Antibody Lineages with Vaccine-Induced Antigen-Binding Hotspots Develop Broad HIV Neutralization.

The vaccine-mediated elicitation of antibodies (Abs) capable of neutralizing diverse HIV-1 strains has been a long-standing goal. To understand how broadly neutralizing antibodies (bNAbs) can be elicited, we identified, characterized, and tracked five neutralizing Ab lineages targeting the HIV-1-fusion peptide (FP) in vaccinated macaques over time. Genetic and structural analyses revealed two of these lineages to belong to a reproducible class capable of neutralizing up to 59% of 208 diverse viral strains. B cell analysis indicated each of the five lineages to have been initiated and expanded by FP-carrier priming, with envelope (Env)-trimer boosts inducing cross-reactive neutralization. These Abs had binding-energy hotspots focused on FP, whereas several FP-directed Abs induced by immunization with Env trimer-only were less FP-focused and less broadly neutralizing. Priming with a conserved subregion, such as FP, can thus induce Abs with binding-energy hotspots coincident with the target subregion and capable of broad neutralization.

Infectious diseases and discrimination: Sicily's Lampedusa migrants.

Lampedusa, a picturesque Italian island in the Mediterranean, serves as a gateway for migrants from Africa and Asia to Europe. Despite populist rhetoric portraying migrants as carriers of disease, epidemiological data reveal very low levels of communicable diseases among migrants, challenging false narratives and xenophobic sentiments propagated by populist governments.

De novo mutation hotspots in homologous protein domains identify function-altering mutations in neurodevelopmental disorders.

Variant interpretation remains a major challenge in medical genetics. We developed Meta-Domain HotSpot (MDHS) to identify mutational hotspots across homologous protein domains. We applied MDHS to a dataset of 45,221 de novo mutations (DNMs) from 31,058 individuals with neurodevelopmental disorders (NDDs) and identified three significantly enriched missense DNM hotspots in the ion transport protein domain family (PF00520). The 37 unique missense DNMs that drive enrichment affect 25 genes, 19 of which were previously associated with NDDs. 3D protein structure modeling supports the hypothesis of function-altering effects of these mutations. Hotspot genes have a unique expression pattern in tissue, and we used this pattern alongside in silico predictors and population constraint information to identify candidate NDD-associated genes. We also propose a lenient version of our method, which identifies 32 hotspot positions across 16 different protein domains. These positions are enriched for likely pathogenic variation in clinical databases and DNMs in other genetic disorders.

PRDM9 Methyltransferase Activity Is Essential for Meiotic DNA Double-Strand Break Formation at Its Binding Sites.

The programmed formation of hundreds of DNA double-strand breaks (DSBs) is essential for proper meiosis and fertility. In mice and humans, the location of these breaks is determined by the meiosis-specific protein PRDM9, through the DNA-binding specificity of its zinc-finger domain. PRDM9 also has methyltransferase activity. Here, we show that this activity is required for H3K4me3 and H3K36me3 deposition and for DSB formation at PRDM9-binding sites. By analyzing mice that express two PRDM9 variants with distinct DNA-binding specificities, we show that each variant generates its own set of H3K4me3 marks independently from the other variant. Altogether, we reveal several basic principles of PRDM9-dependent DSB site determination, in which an excess of sites are designated through PRDM9 binding and subsequent histone methylation, from which a subset is selected for DSB formation.

Autumn stopover hotspots and multiscale habitat associations of migratory landbirds in the eastern United States.

Halting the global decline of migratory birds requires a better understanding of migration ecology. Stopover sites are a crucial yet understudied aspect of bird conservation, mostly due to challenges associated with understanding broad-scale patterns of transient habitat use. Here, we use a national network of weather radar stations to identify stopover hotspots and assess multiscale habitat associations of migratory landbirds across the eastern United States during autumn migration. We mapped seasonal bird densities over 5 y (2015 to 2019) from 60 radar stations covering 63.2 million hectares. At a coarse scale, we found that landbirds migrate across a broad front with small differences in migrant density between radar domains. However, relatively more birds concentrate along the Mississippi River and Appalachian Mountains. At a finer scale, we identified radar pixels that consistently harbored high densities of migrants for all 5 y, which we classify as stopover hotspots. Hotspot probability increased with percent cover of all forest types and decreased with percent cover of pasture and cultivated crops. Moreover, we found strong concentrating effects of deciduous forest patches within deforested regions. We also found that the prairie biome in the Midwest (now mostly cropland) is likely a migration barrier, with large concentrations of migrants at the prairie-forest boundary after crossing the agricultural Midwest. Overall, the broad-front migration pattern highlights the importance of locally based conservation efforts to protect stopover habitats. Such efforts should target forests, especially deciduous forests in highly altered landscapes. These findings demonstrate the value of multiscale habitat assessments for the conservation of migratory landbirds.

A massively parallel assay accurately discriminates between functionally normal and abnormal variants in a hotspot domain of KCNH2.

Many genes, including KCNH2, contain "hotspot" domains associated with a high density of variants associated with disease. This has led to the suggestion that variant location can be used as evidence supporting classification of clinical variants. However, it is not known what proportion of all potential variants in hotspot domains cause loss of function. Here, we have used a massively parallel trafficking assay to characterize all single-nucleotide variants in exon 2 of KCNH2, a known hotspot for variants that cause long QT syndrome type 2 and an increased risk of sudden cardiac death. Forty-two percent of KCNH2 exon 2 variants caused at least 50% reduction in protein trafficking, and 65% of these trafficking-defective variants exerted a dominant-negative effect when co-expressed with a WT KCNH2 allele as assessed using a calibrated patch-clamp electrophysiology assay. The massively parallel trafficking assay was more accurate (AUC of 0.94) than bioinformatic prediction tools (REVEL and CardioBoost, AUC of 0.81) in discriminating between functionally normal and abnormal variants. Interestingly, over half of variants in exon 2 were found to be functionally normal, suggesting a nuanced interpretation of variants in this "hotspot" domain is necessary. Our massively parallel trafficking assay can provide this information prospectively.

Hotspot propensity across mutational processes.

The sparsity of mutations observed across tumours hinders our ability to study mutation rate variability at nucleotide resolution. To circumvent this, here we investigated the propensity of mutational processes to form mutational hotspots as a readout of their mutation rate variability at single base resolution. Mutational signatures 1 and 17 have the highest hotspot propensity (5-78 times higher than other processes). After accounting for trinucleotide mutational probabilities, sequence composition and mutational heterogeneity at 10 Kbp, most (94-95%) signature 17 hotspots remain unexplained, suggesting a significant role of local genomic features. For signature 1, the inclusion of genome-wide distribution of methylated CpG sites into models can explain most (80-100%) of the hotspot propensity. There is an increased hotspot propensity of signature 1 in normal tissues and de novo germline mutations. We demonstrate that hotspot propensity is a useful readout to assess the accuracy of mutation rate models at nucleotide resolution. This new approach and the findings derived from it open up new avenues for a range of somatic and germline studies investigating and modelling mutagenesis.

Using protein language models for protein interaction hot spot prediction with limited data.

BACKGROUND: Protein language models, inspired by the success of large language models in deciphering human language, have emerged as powerful tools for unraveling the intricate code of life inscribed within protein sequences. They have gained significant attention for their promising applications across various areas, including the sequence-based prediction of secondary and tertiary protein structure, the discovery of new functional protein sequences/folds, and the assessment of mutational impact on protein fitness. However, their utility in learning to predict protein residue properties based on scant datasets, such as protein-protein interaction (PPI)-hotspots whose mutations significantly impair PPIs, remained unclear. Here, we explore the feasibility of using protein language-learned representations as features for machine learning to predict PPI-hotspots using a dataset containing 414 experimentally confirmed PPI-hotspots and 504 PPI-nonhot spots. RESULTS: Our findings showcase the capacity of unsupervised learning with protein language models in capturing critical functional attributes of protein residues derived from the evolutionary information encoded within amino acid sequences. We show that methods relying on protein language models can compete with methods employing sequence and structure-based features to predict PPI-hotspots from the free protein structure. We observed an optimal number of features for model precision, suggesting a balance between information and overfitting. CONCLUSIONS: This study underscores the potential of transformer-based protein language models to extract critical knowledge from sparse datasets, exemplified here by the challenging realm of predicting PPI-hotspots. These models offer a cost-effective and time-efficient alternative to traditional experimental methods for predicting certain residue properties. However, the challenge of explaining why specific features are important for determining certain residue properties remains.

Scaffold Matcher: A CMA-ES based algorithm for identifying hotspot aligned peptidomimetic scaffolds.

The design of protein interaction inhibitors is a promising approach to address aberrant protein interactions that cause disease. One strategy in designing inhibitors is to use peptidomimetic scaffolds that mimic the natural interaction interface. A central challenge in using peptidomimetics as protein interaction inhibitors, however, is determining how best the molecular scaffold aligns to the residues of the interface it is attempting to mimic. Here we present the Scaffold Matcher algorithm that aligns a given molecular scaffold onto hotspot residues from a protein interaction interface. To optimize the degrees of freedom of the molecular scaffold we implement the covariance matrix adaptation evolution strategy (CMA-ES), a state-of-the-art derivative-free optimization algorithm in Rosetta. To evaluate the performance of the CMA-ES, we used 26 peptides from the FlexPepDock Benchmark and compared with three other algorithms in Rosetta, specifically, Rosetta's default minimizer, a Monte Carlo protocol of small backbone perturbations, and a Genetic algorithm. We test the algorithms' performance on their ability to align a molecular scaffold to a series of hotspot residues (i.e., constraints) along native peptides. Of the 4 methods, CMA-ES was able to find the lowest energy conformation for all 26 benchmark peptides. Additionally, as a proof of concept, we apply the Scaffold Match algorithm with CMA-ES to align a peptidomimetic oligooxopiperazine scaffold to the hotspot residues of the substrate of the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our implementation of CMA-ES into Rosetta allows for an alternative optimization method to be used on macromolecular modeling problems with rough energy landscapes. Finally, our Scaffold Matcher algorithm allows for the identification of initial conformations of interaction inhibitors that can be further designed and optimized as high-affinity reagents.

Interfacial residues in protein-protein complexes are in the eyes of the beholder.

Interactions between proteins are vital in almost all biological processes. The characterization of protein-protein interactions helps us understand the mechanistic basis of biological processes, thereby enabling the manipulation of proteins for biotechnological and clinical purposes. The interface residues of a protein-protein complex are assumed to have the following two properties: (a) they always interact with a residue of a partner protein, which forms the basis for distance-based interface residue identification methods, and (b) they are solvent-exposed in the isolated form of the protein and become buried in the complex form, which forms the basis for Accessible Surface Area (ASA)-based methods. The study interrogates this popular assumption by recognizing interface residues in protein-protein complexes through these two methods. The results show that a few residues are identified uniquely by each method, and the extent of conservation, propensities, and their contribution to the stability of protein-protein interaction varies substantially between these residues. The case study analyses showed that interface residues, unique to distance, participate in crucial interactions that hold the proteins together, whereas the interface residues unique to the ASA method have a potential role in the recognition, dynamics, and specificity of the complex and can also be a hotspot. Overall, the study recommends applying both distance and ASA methods so that some interface residues missed by either method but crucial to the stability, recognition, dynamics, and function of protein-protein complexes are identified in a complementary manner.

Common occurrence of hotspots of single strand DNA breaks at transcriptional start sites.

BACKGROUND: We recently developed two high-resolution methods for genome-wide mapping of two prominent types of DNA damage, single-strand DNA breaks (SSBs) and abasic (AP) sites and found highly complex and non-random patterns of these lesions in mammalian genomes. One salient feature of SSB and AP sites was the existence of single-nucleotide hotspots for both lesions. RESULTS: In this work, we show that SSB hotspots are enriched in the immediate vicinity of transcriptional start sites (TSSs) in multiple normal mammalian tissues, however the magnitude of enrichment varies significantly with tissue type and appears to be limited to a subset of genes. SSB hotspots around TSSs are enriched on the template strand and associate with higher expression of the corresponding genes. Interestingly, SSB hotspots appear to be at least in part generated by the base-excision repair (BER) pathway from the AP sites. CONCLUSIONS: Our results highlight complex relationship between DNA damage and regulation of gene expression and suggest an exciting possibility that SSBs at TSSs might function as sensors of DNA damage to activate genes important for DNA damage response.

Rapid Evolution of the Fine-scale Recombination Landscape in Wild House Mouse (Mus musculus) Populations.

Meiotic recombination is an important evolutionary force and an essential meiotic process. In many species, recombination events concentrate into hotspots defined by the site-specific binding of PRMD9. Rapid evolution of Prdm9's zinc finger DNA-binding array leads to remarkably abrupt shifts in the genomic distribution of hotspots between species, but the question of how Prdm9 allelic variation shapes the landscape of recombination between populations remains less well understood. Wild house mice (Mus musculus) harbor exceptional Prdm9 diversity, with >150 alleles identified to date, and pose a particularly powerful system for addressing this open question. We employed a coalescent-based approach to construct broad- and fine-scale sex-averaged recombination maps from contemporary patterns of linkage disequilibrium in nine geographically isolated wild house mouse populations, including multiple populations from each of three subspecies. Comparing maps between wild mouse populations and subspecies reveals several themes. First, we report weak fine- and broad-scale recombination map conservation across subspecies and populations, with genetic divergence offering no clear prediction for recombination map divergence. Second, most hotspots are unique to one population, an outcome consistent with minimal sharing of Prdm9 alleles between surveyed populations. Finally, by contrasting aggregate hotspot activity on the X versus autosomes, we uncover evidence for population-specific differences in the degree and direction of sex dimorphism for recombination. Overall, our findings illuminate the variability of both the broad- and fine-scale recombination landscape in M. musculus and underscore the functional impact of Prdm9 allelic variation in wild mouse populations.

Genetic Modification of a Hox Locus Drives Mimetic Color Pattern Variation in a Highly Polymorphic Bumble Bee.

Müllerian mimicry provides natural replicates ideal for exploring mechanisms underlying adaptive phenotypic divergence and convergence, yet the genetic mechanisms underlying mimetic variation remain largely unknown. The current study investigates the genetic basis of mimetic color pattern variation in a highly polymorphic bumble bee, Bombus breviceps (Hymenoptera, Apidae). In South Asia, this species and multiple comimetic species converge onto local Müllerian mimicry patterns by shifting the abdominal setal color from orange to black. Genetic crossing between the orange and black phenotypes suggested the color dimorphism being controlled by a single Mendelian locus, with the orange allele being dominant over black. Genome-wide association suggests that a locus at the intergenic region between 2 abdominal fate-determining Hox genes, abd-A and Abd-B, is associated with the color change. This locus is therefore in the same intergenic region but not the same exact locus as found to drive red black midabdominal variation in a distantly related bumble bee species, Bombus melanopygus. Gene expression analysis and RNA interferences suggest that differential expression of an intergenic long noncoding RNA between abd-A and Abd-B at the onset setal color differentiation may drive the orange black color variation by causing a homeotic shift late in development. Analysis of this same color locus in comimetic species reveals no sequence association with the same color shift, suggesting that mimetic convergence is achieved through distinct genetic routes. Our study establishes Hox regions as genomic hotspots for color pattern evolution in bumble bees and demonstrates how pleiotropic developmental loci can drive adaptive radiations in nature.

fastDRH: a webserver to predict and analyze protein-ligand complexes based on molecular docking and MM/PB(GB)SA computation.

Predicting the native or near-native binding pose of a small molecule within a protein binding pocket is an extremely important task in structure-based drug design, especially in the hit-to-lead and lead optimization phases. In this study, fastDRH, a free and open accessed web server, was developed to predict and analyze protein-ligand complex structures. In fastDRH server, AutoDock Vina and AutoDock-GPU docking engines, structure-truncated MM/PB(GB)SA free energy calculation procedures and multiple poses based per-residue energy decomposition analysis were well integrated into a user-friendly and multifunctional online platform. Benefit from the modular architecture, users can flexibly use one or more of three features, including molecular docking, docking pose rescoring and hotspot residue prediction, to obtain the key information clearly based on a result analysis panel supported by 3Dmol.js and Apache ECharts. In terms of protein-ligand binding mode prediction, the integrated structure-truncated MM/PB(GB)SA rescoring procedures exhibit a success rate of >80% in benchmark, which is much better than the AutoDock Vina (~70%). For hotspot residue identification, our multiple poses based per-residue energy decomposition analysis strategy is a more reliable solution than the one using only a single pose, and the performance of our solution has been experimentally validated in several drug discovery projects. To summarize, the fastDRH server is a useful tool for predicting the ligand binding mode and the hotspot residue of protein for ligand binding. The fastDRH server is accessible free of charge at http://cadd.zju.edu.cn/fastdrh/.

Rapid in situ diversification rates in Rhamnaceae explain the parallel evolution of high diversity in temperate biomes from global to local scales.

The macroevolutionary processes that have shaped biodiversity across the temperate realm remain poorly understood and may have resulted from evolutionary dynamics related to diversification rates, dispersal rates, and colonization times, closely coupled with Cenozoic climate change. We integrated phylogenomic, environmental ordination, and macroevolutionary analyses for the cosmopolitan angiosperm family Rhamnaceae to disentangle the evolutionary processes that have contributed to high species diversity within and across temperate biomes. Our results show independent colonization of environmentally similar but geographically separated temperate regions mainly during the Oligocene, consistent with the global expansion of temperate biomes. High global, regional, and local temperate diversity was the result of high in situ diversification rates, rather than high immigration rates or accumulation time, except for Southern China, which was colonized much earlier than the other regions. The relatively common lineage dispersals out of temperate hotspots highlight strong source-sink dynamics across the cosmopolitan distribution of Rhamnaceae. The proliferation of temperate environments since the Oligocene may have provided the ecological opportunity for rapid in situ diversification of Rhamnaceae across the temperate realm. Our study illustrates the importance of high in situ diversification rates for the establishment of modern temperate biomes and biodiversity hotspots across spatial scales.

Current Status and Future Direction of Albumin-Bilirubin in Hepatocellular Carcinoma: A Bibliometric Analysis.

INTRODUCTION: Hepatocellular carcinoma (HCC) is a common malignant tumor, so we need a convenient and objective way to diagnose and treat HCC. We discuss the current situation, progress, hotspots, and existing problems of Albumin-Bilirubin (ALBI) in HCC, which can provide new ideas for the prevention, diagnosis, and treatment of HCC. METHODS: We adopt Excel 2019 software and visual analysis tools based on Web of Science database search. This manuscript uses VOSviewer, Co-Occurrence13.3 (COOC13.3) software to conduct overall trend analysis, synonym merging, frequency of countries, journals, institutions, funds, dissimilarity matrices, co-occurrence matrices, bimodal matrices, coupling matrices, cluster analysis of topic evolution time zone graphs. RESULTS: A total of 610 papers were included, and the number of papers output showed an overall upward trend. ALBI has been valued by the industry in HCC and plays an important role in diagnosing and treating HCC, even better than the classic Child-Pugh (C-P) grade. At the same time, hot spots in the treatment of HCC and other applications of ALBI were discovered. CONCLUSION: ALBI score is a convenient and objective liver function evaluation index, which plays an important role in the prediction of patient survival rate and prognosis. Promoting the ALBI score in HCC can help doctors judge the patient's condition and improve the diagnosis and precise treatment effect.

Dry-Cleaning Chemicals and a Cluster of Parkinson's Disease and Cancer: A Retrospective Investigation.

BACKGROUND: Environmental exposure to trichloroethylene (TCE), a carcinogenic dry-cleaning chemical, may be linked to Parkinson's disease (PD). OBJECTIVE: The objective of this study was to determine whether PD and cancer were elevated among attorneys who worked near a contaminated site. METHODS: We surveyed and evaluated attorneys with possible exposure and assessed a comparison group. RESULTS: Seventy-nine of 82 attorneys (96.3%; mean [SD] age: 69.5 [11.4] years; 89.9% men) completed at least one phase of the study. For comparison, 75 lawyers (64.9 [10.2] years; 65.3% men) underwent clinical evaluations. Four (5.1%) of them who worked near the polluted site reported PD, more than expected based on age and sex (1.7%; P = 0.01) but not significantly higher than the comparison group (n = 1 [1.3%]; P = 0.37). Fifteen (19.0%), compared to four in the comparison group (5.3%; P = 0.049), had a TCE-related cancer. CONCLUSIONS: In a retrospective study, diagnoses of PD and TCE-related cancers appeared to be elevated among attorneys who worked next to a contaminated dry-cleaning site. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Microgeographic speciation in a complex of Anatolian bush crickets facilitated by fast evolution of reproductive isolation.

Identifying the drivers of microgeographic speciation (i.e., speciation over small, local geographic scales) is key to understand the origin of speciose groups. Here, we use genomic data to infer the demographic processes underlying diversification in Poecilimon luschani (Orthoptera: Tettigoniidae), a species complex belonging to the most diverse genus of bush crickets from the Mediterranean region (>170 taxa) that comprises three recognized subspecies with small allopatric distributions in the topographically complex Teke Peninsula, southwestern Anatolia. Phylogenomic reconstructions that include all other taxa within the species group confirmed that subspecies of P. luschani originated from a common ancestor during the Pleistocene, supporting recent (<1 Ma) diversification within a small geographical area (ca. 120 × 80 km). Genetic clustering analyses corroborated the distinctiveness of each subspecies and the cohesiveness of their respective populations, with abrupt genetic discontinuities coinciding with contemporary range boundaries. Indeed, our analyses uncovered the presence of two sympatric cryptic sister lineages that diverged <300 ka ago and do not admix despite being co-distributed. Collectively, these results support that all lineages within the complex represent independently evolving entities corresponding to full-fledged species. Statistical evaluation of alternative models of speciation strongly supports a scenario of divergence in isolation followed by a period of limited gene flow during the last glacial period, when all lineages experienced marked expansions according to demographic reconstructions. Our study exemplifies how localized allopatric divergence and fast evolution of reproductive isolation can promote microgeographic speciation and explain the high rates of endemism characterizing biodiversity hotspots.

TP53 mutations and the association with platinum resistance in high grade serous ovarian carcinoma.

OBJECTIVES: Alterations in the tumor suppressor TP53 gene are the most common mutations in high grade serous ovarian carcinoma. The impact of TP53 mutations on clinical outcomes and platinum resistance is controversial. We sought to evaluate the genomic profile of high grade serous ovarian carcinoma and explore the association of TP53 mutations with platinum resistance. METHODS: Next generation sequencing data was obtained from our institutional database for patients with high grade serous ovarian carcinoma undergoing primary treatment. Sequencing data, demographic, and clinical information was reviewed. The primary outcome analyzed was time to recurrence or refractory diagnosis. Associations between the primary outcome and different classification schemes for TP53 mutations (structural, functional, hot spot, pathogenicity scores, immunohistochemical staining patterns) were performed. RESULTS: 209 patients met inclusion criteria. TP53 mutations were the most common mutation. There were no differences in platinum response with TP53 hotspot mutations or high pathogenicity scores. Presence of TP53 gain-of-function mutations or measure of TP53 gain-of function activity were not associated with platinum resistance. Immunohistochemical staining patterns correlated with expected TP53 protein function and were not associated with platinum resistance. CONCLUSIONS: TP53 hotspot mutations or high pathogenicity scores were not associated with platinum resistance or refractory disease. Contrary to prior studies, TP53 gain-of-function mutations were not associated with platinum resistance. Estimation of TP53 gain-of-function effect using missense mutation phenotype scores was not associated with platinum resistance. The polymorphic nature of TP53 mutations may be too complex to demonstrate effect using simple models, or response to platinum therapy may be independent of initiating TP53 mutation.

Heterogeneity in Arbuscular Mycorrhizal Fungi and Plant Communities of the Brazilian Cerrado, Transitional Areas toward the Caatinga, and the Atlantic Forest.

The Cerrado is the most diverse tropical savanna worldwide and the second-largest biome in South America. The objective of this study was to understand the heterogeneity and dynamics of arbuscular mycorrhizal fungi (AMF) in different types of natural Cerrado vegetation and areas that are transitioning to dryer savannas or tropical rainforests and to elucidate the driving factors responsible for the differences between these ecosystems. Twenty-one natural sites were investigated, including typical Cerrado forest, typical Caatinga, Atlantic Rainforest, transitions between Cerrado and Caatinga, Cerrado areas near Caatinga or rainforest, and Carrasco sites. Spores were extracted from the soils, counted, and morphologically analyzed. In total, 82 AMF species were detected. AMF species richness varied between 36 and 51, with the highest richness found in the area transitioning between Cerrado and Caatinga, followed by areas of Cerrado close to Caatinga and typical Cerrado forest. The types of Cerrado vegetation and the areas transitioning to the Caatinga shared the highest numbers of AMF species (32-38). Vegetation, along with chemical and physical soil parameters, affected the AMF communities, which may also result from seasonal rainfall patterns. The Cerrado has a great AMF diversity and is, consequently, a natural refuge for AMF. The plant and microbial communities as well as the diversity of habitats require urgent protection within the Cerrado, as it represents a key AMF hotspot.