Predicting soil carbon changes in switchgrass grown on marginal lands under climate change and adaptation strategies

The United States Great Lakes Region (USGLR) is a critical geographic area for future bioenergy production. Switchgrass (Panicum virgatum) is widely considered a carbon (C)‐neutral or C‐negative bioenergy production system, but projected increases in air temperature and precipitation due to climate change might substantially alter soil organic C (SOC) dynamics and storage in soils. This study examined long‐term SOC changes in switchgrass grown on marginal land in the USGLR under current and projected climate, predicted using a process‐based model (Systems Approach to Land‐Use Sustainability) extensively calibrated with a wealth of plant and soil measurements at nine experimental sites. Simulations indicate that these soils are likely a net C sink under switchgrass (average gain 0.87 Mg C ha^?1 year^?1), although substantial variation in the rate of SOC accumulation was predicted (range: 0.2–1.3 Mg C ha^?1 year^?1). Principal component analysis revealed that the predicted intersite variability in SOC sequestration was related in part to differences in climatic characteristics, and to a lesser extent, to heterogeneous soils. Although climate change impacts on switchgrass plant growth were predicted to be small (4%–6% decrease on average), the increased soil respiration was predicted to partially negate SOC accumulations down to 70% below historical rates in the most extreme scenarios. Increasing N fertilizer rate and decreasing harvest intensity both had modest SOC sequestration benefits under projected climate, whereas introducing genotypes better adapted to the longer growing seasons was a much more effective strategy. Best‐performing adaptation scenarios were able to offset >60% of the climate change impacts, leading to SOC sequestration 0.7 Mg C ha^?1 year^?1 under projected climate. On average, this was 0.3 Mg C ha^?1 year^?1 more C sequestered than the no adaptation baseline. These findings provide crucial knowledge needed to guide policy and operational management for maximizing SOC sequestration of future bioenergy production on marginal lands in the USGLR.     

Postglacial recolonization of North America by spadefoot toads: integrating niche and corridor modeling to study species’ range dynamics over geologic time

Understanding the factors that shape species’ distributions is a key topic in biogeography. As climates change, species can either cope with these changes through evolution, plasticity or by shifting their ranges to track the optimal climatic conditions. Ecological niche modeling (ENM) is a widespread technique in biogeography that estimates the niche of the organism by using occurrences and environmental data to estimate species’ potential distributions. ENMs are often criticized for failing to take species’ dispersal abilities into consideration. Here, we attempt to fill this gap by combining ENMs with dispersal and corridor modeling to study the range dynamics of North American spadefoot toads (Scaphiopodidae) over the Holocene. We first estimated the current and past distributions of spadefoot toads and then estimated their past distributions from the Last Glacial Maximum (LGM) to the present day. Then, we estimated how each taxon recolonized North American by using dispersal and corridor modeling. By combining these two modeling approaches we were able to 1) estimate the LGM refugia used by the North American spadefoot toads, 2) further refine these projections by estimating which of the putative LGM refugia contributed to the recolonization of North America via dispersal, and 3) estimate the relative influence of each LGM refugium to the current species’ distributions. The models were tested using previously published phylogeographic data, revealing a high degree of congruence between our models and the genetic data. These results suggest that combining ENMs and dispersal modeling over time is a promising approach to investigate both historical and future species’ range dynamics.     

Incorporating intraspecific variation into species distribution models improves distribution predictions,but cannot predict species traits for a wide-spread plant species

The most common approach to predicting how species ranges and ecological functions will shift with climate change is to construct correlative species distribution models (SDMs). These models use a species’ climatic distribution to determine currently suitable areas for the species and project its potential distribution under future climate scenarios. A core, rarely tested, assumption of SDMs is that all populations will respond equivalently to climate. Few studies have examined this assumption, and those that have rarely dissect the reasons for intraspecific differences. Focusing on the arctic-alpine cushion plant Silene acaulis, we compared predictive accuracy from SDMs constructed using the species’ full global distribution with composite predictions from separate SDMs constructed using subpopulations defined either by genetic or habitat differences. This is one of the first studies to compare multiple ways of constructing intraspecific-level SDMs with a species-level SDM. We also examine the contested relationship between relative probability of occurrence and species performance or ecological function, testing if SDM output can predict individual performance (plant size) and biotic interactions (facilitation). We found that both genetic- and habitat-informed SDMs are considerably more accurate than a species-level SDM, and that the genetic model substantially differs from and outperforms the habitat model. While SDMs have been used to infer population performance and possibly even biotic interactions, in our system these relationships were extremely weak. Our results indicate that individual subpopulations may respond differently to climate, although we discuss and explore several alternative explanations for the superior performance of intraspecific-level SDMs. We emphasize the need to carefully examine how to best define intraspecific-level SDMs as well as how potential genetic, environmental, or sampling variation within species ranges can critically affect SDM predictions. We urge caution in inferring population performance or biotic interactions from SDM predictions, as these often-assumed relationships are not supported in our study.     

Incorporating physiology into species distribution models moderates the projected impact of warming on selected Mediterranean marine species

Species distribution models (SDMs) correlate species occurrences with environmental predictors, and can be used to forecast distributions under future climates. SDMs have been criticized for not explicitly including the physiological processes underlying the species response to the environment. Recently, new methods have been suggested to combine SDMs with physiological estimates of performance (physiology-SDMs). In this study, we compare SDM and physiology-SDM predictions for select marine species in the Mediterranean Sea, a region subjected to exceptionally rapid climate change. We focused on six species and created physiology-SDMs that incorporate physiological thermal performance curves from experimental data with species occurrence records. We then contrasted projections of SDMs and physiology-SDMs under future climate (year 2100) for the entire Mediterranean Sea, and particularly the ‘warm’ trailing edge in the Levant region. Across the Mediterranean, we found cross-validation model performance to be similar for regular SDMs and physiology-SDMs. However, we also show that for around half the species the physiology-SDMs substantially outperform regular SDM in the warm Levant. Moreover, for all species the uncertainty associated with the coefficients estimated from the physiology-SDMs were much lower than in the regular SDMs. Under future climate, we find that both SDMs and physiology-SDMs showed similar patterns, with species predicted to shift their distribution north-west in accordance with warming sea temperatures. However, for the physiology-SDMs predicted distributional changes are more moderate than those predicted by regular SDMs. We conclude, that while physiology-SDM predictions generally agree with the regular SDMs, incorporation of the physiological data led to less extreme range shift forecasts. The results suggest that climate-induced range shifts may be less drastic than previously predicted, and thus most species are unlikely to completely disappear with warming climate. Taken together, the findings emphasize that physiological experimental data can provide valuable supplemental information to predict range shifts of marine species.     

Circadian clock effects on cellular proliferation: Insights from theory and experiments

Oscillations of the cellular circadian clock have emerged as an important regulator of many physiological processes, both in health and in disease. One such process, cellular proliferation, is being increasingly recognized to be affected by the circadian clock. Here, we review how a combination of experimental and theoretical work has furthered our understanding of the way circadian clocks couple to the cell cycle and play a role in tissue homeostasis and cancer. Finally, we discuss recently introduced methods for modeling coupling of clocks based on techniques from survival analysis and machine learning and highlight their potential importance for future studies.     

Discovery of a potent and selective adenylyl cyclase type 8 agonist by docking-based virtual screening

Adenylyl cyclases (ACs), which are responsible for catalyzing the conversion of adenosine triphosphate (ATP) into the second messenger cyclic adenosine monophosphate (cAMP), play a critical role in cell signal transduction. In this study, a combined approach involving docking-based virtual screening, with the combination of homology modeling followed by an in-vitro, and cell-based biological assay have been performed for discovering a class of novel potent and selective isoform adenylyl cyclase type 8 (AC8) agonist. The computer-aided virtual screening was used to identify fourteen virtual cluster compounds as potential hits which were further subjected to rigorous bioassays. A novel hit compound VHC-7 (ethyl 3-(2,4-dichlorobenzyl)-2-oxoindoline-3-carboxylate) was identified as a highly potent selective AC8 agonist with EC₅₀ value of 0.1052 ± 0.038 µM. Remarkably, the molecule herein reported can be explored further to discover greater number of hit compounds with better pharmacokinetic properties as well as to serve as a promising novel hit agonist of AC8 for the treatment of various central nervous system disorders and its associated diseases.     

Mdm2 inhibitors as a platform for the design of P-glycoprotein inhibitors

Chemoresistance is thought to be the cause of low treatment efficacy and mortality in more than 90% of patients with advanced cancer. The activation of drug efflux by P-glycoprotein is the key mechanism of resistance. All known P-gp inhibitors are used only in the combination therapy. We propose a new approach based on the multitarget rational design of drugs, which possess both the antitumor and efflux pump inhibitory activity. In this work, the principle possibility of combining the ability to inhibit P-gp and p53-Mdm2 protein-protein interaction in one structure is considered. The biological activity of a number of known and newly synthesized compounds was evaluated using cell lines with different p53 status. The possibility of using computer modeling for the search for P-glycoprotein inhibitors among Mdm2 inhibitors was analyzed; P-gp interaction site and binding modes of substrates and inhibitors were identified. The results obtained in cells that have the native balance of drug resistance and sensitivity showed the ability of the cells to both actively throw out xenobiotics and to lose this ability using P-gp inhibitors. The data obtained indicate that Mdm2 inhibitors are a promising platform for the development of multitarget drugs that can overcome tumor resistance by inhibiting the P-glycoprotein activity.     

Integrative structure and function of the yeast exocyst complex

Exocyst is an evolutionarily conserved hetero‐octameric tethering complex that plays a variety of roles in membrane trafficking, including exocytosis, endocytosis, autophagy, cell polarization, cytokinesis, pathogen invasion, and metastasis. Exocyst serves as a platform for interactions between the Rab, Rho, and Ral small GTPases, SNARE proteins, and Sec1/Munc18 regulators that coordinate spatial and temporal fidelity of membrane fusion. However, its mechanism is poorly described at the molecular level. Here, we determine the molecular architecture of the yeast exocyst complex by an integrative approach, based on a 3D density map from negative‐stain electron microscopy (EM) at ~16 Å resolution, 434 disuccinimidyl suberate and 1‐ethyl‐3‐(3‐dimethylaminopropyl)carbodiimide hydrochloride cross‐links from chemical‐crosslinking mass spectrometry, and partial atomic models of the eight subunits. The integrative structure is validated by a previously determined cryo‐EM structure, cross‐links, and distances from in vivo fluorescence microscopy. Our subunit configuration is consistent with the cryo‐EM structure, except for Sec5. While not observed in the cryo‐EM map, the integrative model localizes the N‐terminal half of Sec3 near the Sec6 subunit. Limited proteolysis experiments suggest that the conformation of Exo70 is dynamic, which may have functional implications for SNARE and membrane interactions. This study illustrates how integrative modeling based on varied low‐resolution structural data can inform biologically relevant hypotheses, even in the absence of high‐resolution data.     

Flexible docking of peptides to proteins using CABS‐dock

Molecular docking of peptides to proteins can be a useful tool in the exploration of the possible peptide binding sites and poses. CABS‐dock is a method for protein–peptide docking that features significant conformational flexibility of both the peptide and the protein molecules during the peptide search for a binding site. The CABS‐dock has been made available as a web server and a standalone package. The web server is an easy to use tool with a simple web interface. The standalone package is a command‐line program dedicated to professional users. It offers a number of advanced features, analysis tools and support for large‐sized systems. In this article, we outline the current status of the CABS‐dock method, its recent developments, applications, and challenges ahead.     

枯草芽孢杆菌表达与调控工具相关研究进展

枯草芽孢杆菌作为革兰氏阳性模式微生物,由于其清晰的遗传背景、高效的分泌能力以及简单的培养条件等优势被广泛的应用于生物技术产业。近年来,随着代谢工程与合成生物学的发展,枯草芽孢杆菌相关表达系统与调控工具研究也取得了很大进展。围绕枯草芽孢杆菌动态调控工具的研究进展,分别从转录水平调控和转录后水平调控两个层面上进行综述,并对调控元件在生物技术中的应用进行了讨论。最后,对未来枯草芽孢杆菌表达与调控工具的发展进行了展望。