic food webs can evolve, making obsolete the need of arbitrary constraints on traits' evolution. We finally conclude that, on the one hand, ecologists should pay attention to how biomass flows into food webs in models. On the other hand, we question more generally the robustness of evolutionary models for the study of food webs.     

Temperature and multiple parasites combine to alter host community structure

Predicting the effects of climate change requires understanding complex interactions among multiple abiotic and biotic factors. By influencing key interactions among host species, parasites can affect community and ecosystem structuring. Yet, our understanding of how multiple parasites and abiotic factors interact to alter ecosystem structure remains limited. To empirically test the role of temperature variation and parasites in shaping communities, we used a multigenerational mesocosm experiment composed of four sympatric freshwater crustacean species (isopods and amphipods) that share up to four parasite species. Mesocosms were assigned to one of four different treatments with contrasting seasonal temperatures (normal and elevated) and parasite exposure levels (continuous and arrested (presence or absence of parasite larvae in mesocosm)). We found that parasite exposure and water temperature had interactive effects on the host community. Continuous exposure to parasites altered the community structure and differences in water temperature altered species abundance. The abundance of the amphipod Paracalliope fluviatilis decreased substantially when experiencing continuous parasite exposure and elevated water temperatures. Elevated temperatures also led to parasite-induced mortality in another amphipod host, Paracorophium excavatum. Contrastingly, isopod hosts were affected much less, suggesting increasing temperatures in conjunction with higher parasite exposure might increase their relative abundance in the community. Changes in invertebrate host populations have implications for other species such as fish and birds that consume crustaceans as well as having impacts on ecosystem processes, such as aquatic primary production and nutrient cycling. In light of climate change predictions, parasite exposure and rise in average temperatures may have substantial impacts on communities and ecosystems, altering ecosystem structure and dynamics.