Perspectives on label-free microscopy of heterogeneous and dynamic biological systems.

Significance: Advancements in label-free microscopy could provide real-time, non-invasive imaging with unique sources of contrast and automated standardized analysis to characterize heterogeneous and dynamic biological processes. These tools would overcome challenges with widely used methods that are destructive (e.g., histology, flow cytometry) or lack cellular resolution (e.g., plate-based assays, whole animal bioluminescence imaging). Aim: This perspective aims to (1) justify the need for label-free microscopy to track heterogeneous cellular functions over time and space within unperturbed systems and (2) recommend improvements regarding instrumentation, image analysis, and image interpretation to address these needs. Approach: Three key research areas (cancer research, autoimmune disease, and tissue and cell engineering) are considered to support the need for label-free microscopy to characterize heterogeneity and dynamics within biological systems. Based on the strengths (e.g., multiple sources of molecular contrast, non-invasive monitoring) and weaknesses (e.g., imaging depth, image interpretation) of several label-free microscopy modalities, improvements for future imaging systems are recommended. Conclusion: Improvements in instrumentation including strategies that increase resolution and imaging speed, standardization and centralization of image analysis tools, and robust data validation and interpretation will expand the applications of label-free microscopy to study heterogeneous and dynamic biological systems.

New insights into the role of mitochondrial dynamics in oxidative stress-induced diseases.

The accumulation of excess reactive oxygen species (ROS) can lead to oxidative stress (OS), which can induce gene mutations, protein denaturation, and lipid peroxidation directly or indirectly. The expression is reduced ATP level in cells, increased cytoplasmic Ca2+, inflammation, and so on. Consequently, ROS are recognized as significant risk factors for human aging and various diseases, including diabetes, cardiovascular diseases, and neurodegenerative diseases. Mitochondria are involved in the production of ROS through the respiratory chain. Abnormal mitochondrial characteristics, including mitochondrial OS, mitochondrial fission, mitochondrial fusion, and mitophagy, play an important role in various tissues. However, previous excellent reviews focused on OS-induced diseases. In this review, we focus on the latest progress of OS-induced mitochondrial dynamics, discuss OS-induced mitochondrial damage-related diseases, and summarize the OS-induced mitochondrial dynamics-related signaling pathways. Additionally, it elaborates on potential therapeutic methods aimed at preventing oxidative stress from further exacerbating mitochondrial disorders.

Mining and characterization of novel antimicrobial peptides from the large-scale microbiome of Shanxi aged vinegar based on metagenomics, molecular dynamics simulations and mechanism validation.

The study aimed to mine and characterize novel antimicrobial peptides (AMPs) from the Shanxi aged vinegar microbiome. Utilizing machine learning techniques, AlphaFold2 structure prediction and molecular dynamics simulations, six novel AMPs were innovatively mined from 98,539 peptides based on metagenomic data, of which one peptide secreted by Lactobacillus (named La-AMP) was experimentally validated to have remarkable bactericidal effects against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) with high stability and no hemolytic activity. Scanning electron microscopy revealed that La-AMP caused irreversible damage to cell membranes of S. aureus and E. coli, a finding further confirmed by calcein-AM/propidium iodide staining. Additionally, La-AMP induced nucleic acid leakage and reactive oxygen species accumulation in bacterial cells. It was found to bind to DNA gyrase through salt bridges, hydrogen bonds, and hydrophobic interactions, ultimately inducing apoptosis. Thus, La-AMP exhibited encouraging promise as a valuable bioactive component for the development of natural preservatives.

Two thiosemicarbazones derived from 1-indanone as potent non-nucleoside inhibitors of bovine viral diarrhea virus of different genotypes and biotypes.

Bovine viral diarrhea virus (BVDV) is a widespread pathogen of cattle and other mammals that causes major economic losses in the livestock industry. N4-TSC and 6NO2-TSC are two thiosemicarbazones derived from 1-indanone that exhibit anti-BVDV activity in vitro. These compounds selectively inhibit BVDV and are effective against both cytopathic and non-cytopathic BVDV-1 and BVDV-2 strains. We confirmed that N4-TSC acts at the onset of viral RNA synthesis, as previously reported for 6NO2-TSC. Moreover, resistance selection and characterization showed that N4-TSCR mutants were highly resistant to N4-TSC but remained susceptible to 6NO2-TSC. In contrast, 6NO2-TSCR mutants were resistant to both compounds. Additionally, mutations N264D and A392E were found in the viral RNA-dependent RNA polymerase (RdRp) of N4-TSCR mutants, whereas I261 M was found in 6NO2-TSCR mutants. These mutations lay in a hydrophobic pocket within the fingertips region of BVDV RdRp that has been described as a "hot spot" for BVDV non-nucleoside inhibitors.

DN-ODE: Data-driven neural-ODE modeling for breast cancer tumor dynamics and progression-free survivals.

Pharmacokinetic/Pharmacodynamic (PK/PD) modeling is crucial in the development of new drugs. However, traditional population-based PK/PD models encounter challenges when modeling for individual patients. We aim to explore the potential of constructing a pharmacodynamic model for individual breast cancer pharmacodynamics leveraging only limited data from early clinical trial phases. While previous studies on Neural Ordinary Differential Equations (ODEs) suggest promising results in clinical trial practices, they primarily focused on theoretical applications or independent PK/PD modeling. PD modeling from complex and irregular clinical trial data, especially when interacting with PK parameters, is still unclear. To achieve that, we introduce a Data-driven Neural Ordinary Differential Equation (DN-ODE) modeling for breast cancer tumor dynamics and progression-free survival data. To validate this approach, experiments are conducted with early-phase clinical trial data from the Amcenestrant (an oral treatment for breast cancer) dataset (AMEERA 1-2), aiming to predict pharmacodynamics in the later phase (AMEERA 3). DN-ODE model achieves RMSE scores of 8.78 and 0.21 in tumor size and progression-free survival, respectively, with R2 scores over 0.9 for each task. Compared to PK/PD methodologies, DN-ODE is able to predict robust individual tumor dynamics with only limited cycle data. We also introduce Principal Component Analysis visualizations for encoder results, demonstrating the DN-ODE's capability to discern individual distributions and diverse tumor growth patterns. Therefore, DN-ODE facilitates comprehensive drug efficacy assessments, pinpoints potential responders, and aids in trial design.

On the dual role of (+)-catechin as primary antioxidant and inhibitor of viral proteases.

Natural antioxidants have become the subject of many investigations due to the role that they play in the reduction of oxidative stress. Their main scavenging mechanisms concern the direct inactivation of free radicals and the coordination of metal ions involved in Fenton-like reactions. Recently, increasing attention has been paid to non-covalent inhibition of enzymes involved in different diseases by the antioxidants. Here, a computational investigation on the primary antioxidant power of (+)-catechin against the •OOH radical has been performed in both lipid-like and aqueous environments, taking into account the relevant species present in the simulated acid-base equilibria at the physiological pH. Hydrogen Atom Transfer (HAT), Single Electron Transfer (SET), and Radical Adduct Formation (RAF) mechanisms were studied, and relative rate constants were estimated. The potential inhibitory activity of the (+)-catechin towards the most important proteases from SARS-CoV-2, 3C-like (Mpro) and papain-like (PLpro) proteases was also investigated by MD simulations to provide deeper atomistic insights on the binding sites. Based on the antioxidant and antiviral properties also unravelled by comparison with other molecules having similar chemical scaffold, our results propose that (+)-CTc satisfies can explicate a dual action as antioxidant and antiviral in particular versus Mpro from SARS-CoV-2.

Intrinsic dynamics of emulsions: Experiments in microgravity on the International Space Station.

HYPOTHESIS: In order to understand the basic mechanisms affecting emulsion stability, the intrinsic dynamics of the drop population must be investigated. We hypothesize that transient ballistic motion can serve as a marker of interactions between drops. In 1G conditions, buoyancy-induced drop motion obscures these interactions. The microgravity condition onboard the International Space Station enable this investigation. EXPERIMENTS: We performed Diffusing Wave Spectroscopy (DWS) experiments in the ESA Soft Matter Dynamics (SMD) facility. We used Monte Carlo simulations of photon trajectory to support data analysis. The analysis framework was validated by ground-based characterizations of the initial drop size distribution (DSD) and the properties of the oil/water interface in the presence of surfactant. FINDINGS: We characterized the drop size distribution and found to be bi-disperse. Drop dynamics shows transient ballistic features at early times, reaching a stationary regime of primarily diffusion-dominated motion. This suggests different ageing mechanisms: immediately after emulsification, the main mechanism is coalescence or aggregation between small drops. However at later times, ageing proceeds via coalescence or aggregation of small with large drops in some emulsions. Our results elucidate new processes relevant to emulsion stability with potential impact on industrial processes on Earth, as well as enabling technologies for space exploration.

Differential contribution of microbial and plant-derived organic matter to soil organic carbon sequestration over two decades of natural revegetation and cropping.

Both natural revegetation and cropping have great impact on long-term soil carbon (C) sequestration, yet the differences in their underlying mechanisms remain unclear. In this study, we investigated trends in soil organic C (SOC) accumulation during natural revegetation (VR) and cropping processes over 24 years, and explored the contributions of microbial necromass and plant-derived C to SOC formation and their primary controls. Over the course of 24 years of land use/cover change (LUCC) from 1995, SOC content exhibited a more substantial increase in VR (0.31 g kg-1 a-1) than in cropland (0.14 g kg-1 a-1) during Stage II (>10 y after LUCC), and recalcitrant organic carbon explained more of the SOC variation than easily oxidizable carbon. The higher SOC content in VR was attributed to a greater contribution of plant-derived C (14-28 %) than that in cropland (3-11 %) to SOC and a consistently lower ratio of cinnamyl (C)- to vanillyl (V)-type phenols in VR across all the assessed years. Although there were higher proportion of microbial necromass of SOC (41-84 %) in cropland than in VR, the differences were not significant. The dominant bacterial phylum of Chloroflexi and soil nitrogen content were the primary biotic and abiotic factors regulating microbial-derived and plant-derived C in both cropland and VR. However, soil phosphorus content was the main factor in cropland, while climatic factors such as mean annual precipitation were more important in VR. These results provided evidence that long-term natural revegetation enhanced SOC sequestration by greater contribution of plant-derived C to SOC formation compared to cropping. These findings underscore the synergistic contribution of vegetation and microorganisms to long-term SOC sequestration, offering insights into the different mechanisms of carbon formation during VR and cropping processes, and providing support for optimizing land management to achieve global carbon neutrality goals.

Mitochondrial dynamics and psychiatric disorders: The missing link.

Elucidating the molecular mechanisms of psychopathology is crucial for optimized diagnosis and treatment. Accumulating literature has underlined how mitochondrial bioenergetics affect major psychiatric disorders. However, how mitochondrial dynamics, a term addressing mitochondria quality control, including mitochondrial fission, fusion, biogenesis and mitophagy, is implicated in psychopathologies remains elusive. In this review we summarize the existing literature on mitochondrial dynamics perturbations in psychiatric disorders/neuropsychiatric phenotypes. We include preclinical/clinical literature on mitochondrial dynamics recalibrations in anxiety, depression, post-traumatic stress disorder (PTSD), bipolar disorder and schizophrenia. We discuss alterations in mitochondrial network, morphology and shape; molecular markers of the mitochondrial dynamics machinery and mitochondrial DNA copy number (mtDNAcn) in animal models and human cohorts in brain and peripheral material. By looking for common altered mitochondrial dynamics patterns across diagnoses/phenotypes, we highlight mitophagy and biogenesis as regulators of anxiety and depression pathophysiology, respectively, as well as the fusion mediator dynamin-like 120kDa protein (Opa1) as a molecular hub contributing to psychopathology. Finally, we comment on limitations and future directions in this novel neuropsychiatry field.

Intrinsic disorder and salt-dependent conformational changes of the N-terminal region of TFIP11 splicing factor.

Tuftelin Interacting Protein 11 (TFIP11) was identified as a critical human spliceosome assembly regulator, interacting with multiple proteins and localising in membrane-less organelles. However, a lack of structural information on TFIP11 limits the rationalisation of its biological role. TFIP11 is predicted as an intrinsically disordered protein (IDP), and more specifically concerning its N-terminal (N-TER) region. IDPs lack a defined tertiary structure, existing as a dynamic conformational ensemble, favouring protein-protein and protein-RNA interactions. IDPs are involved in liquid-liquid phase separation (LLPS), driving the formation of subnuclear compartments. Combining disorder prediction, molecular dynamics, and spectroscopy methods, this contribution shows the first evidence TFIP11 N-TER is a polyampholytic IDP, exhibiting a structural duality with the coexistence of ordered and disordered assemblies, depending on the ionic strength. Increasing the salt concentration enhances the protein conformational flexibility, presenting a more globule-like shape, and a fuzzier unstructured arrangement that could favour LLPS and protein-RNA interaction. The most charged and hydrophilic regions are the most impacted, including the G-Patch domain essential to TFIP11 function. This study gives a better understanding of the salt-dependent conformational behaviour of the N-TER TFIP11, supporting the hypothesis of the formation of different types of protein assembly, in line with its multiple biological roles.

Computer-aided mining of a psychrophilic cellobiose 2-epimerase from the Qinghai-Tibet plateau gene catalogue.

Cellobiose 2-epimerase (CE) catalyzes the conversion of the lactose into its high-value derivatives, epilactose and lactulose, which has great prospects in food applications. In this study, CE sequences from the Qinghai-Tibet Plateau gene catalogue, we screened these for structural flexibility through molecular dynamics simulation to identify potential psychrophilic CE candidates. One such psychrophilic CE we termed psyCE demonstrated exceptional epimerization activity, achieving an optimum activity of 122.2 ±â€¯1.6 U/mg. Its kinetic parameters (Kcat and Km) for epimerization activity were 219.9 ±â€¯5.6 s-1 and 261.9 ±â€¯18.1 mM, respectively, representing the highest Kcat recorded among known cold-active CEs. Notably, this is the first report of a psychrophilic CE. The psyCE can effectively produce epilactose at 8 °C, converting 20.3 % of 200 mM lactose into epilactose within four hours. These findings suggest that psyCE is highly suitable for cryogenic food processing, and glaciers may serve as a valuable repository of psychrophilic enzymes.

Exploration of dynamic interaction between ß-lactoglobulin and casein micelles during UHT milk process.

The protein aggregation induced by UHT treatment shortens the shelf life of UHT milk. However, the mechanism of ß-Lg induced casein micelle aggregation remains unclear. Herein, the dynamic interaction between ß-Lg and casein micelles during UHT processing was investigated by experimental techniques and molecular dynamics simulations. Results showed that ß-Lg decreased the stability of casein micelles, increased their size and zeta potential. Raman and FTIR spectra analysis suggested that hydrogen and disulfide bonds facilitated their interaction. Cryo-TEM showed that the formation of the casein micelle/ß-Lg complex involved rigid binding, flexible linking, and severe cross-linking aggregation during UHT processing. SAXS and MST demonstrated ß-Lg bound to κ-casein on micelle surfaces with a dissociation constant (Kd) of 3.84 ±â€¯1.14 µm. Molecular docking and dynamic simulations identified the interacting amino acid residues and clarified that electrostatic and van der Waals forces drove the interaction. UHT treatment increased hydrogen bonds and decreased total binding energy. The non-covalent binding promoted the formation of disulfide bonds between ß-Lg and casein micelles under heat treatment. Ultimately, it was concluded that non-covalent interaction and disulfide bonding resulted in casein micelle/ß-Lg aggregates. These findings provided scientific insights into protein aggregation in UHT milk.

An Infrared Nanospectroscopy Technique for the Study of Electric-Field-Induced Molecular Dynamics.

Static electric fields play a considerable role in a variety of molecular nanosystems as diverse as single-molecule junctions, molecules supporting electrostatic catalysis, and biological cell membranes incorporating proteins. External electric fields can be applied to nanoscale samples with a conductive atomic force microscopy (AFM) probe in contact mode, but typically, no structural information is retrieved. Here we combine photothermal expansion infrared (IR) nanospectroscopy with electrostatic AFM probes to measure nanometric volumes where the IR field enhancement and the static electric field overlap spatially. We leverage the vibrational Stark effect in the polymer poly(methyl methacrylate) for calibrating the local electric field strength. In the relevant case of membrane protein bacteriorhodopsin, we observe electric-field-induced changes of the protein backbone conformation and residue protonation state. The proposed technique also has the potential to measure DC currents and IR spectra simultaneously, insofar enabling the monitoring of the possible interplay between charge transport and other effects.

A Polarizable Forcefields for Glyoxal Acetals as Electrolyte Components for Lithium-Ion Batteries.

In this work we have derived the parameters of an AMOEBA-like polarizable forcefield for electrolytes based on tetramethoxy and tetraethoxy-glyoxal acetals, and propylene carbonate. The resulting forcefield has been validated using both ab-initio data and the experimental properties of the fluids. Using molecular dynamics simulations, we have investigated the structural features and the solvation properties of both the neat liquids and of the corresponding 1 M LiTFSI electrolytes at the molecular level. We present a detailed analysis of the Li ion solvation shells, of their structure and highlight the different behavior of the solvents in terms of their molecular structure and coordinating features.

Universality in the Structure and Dynamics of Water under Lipidic Mesophase Soft Nanoconfinement.

Water under soft nanoconfinement features physical and chemical properties fundamentally different from bulk water; yet, the multitude and specificity of confining systems and geometries mask any of its potentially universal traits. Here, we advance in this quest by resorting to lipidic mesophases as an ideal nanoconfinement system, allowing inspecting the behavior of water under systematic changes in the topological and geometrical properties of the confining medium, without altering the chemical nature of the interfaces. By combining Terahertz absorption spectroscopy experiments and molecular dynamics simulations, we unveil the presence of universal laws governing the physics of nanoconfined water, recapitulating the data collected at varying levels of hydration and nanoconfinement topologies. This geometry-independent universality is evidenced by the existence of master curves characterizing both the structure and dynamics of simulated water as a function of the distance from the lipid-water interface. Based on our theoretical findings, we predict a parameter-free law describing the amount of interfacial water against the structural dimension of the system (i.e., the lattice parameter), which captures both the experimental and numerical results within the same curve, without any fitting. Our results offer insight into the fundamental physics of water under soft nanoconfinement and provide a practical tool for accurately estimating the amount of nonbulk water based on structural experimental data.

Preparation of magnetic activated carbon fibers@Fe3O4 by electrostatic self-assembly method and adsorption properties for methylene blue.

Nano-Fe3O4 was loaded onto coconut-based activated carbon fibres (CACF) using an electrostatic self-assembly method. The effects of the mass ratio of CACF to nano-Fe3O4, loading time, pH and temperature on the loading effect were investigated and ideal loading conditions were determined. To study the adsorption performance of MACF@Fe3O4 for methylene blue, the effects of the initial concentration, pH and time on the adsorption were investigated and the working conditions of adsorption were established. MACF@Fe3O4 was systematically characterized. Adsorption kinetics were investigated under ideal conditions. The ideal loading conditions for MACF@Fe3O4 were as follows: mass ratio of 1:1, 20 min, pH 9.36, 22.5°C. The saturation magnetization of MACF@Fe3O4 was 48.2263 emu·g-1, which could be quickly separated under an external magnetic field. When the dosage was 0.010 g, the adsorption rate reached 97.29% and the maximum adsorption capacity was 12.1616 mg·g-1. The adsorption process conformed to pseudo-first-order kinetics during the first 15 min and pseudo-second-order kinetics during 20-120 min. The equations were ln( Q e - Q t )=2.2394-0.0689t and t Q t =0.0774 + 0.5295t , respectively. The isothermal adsorption model showed that MACF@Fe3O4 was more in line with the Langmuir model, indicating that the adsorption process was mainly monolayer adsorption. The thermodynamic analysis results showed that the adsorption process of MB by MACF@Fe3O4 was an endothermic process. In this study, MACF@Fe3O4 with high adsorption capacity and easy separation from coconut palm fibres has good application prospects in the field of adsorption, which can promote the high-value utilization of coconut palms.

Cheminformatics-based identification of phosphorylated RET tyrosine kinase inhibitors for human cancer.

Background: Rearranged during transfection (RET), an oncogenic protein, is associated with various cancers, including non-small-cell lung cancer (NSCLC), papillary thyroid cancer (PTC), pancreatic cancer, medullary thyroid cancer (MTC), breast cancer, and colorectal cancer. Dysregulation of RET contributes to cancer development, highlighting the importance of identifying lead compounds targeting this protein due to its pivotal role in cancer progression. Therefore, this study aims to discover effective lead compounds targeting RET across different cancer types and evaluate their potential to inhibit cancer progression. Methods: This study used a range of computational techniques, including Phase database creation, high-throughput virtual screening (HTVS), molecular docking, molecular mechanics with generalized Born surface area (MM-GBSA) solvation, assessment of pharmacokinetic (PK) properties, and molecular dynamics (MD) simulations, to identify potential lead compounds targeting RET. Results: Initially, a high-throughput virtual screening of the ZINC database identified 2,550 compounds from a pool of 170,269. Subsequent molecular docking studies revealed 10 compounds with promising negative binding scores ranging from -8.458 to -7.791 kcal/mol. MM-GBSA analysis further confirmed the potential of four compounds to exhibit negative binding scores. MD simulations demonstrated the stability of CID 95842900, CID 137030374, CID 124958150, and CID 110126793 with the target receptors. Conclusion: These findings suggest that these selected four compounds have the potential to inhibit phosphorylated RET (pRET) tyrosine kinase activity and may represent promising candidates for the treatment of various cancers.

Superposition of Substrate Deformation Fields Induced by Molecular Clutches Explains Cell Spatial Sensing of Ligands.

Cells can sense the physical properties of the extracellular matrices (ECMs), such as stiffness and ligand density, through cell adhesions to actively regulate their behaviors. Recent studies have shown that varying ligand spacing of ECMs can influence adhesion size, cell spreading, and even stem cell differentiation, indicating that cells have the spatial sensing ability of ECM ligands. However, the mechanism of the cells' spatial sensing remains unclear. In this study, we have developed a lattice-spring motor-clutch model by integrating cell membrane deformation, the talin unfolding mechanism, and the lattice spring for substrate ligand distribution to explore how the spatial distribution of integrin ligands and substrate stiffness influence cell spreading and adhesion dynamics. By applying the Gillespie algorithm, we found that large ligand spacing reduces the superposition effect of the substrate's displacement fields generated by pulling force from motor-clutch units, increasing the effective stiffness probed by the force-sensitive receptors; this finding explains a series of previous experiments. Furthermore, using the mean-field theory, we obtain the effective stiffness sensed by bound clutches analytically; our analysis shows that the bound clutch number and ligand spacing are the two key factors that affect the superposition effects of deformation fields and, hence, the effective stiffness. Overall, our study reveals the mechanism of cells' spatial sensing, i.e., ligand spacing changes the effective stiffness sensed by cells due to the superposition effect of deformation fields, which provides a physical clue for designing and developing biological materials that effectively control cell behavior and function.

When is lethal deceptive pollination maintained? A population dynamics approach.

BACKGROUND AND AIMS: Not all plant-pollinator interactions are mutualistic, and in fact, deceptive pollination systems are widespread in nature. The genus Arisaema has a pollination system known as lethal deceptive pollination, in which plants not only attract pollinating insects without providing any rewards, but also trap them until they die. Many Arisaema species are endangered from various disturbances including reduction in forest habitat, modification of the forest understory owing to increasing deer abundance, and plant theft for horticultural cultivation. We aimed to theoretically investigate how lethal deceptive pollination can be maintained from a demographic perspective and how plant and pollinator populations respond to different types of disturbance. METHODS: We developed and analysed a mathematical model to describe the population dynamics of a deceptive plant species and its victim pollinator. Calibrating the model based on empirical data, we assessed the conditions under which plants and pollinators could coexist, while manipulating relevant key parameters. KEY RESULTS: The model exhibited qualitatively distinct behaviours depending on certain parameters. The plant becomes extinct when it has a low capability for vegetative reproduction and slow transition from male to female, and plant-insect co-extinction occurs especially when the plant is highly attractive to male insects. Increasing deer abundance has both positive and negative effects because of removal of other competitive plants and diminishing pollinators, respectively. Theft for horticultural cultivation can readily threaten plants whether male or female plants are frequently collected. The impact of forest habitat reduction may be limited compared to that of other disturbance types. CONCLUSIONS: Our results have emphasised that the demographic vulnerability of lethal deceptive pollination systems would differ qualitatively from that of general mutualistic pollination systems. It is therefore important to consider the demographics of both victim pollinators and deceptive plants to estimate how endangered Arisaema populations respond to various disturbances.

Range dynamics of Anopheles mosquitoes in Africa suggest a significant increase in the malaria transmission risk.

Despite a more than 100-year effort to combat malaria, it remains one of the most malignant infectious diseases globally, especially in Africa. Malaria is transmitted by several Anopheles mosquitoes. However, until now few studies have investigated future range dynamics of major An. mosquitoes in Africa through a unified scheme. Through a unified scheme, we developed 21 species distribution models to predict the range dynamics of 21 major An. species in Africa under future scenarios and also examined their overall range dynamic patterns mainly through suitability overlap index and range overlap index. Although future range dynamics varied substantially among the 21 An. species, we predicted large future range expansions for all 21 An. species, and increases in suitability overlap index were detected in more than 90% of the African continent for all future scenarios. Additionally, we predicted high range overlap index in West Africa, East Africa, South Sudan, Angola, and the Democratic Republic of the Congo under future scenarios. Although the relative impacts of land use, topography and climate variables on the range dynamics depended on species and spatial scale, climate played the strongest roles in the range dynamics of most species. Africa might face an increasing risk of malaria transmissions in the future, and better strategies are required to address this problem. Mitigating climate change and human disturbance of natural ecosystems might be essential to reduce the proliferation of An. species and the risk of malaria transmissions in Africa in the future. Our strategies against their impacts should be species-specific.