Fungus under a Changing Climate: Modeling the Current and Future Global Distribution of Fusarium oxysporum Using Geographical Information System Data

Impact of climate change on the potential global prevalence of Macrophomina phaseolina (Tassi) Goid. under several climatological scenarios

Introduction

Climate change forms one of the most dangerous problems that disturb the earth today. It not only devastates the environment but also affects the biodiversity of living organisms, including fungi. Macrophomina phaseolina (Tassi) Goid. is one of the most pervasive and destructive soil-borne fungus that threatens food security, so predicting its current and future distribution will aid in following its emergence in new regions and taking precautionary measures to control it.

Methods

Throughout this work, there are about 324 records of M. phaseolina were used to model its global prevalence using 19 environmental covariates under several climate change scenarios for analysis. Maximum Entropy (MaxEnt) model was used to predict the spatial distribution of this fungus throughout the world while algorithms of DIVA-GIS were chosen to confirm the predicted model.

Results

Based on the Jackknife test, minimum temperature of coldest month (bio_6) represented the most effective bioclimatological parameter to fungus distribution with a 52.5% contribution. Two representative concentration pathways (RCPs) 2.6 and 8.5 of global climate model (GCM) code MG, were used to forecast the global spreading of the fungus in 2050 and 2070. The area under curve (AUC) and true skill statistics (TSS) were assigned to evaluate the resulted models with values equal to 0.902 ± 0.009 and 0.8, respectively. These values indicated a satisfactory significant correlation between the models and the ecology of the fungus. Two-dimensional niche analysis illustrated that the fungus could adapt to a wide range of temperatures (9 °C to 28 °C), and its annual rainfall ranges from 0 mm to 2000 mm. In the future, Africa will become the low habitat suitability for the fungus while Europe will become a good place for its distribution.

Discussion

The MaxEnt model is potentially useful for predicting the future distribution of M. phaseolina under changing climate, but the results need further intensive evaluation including more ecological parameters other than bioclimatological data.

Evaluation of ecological consequences on the global distribution of Staphylococcus aureus Rosenbach 1884 due to climate change, using Maxent modeling

Staphylococcus aureus is a primary cause of many infections in humans, and its rising prevalence and drug resistance are serious public health concerns. While there is evidence that climate change can influence the distribution and abundance of microbial species, the precise effects on S. aureus are not well characterized. The purpose of this study is to predict the potential influence of climate change on the global distribution of Staphylococcus aureus in 2050 and 2070 using GIS and Maxent modeling. S. aureus occurrence data was acquired from global databases and coupled with bioclimatic variables to simulate current and future habitat suitability under several climate change scenarios (RCP 2.6 and 8.5). The Maxent modeling approach was used to forecast geographical patterns of S. aureus distribution, providing insights into locations that may see increased prevalence of this essential species as a result of climate change. The study's findings can be used to inform public health measures and focused surveillance activities aimed at reducing the burden of Staphylococcus aureus infection.

Elevating fungal care: bridging Brazil's healthcare practices to global standards

Brazil faces unique challenges in managing invasive fungal infections (IFIs) due to diverse ecosystems, a rural workforce, and prevalent health conditions. In Europe, IFIs are primarily associated with transplantation, intensive care, and chronic diseases. Inspired by initiatives in the Caribbean and Latin America in 2019, efforts to map global diagnostic and treatment resources expanded to Africa, Europe, and Asia/Pacific. This study conducts a comparative analysis, mainly drawing data from Brazil and Europe, to investigate IFI epidemiology and management. Data were collected through online surveys distributed to Brazilian and European institutions, with collaborations from scientific organizations. Surveys covered institutional profiles, IFI diagnoses, accessibility to diagnostic techniques, and antifungal drugs. A comparative survey involving 96 Brazilian and 388 European institutions revealed variations in the perception and practices related to fungal pathogens. Differences in ranking and prevalence were observed, along with variations in diagnostic procedures, fluorescence dye usage, culture practices, antifungal medication availability, and technological approaches. Europe exhibited higher utilization rates for molecular diagnostic approaches, including PCR tests, and therapeutic drug monitoring (TDM) was more widespread in Europe compared with Brazil, indicating substantial differences in understanding and managing fungal infections. Customized IFI management is crucial, considering regional differences and addressing technological gaps like underutilized PCR. The study advocates for increased international collaboration, targeted training, and enhanced resources to foster a unified global approach in preventing, diagnosing, and treating IFI.

IMPORTANCE

This work is significant as it highlights the unique challenges Brazil faces in managing invasive fungal infections (IFIs) due to its diverse ecosystems and public health landscape. By comparing Brazil's situation with Europe-where IFIs are mainly linked to transplantation and intensive care-this study identifies key disparities in diagnostic and treatment practices. The findings reveal substantial differences in the availability and use of molecular diagnostics, antifungal drugs, and therapeutic drug monitoring, with Europe demonstrating more advanced practices. By mapping these variations, the study underscores the importance of tailored approaches to IFI management that consider regional differences and technological gaps. Ultimately, it calls for enhanced international collaboration, targeted training, and resource allocation to improve IFI outcomes globally, particularly in regions with limited access to advanced diagnostic tools and treatments.

Computational and In silico study of novel fungicides against combating root rot, gray mold, fusarium wilt, and cereal rust

The exploration of potential candidates for fungicides against four fungal proteins that cause some vital plant diseases, namely Phytophthora capsici, Botrytis cinerea, Fusarium oxysporum f. sp. lycopersici, and Puccinia graminis f. sp. tritici, was conducted using in silico, molecular docking simulations, and molecular dynamic (MD) simulation for selecting the nature of binding affinity with actives sites of proteins. First of all, the DFT was employed to optimize the molecular geometry, and get the prepared optimized ligand. From the DFT data, the chemical descriptors were calculated. Next, two docking tools, such as AutoDock by PyRx and Molecular Docking by Glide from the Schrödinger suite, were used to convey the docking score, and ligand protein interactions against four main proteases, for instance 7VEM, 8H6Q, 8EBB, and 7XDS having name of pathogens: Phytophthora capsici, Botrytis cinerea, Fusarium oxysporum f. sp. lycopersici, and Puccinia graminis f. sp. tritici, respectively. In case of auto dock from PyRx, the fungicides L01, L03, L04, L13, L14, L17, L18, and L19 demonstrated significantly higher affinities for binding to the four fungal pathogens. Surprisingly, it is conveyed that the L03 illustrated the highest binding score against three of 7VEM, 8EBB, and 7XDS proteins and L09 is highest for 8H6Q. However, MD was performed to check the validation and calculation the docking procedure and stability of the protein ligand docked complex accounting of RMSD, RMSF, SASA, Radius of gyration (Rg), Protein secondary structure elements (SSE), Ramachandran plot which confirm that the stability of docked complex is so high, and number of calculating the hydrogen bonds is more than good enough, as a result it is concluded the docking procedure is valid. Finally, Difenoconazole (L03) has been considered as the most promising antifungal drug evaluated from the studies.

Using MaxEnt modeling to analyze climate change impacts on Pseudomonas syringae van Hall, 1904 distribution on the global scale

Pseudomonas syringae is a pathogenic bacterium that poses a significant threat to global agriculture, necessitating a deeper understanding of its ecological dynamics in the context of global warming. This study investigates the current and projected future distribution of P. syringae, focusing on the climatic factors that influence its spread. To achieve this, we employed Maximum Entropy (MaxEnt) modeling based on Geographic Information Systems (GIS) to analyze species occurrence records alongside relevant climate data. The MaxEnt model was calibrated using 75 % of the occurrence data, with the remaining 25 % reserved for validation. The model's performance was meticulously assessed utilizing the area under the curve (AUC) and true skill statistics (TSS), resulting in an AUC score of 0.92, indicating excellent predictive capability. Our analysis identified key climatic parameters-temperature, precipitation, and humidity-that significantly affect the presence of P. syringae. Notably, our findings project an expansion of the bacterium's geographic range in the coming decades, with optimal conditions shifting toward the poles. This research underscores the significant influence of climate change on the distribution of P. syringae and provides valuable insights for developing targeted disease management strategies. The anticipated increase in bacterial infections in crops highlights the urgent need for proactive measures to mitigate these effects.

Global patterns of species diversity and distribution in the biomedically and biotechnologically important fungal genus Aspergillus

Aspergillus fungi are key producers of pharmaceuticals, enzymes, and food products and exhibit diverse lifestyles, ranging from saprophytes to opportunistic pathogens. To improve understanding of Aspergillus species diversity, identify key environmental factors influencing their geographic distributions, and estimate the impact of future climate change, we trained a random forest machine learning classifier on 30,542 terrestrial occurrence records for 176 species (~40% of known species in the genus) and 96 environmental variables. We found that regions with high species diversity are concentrated in temperate forests, which suggests that areas with mild seasonal variation may serve as diversity hotspots. Species range estimates revealed extensive variability, both within and across taxonomic sections; while some species are cosmopolitan, others have more restricted ranges. Furthermore, range overlap between species is generally low. The top predictors of mean species richness were the index of cumulative human impact and five bioclimatic factors, such as temperature and temperate vs non-temperate ecoregions. Our future climate analyses revealed considerable variation in species range estimates in response to changing climates; some species ranges are predicted to expand (e.g., the food spoilage and mycotoxin-producing Aspergillus versicolor), and others are predicted to contract or remain stable. Notably, the predicted range of the major pathogen Aspergillus fumigatus was predicted to decrease in response to climate change, whereas the range of the major pathogen Aspergillus flavus was predicted to increase and gradually decrease. Our findings reveal how both natural and human factors influence Aspergillus species ranges and highlight their ecological diversity, including the diversity of their responses to changing climates, which is of relevance to pathogen and mycotoxin risk assessment.

Modeling climate-related global risk maps of rice bacterial blight caused by Xanthomonas oryzae (Ishiyama 1922) using geographical information system (GIS)

Rice is a critical staple crop that feeds more than half of the world's population. Still, its production confronts various biotic risks, notably the severe bacterial blight disease produced by Xanthomonas oryzae. Understanding the possible effects of climate change on the geographic distribution of this virus is critical to ensuring food security. This work used ecological niche modeling and the Maxent algorithm to create future risk maps for the range of X. oryzae under several climate change scenarios between 2050 and 2070. The model was trained using 93 occurrence records of X. oryzae and five critical bioclimatic variables. It has an excellent predictive performance, with an AUC of 0.889. The results show that X. oryzae's potential geographic range and habitat suitability are expected to increase significantly under low (RCP2.6) and high (RCP8.5) emission scenarios. Key climatic drivers allowing this development include increased yearly precipitation, precipitation during the wettest quarter, and the wettest quarter's mean temperature. These findings are consistent with broader research revealing that climate change is allowing many plant diseases and other dangerous microbes to spread across the globe. Integrating these spatial predictions with data on host susceptibility, agricultural practices, and socioeconomic vulnerabilities can help to improve targeted surveillance, preventative, and management methods for reducing the growing threat of bacterial blight to rice production. Proactive, multidisciplinary efforts to manage the changing disease dynamics caused by climate change will be critical to assuring global food security in the future decades.

Incorporating Implicit Information to Disentangle the Impacts of Hydropower Dams and Climate Change on Basin-Scale Fish Habitat Distribution

The loss of freshwater fish habitats, exacerbated by climate change and dam constructions, poses a critical environmental concern. The upper Yangtze River basin, noted for its abundant fish fauna and concentrated dam development, serves as a crucial locale for investigating the impacts of climate shifts and dam construction. This study aims to disentangle the impacts of hydroelectric dams and climate change on fish habitat distribution by analyzing species presence data across different periods. Species distribution models were constructed using Maxent for Coreius guichenoti (a warm-water endangered fish) and Schizopygopsis malacanthus (a cold-water endangered fish). The model accuracy was assessed using the area under the curve of the receiver operating characteristic. Habitat distribution modeling and prediction for the pre-dam period (1970-2000) and post-dam period (2001-2020), as well as future climate change under two shared socioeconomic pathways scenarios, were conducted. The impacts of climate change and dam construction on the habitat suitability of two fish species were quantified. The results revealed dam construction predominantly diminished habitat suitability and range, with high-suitability habitats in the post-dam period decreasing by 56.3% (720.18 km) and 67.0% (1665.52 km) for the two fishes, respectively. Climate change would enhance the habitat suitability of Coreius guichenoti, while it would decrease the habitat suitability of Schizopygopsis malacanthus. The impact of dam construction is greater that of climate change for them. This study underscores the profound impacts of dam construction on fish habitats, particularly for cold-water species, and highlights the critical need for habitat restoration in sustainable hydropower development. Our method of disentangling these factors also provides a new approach to evaluating environmental impacts in large river basins.

Global climate change-driven impacts on the Asian distribution of Limassolla leafhoppers, with implications for biological and environmental conservation

Knowing the impacts of global climate change on the habitat suitability distribution of Limassolla leafhoppers contributes to understanding the feedback of organisms on climate change from a macroecological perspective, and provides important scientific basis for protecting the ecological environment and biodiversity. However, there is limited knowledge on this aspect. Thus, our study aimed to address this gap by analyzing Asian habitat suitability and centroid shifts of Limassolla based on 19 bioclimatic variables and occurrence records. Selecting five ecological niche models with the outstanding predictive performance (Maxlike, generalized linear model, generalized additive model, random forest, and maximum entropy) along with their ensemble model from 12 models, the current habitat suitability of Limassolla and its future habitat suitability under two Shared Socio-economic Pathways (SSP1-2.6 and SSP5-8.5) in the 2050s and 2090s were predicted. The results showed that the prediction results of the five models are generally consistent. Based on ensemble model, 11 potential biodiversity hotspots with high suitability were identified. With climate change, the suitable range of Limassolla will experience both expansion and contraction. In SSP5-8.52050s, the expansion area is 118.56 × 104 km2, while the contraction area is 25.40 × 104 km2; in SSP1-2.62090s, the expansion area is 91.71 × 104 km2, and the contraction area is 26.54 × 104 km2. Furthermore, the distribution core of Limassolla will shift toward higher latitudes in the northeast direction, and the precipitation of warmest quarter was found to have the greatest impact on the distribution of Limassolla. Our research results supported our four hypotheses. Finally, this research suggests establishing ecological reserves in identified contraction to prevent habitat loss, enhancing the protection of biodiversity hotspots, and pursuing a sustainable development path with reduced emissions.

On the way to potential antifungal compounds: synthesis and in vitro activity of 2-benzofuranylacetic acid amides

Crop losses caused by microbial infections are a significant global issue, especially in tropical regions. The development of novel antimicrobial agents, particularly antifungal agents, has been explored from various perspectives, including chemical synthesis. However, conventional approaches typically involve synthesizing new and potent compounds on a small scale (a few milligrams), making the scale-up of the reaction a major challenge. In this manuscript, we present a method for the synthesis of new and active (against Fusarium oxysporum) benzofuranyl acetic acid amides. Our strategy allows us to synthesize the key precursor on the gram scale, enabling the production of sufficient quantities of other active compounds within short timeframes for conducting biological studies. All the reactions used in this manuscript are recognized by their industrial application.

Biogeography of Fungal Communities Associated with Pinus sylvestris L. and Picea abies (L.) H. Karst. along the Latitudinal Gradient in Europe

We assessed the diversity and composition of fungal communities in different functional tissues and the rhizosphere soil of Pinus sylvestris and Picea abies stands along the latitudinal gradient of these tree species distributions in Europe to model possible changes in fungal communities imposed by climate change. For each tree species, living needles, shoots, roots, and the rhizosphere soil were sampled and subjected to high-throughput sequencing. Results showed that the latitude and the host tree species had a limited effect on the diversity and composition of fungal communities, which were largely explained by the environmental variables of each site and the substrate they colonize. The mean annual temperature and mean annual precipitation had a strong effect on root fungal communities, isothermality on needle fungal communities, mean temperature of the warmest quarter and precipitation of the driest month on shoot fungal communities, and precipitation seasonality on soil fungal communities. Fungal communities of both tree species are predicted to shift to habitats with a lower annual temperature amplitude and with increasing precipitation during the driest month, but the suitability of these habitats as compared to the present conditions is predicted to decrease in the future.

Prediction of Suitable Habitat Distribution of Cryptosphaeria pullmanensis in the World and China under Climate Change

Years of outbreaks of woody canker (Cryptosphaeria pullmanensis) in the United States, Iran, and China have resulted in massive economic losses to biological forests and fruit trees. However, only limited information is available on their distribution, and their habitat requirements have not been well evaluated due to a lack of research. In recent years, scientists have utilized the MaxEnt model to estimate the effect of global temperature and specific environmental conditions on species distribution. Using occurrence and high resolution ecological data, we predicted the spatiotemporal distribution of C. pullmanensis under twelve climate change scenarios by applying the MaxEnt model. We identified climatic factors, geography, soil, and land cover that shape their distribution range and determined shifts in their habitat range. Then, we measured the suitable habitat area, the ratio of change in the area of suitable habitat, the expansion and shrinkage of maps under climate change, the direction and distance of range changes from the present to the end of the twenty-first century, and the effect of environmental variables. C. pullmanensis is mostly widespread in high-suitability regions in northwestern China, the majority of Iran, Afghanistan, and Turkey, northern Chile, southwestern Argentina, and the west coast of California in the United States. Under future climatic conditions, climate changes of varied intensities favored the expansion of suitable habitats for C. pullmanensis in China. However, appropriate land areas are diminishing globally. The trend in migration is toward latitudes and elevations that are higher. The estimated area of possible suitability shifted eastward in China. The results of the present study are valuable not only for countries such as Morocco, Spain, Chile, Turkey, Kazakhstan, etc., where the infection has not yet fully spread or been established, but also for nations where the species has been discovered. Authorities should take steps to reduce greenhouse gas emissions in order to restrict the spread of C. pullmanensis. Countries with highly appropriate locations should increase their surveillance, risk assessment, and response capabilities.