Co-occurrence Patterns Research Articles

Seasonal infestation patterns of ticks on Hokkaido sika deer (Cervus nippon yesoensis).

Ticks prefer specific feeding sites on a host that are influenced by host–tick and tick–tick interactions. This study focused on the spatiotemporal distribution of ticks in Hokkaido sika deer, an important tick host in Hokkaido, Japan. Tick sampling was performed on the sika deer in the Shiretoko National Park between June and October 2022. Ticks were collected from 9 different body parts of the deer to compare their attachment site preferences. Interspecific and intraspecific relationships among ticks were examined using co-occurrence analysis. The collected ticks were nymphal and adult stages of 4 species: Ixodes ovatus, Ixodes persulcatus, Haemaphysalis japonica and Haemaphysalis megaspinosa. Seasonal variations in tick burden were observed, with I. persulcatus and I. ovatus peaking in June and declining towards October; H. japonica showing low numbers in July and August and increasing from September; and H. megaspinosa appearing from September onwards with little variation. Attachment site preferences varied among species, with a significant preference for the pinna in I. ovatus and I. persulcatus. Haemaphysalis japonica was mainly found on the body and legs between June and August, and shifted to the pinna from September. Haemaphysalis megaspinosa showed a general preference for areas other than the legs. Co-occurrence analysis revealed positive, negative and random co-occurrence patterns among the tick species. Ticks of the same genus and species exhibited positive co-occurrence patterns; I. ovatus showed negative co-occurrence patterns with Haemaphysalis spp. This study revealed the unique attachment site preferences and distinct seasonal distributions of tick species in the Hokkaido sika deer.

Characteristics of soil microbial community assembly patterns in fields with serious occurrence of tobacco Fusarium wilt disease

IntroductionFusarium wilt disease (FWD) of tobacco is a destructive disease caused by Fusarium spp. in tobacco-growing regions worldwide. The Fusarium spp. infection may alter the composition and structure of the tobacco root microbial community; however, the relationship between these factors under large-scale geographical conditions in China remains underexplored.MethodsIn the context of this investigation, soil samples from the rhizosphere of tobacco plants were procured from fields afflicted with FWD and those devoid of the disease in the Hanzhong region of Shaanxi province, as well as in the Sanmenxia and Nanyang regions of Henan province. These regions are recognized for the commercial cultivation of tobacco. The examination focused on discerning the influence of tobacco FWD on the composition and configuration of the rhizosphere microbial community, along with their co-occurrence patterns. This scrutiny was underpinned by targeted PCR amplification and high-throughput sequencing (amplicon sequencing) of the 16S rRNA gene and the ITS1 region.ResultsThe amplicon data analyses showed that FWD influenced the microbial structure and composition of the tobacco rhizosphere soil. FWD had a greater impact on the microbiome of the tobacco fungal community than on the microbiome of the bacterial community. Healthy plants had the ability to recruit potential beneficial bacteria. Diseased plants were more susceptible to colonization by other pathogenic fungi, but they still had the capacity to recruit potential beneficial bacteria. The analysis of microbial intra- and inter-kingdom networks further indicated that FWD destabilized microbial networks. In the overall microbial interaction, microorganisms primarily interacted within their boundaries, but FWD increased the proportion of interactions occurring across boundaries. In addition, FWD could disrupt the interactions within microbial network modules.DiscussionThis study provides evidence that FWD can cause changes in the composition and network of microbial communities, affecting the interactions among various microorganisms, including bacteria and fungi. These findings contribute to our understanding of how plant microbiomes change due to disease. Furthermore, they add to our knowledge of the mechanisms that govern the assembly and interactions of microbial communities under the influence of FWD.

Functional characteristics and computational model of abundant hyperactive loci in the human genome.

Enhancers and promoters are classically considered to be bound by a small set of transcription factors (TFs) in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract hundreds of TFs with often no detectable correlation between ChIP-seq peaks and DNA-binding motif presence. Here, we used a set of 1003 TF ChIP-seq datasets (HepG2, K562, H1) to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We identified 43,891 HOT loci forming at the promoter (53%) and enhancer (47%) regions. HOT promoters regulate housekeeping genes, whereas HOT enhancers are involved in tissue-specific process regulation. HOT loci form the foundation of human super-enhancers and evolve under strong negative selection, with some of these loci being located in ultraconserved regions. Sequence-based classification analysis of HOT loci suggested that their formation is driven by the sequence features, and the density of mapped ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. Based on the affinities to bind to promoters and enhancers we detected five distinct clusters of TFs that form the core of the HOT loci. We report an abundance of HOT loci in the human genome and a commitment of 51% of all TF ChIP-seq binding events to HOT locus formation thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.

Functional characteristics and computational model of abundant hyperactive loci in the human genome

Enhancers and promoters are classically considered to be bound by a small set of transcription factors (TFs) in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract hundreds of TFs with often no detectable correlation between ChIP-seq peaks and DNA-binding motif presence. Here, we used a set of 1003 TF ChIP-seq datasets (HepG2, K562, H1) to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We identified 43,891 HOT loci forming at the promoter (53%) and enhancer (47%) regions. HOT promoters regulate housekeeping genes, whereas HOT enhancers are involved in tissue-specific process regulation. HOT loci form the foundation of human super-enhancers and evolve under strong negative selection, with some of these loci being located in ultraconserved regions. Sequence-based classification analysis of HOT loci suggested that their formation is driven by the sequence features, and the density of mapped ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. Based on the affinities to bind to promoters and enhancers we detected five distinct clusters of TFs that form the core of the HOT loci. We report an abundance of HOT loci in the human genome and a commitment of 51% of all TF ChIP-seq binding events to HOT locus formation thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.

Microbial diversity in the arid and semi-arid soils of Botswana.

To date, little research has been conducted on the landscape-scale distribution of soil microbial communities and the factors driving their community structures in the drylands of Africa. We investigated the influence of landscape-scale variables on microbial community structure and diversity across different ecological zones in Botswana. We used amplicon sequencing of bacterial 16S rRNA gene and fungal internal transcribed spacers (ITS) and a suite of environmental parameters to determine drivers of microbial community structure. Bacterial communities were dominated by Actinomycetota (21.1%), Pseudomonadota (15.9%), and Acidobacteriota (10.9%). The dominant fungal communities were Ascomycota (57.3%) and Basidiomycota (7.5%). Soil pH, mean annual precipitation, total organic carbon, and soil ions (calcium and magnesium) were the major predictors of microbial community diversity and structure. The co-occurrence patterns of bacterial and fungal communities were influenced by soil pH, with network-specific fungi-bacteria interactions observed. Potential keystone taxa were identified for communities in the different networks. Most of these interactions were between microbial families potentially involved in carbon cycling, suggesting functional redundancy in these soils. Our findings highlight the significance of soil pH in determining the landscape-scale structure of microbial communities in Botswana's dryland soils.

PATH-54. HIGH-THROUGHPUT SINGLE NUCLEAR DNA SEQUENCING OF HUMAN SPORADICNF1 MUTANT IDH-WILDTYPE GLIOBLASTOMAS REVEALS PATTERNS OF TUMOR EVOLUTION AND RECURRENCE

Abstract The advent of single cell techniques has advanced our understanding of glioblastoma (GBM) evolution and cell lineage relationships. However, study of mutational co-occurrence and clonal phylogeny has been hampered by limitations in single cell genotyping. Here, we perform semi-automated, rapid single nuclear dissociation followed by targeted single nucleus DNA sequencing (snDNA-seq) of eleven retrospectively identified somatic NF1 mutant IDH-wildtype glioblastomas. Bulk DNA sequencing was performed as part of routine clinical care using a CLIA-certified targeted sequencing panel. For snDNA-seq, tissue cores with greater than 30% tumor were dissociated on a S2 genomics S100 Singulator followed by snDNA-seq using a targeted 361 amplicon panel (Tapestri, Mission Bio, USA) to sequence for recurrently observed single nucleotide substitutions and copy number alterations. A mean of 3,661 cells were recovered per sample with a mean of 96 reads per cell per amplicon and 87% mean panel uniformity. SnDNA-seq validated point mutations and copy number alterations observed in bulk DNA-sequencing and revealed novel alterations and subclonal copy number alterations not detected on bulk analysis. Within individual samples, snDNA-seq based phylogenetic reconstruction identified mutually exclusive patterns of mutation between NF1 and PI3K signaling alterations, suggesting these events may occur in distinct tumor subclones. With regard to copy number alterations (CNAs), snDNA-seq demonstrated intra-tumoral heterogeneity for chromosome 9p loss, chromosome 7 gain, and chromosome 10 monosomy. Subclonal CNA clones not detected by bulk sequencing were identified in 5 samples. Analysis of a matched primary-recurrent tumor pair revealed expansion of a specific mutational clone (loss of 9p, 10p, gains of 1p, 7, 15, and 19q) at recurrence. SnDNA-seq recapitulated bulk DNA sequencing alterations and identified distinct patterns of mutational co-occurrence, CNAs, and tumor evolution over time. Reconstructing GBM phylogeny at single cell resolution has potential translational implications for understanding tumor evolution and treatment resistance.

NIMG-60. SUBTYPING GLIOBLASTOMA FROM JOINT CLUSTERING OF IMAGING AND GENOMIC DATA

Abstract PURPOSE To comprehensively unravel the heterogeneity of glioblastoma, we developed a subtyping method using integrated imaging and genomic data. METHODS We assembled a retrospective cohort of 571 IDH-wildtype glioblastoma patients, obtaining pre-operative multi-parametric MRI (T1, T1-GD, T2, T2-FLAIR, DSC, DTI) scans (available for 462 patients) and targeted next-generation sequencing (NGS) data (available for 355 patients). We extracted 971 radiomic features from these MRI scans, selecting 12 significant dimensions through L21-norm minimization guided by 13 key driver genes from the five most frequently altered pathways in glioblastoma compared to healthy controls (RB1, P53, MAPK, PI3K, and RTK). Subtypes were identified using a joint clustering approach that integrated radiomics and genomics. RESULTS Our method identified three glioblastoma subtypes with distinct risk levels: high-risk (subtype 1), medium-risk (subtype 2), and low-risk (subtype 3), each characterized by their differential overall survival outcomes (Kaplan-Meier analysis, p < 0.05). The intensities of axial diffusivity in enhancing tumor regions and radial diffusivity in non-enhancing cores increased across three subtypes. All subtypes shared a common tendency for more frequent mutation co-occurrence pattern in [TP53,RB1] but exhibited unique molecular characteristics. For example, subtype 1 displayed a relatively high frequency of co-occurring mutations in [TP53,KDR] and [NOTCH2,MDM4]; subtype 2 had six co-occurring pairs [TP53,KDR], [PTPN11,NF1], [RB1,FUBP1], [PTEN,CIC], [PTEN,KRAS], and [NOTCH2,CDKN2A]; subtype 3 showed six co-occurring pairs [PTPN11,NF1], [PDGFRA,NF1], [NTRK1,NOTCH2], [MET,ATRX], [KRAS,KDR], and [FGFR2,DNMT3A] plus four significant patterns of mutual exclusivity in [TP53,PTPN11], [TP53,EGFR], [EGFR,RB1], and [EGFR,NF1]. CONCLUSION Our study discovered distinct glioblastoma subtypes, revealing complex patterns and structures across multiple data modalities without relying on prior clinical assumptions. This is promising to help enhance the precision of diagnosis and treatment of glioblastoma.

Soil P-stimulating bacterial communities: response and effect assessment of long-term fertilizer and rhizobium inoculant application

BackgroundPhosphorus (P) plays a vital role in plant growth. The pqqC and phoD genes serve as molecular markers for inorganic and organic P breakdown, respectively. However, the understanding of how P-mobilizing bacteria in soil respond to long-term fertilization and rhizobium application is limited. Herein, soil that had been treated with fertilizer and rhizobium for 10 years was collected to investigate the characteristics of P-mobilizing bacterial communities. Five treatments were included: no fertilization (CK), phosphorus fertilizer (P), urea + potassium fertilizer (NK), NPK, and PK + Bradyrhizobium japonicum 5821 (PK + R).ResultsThe soybean nodule dry weight was highest in the P treatment (1.93 g), while the soybean yield peaked in the PK + R treatment (3025.33 kg ha− 1). The abundance of the pqqC gene increased in the rhizosphere soil at the flowering-podding stage and in the bulk soil at the maturity stage under the P treatment, while its abundance increased in the bulk soil at the flowering-podding stage and in the rhizosphere soil at the maturity stage under the PK + R treatment. The abundance of the phoD gene was enhanced in the bulk soil at the flowering-podding stage under the PK + R treatment. The Shannon and Ace indexes of pqqC- and phoD-harboring bacteria were higher in the rhizosphere soil at maturity under the PK + R treatment compared to other treatments. Furthermore, a comprehensive analysis of the neutral community model and co-occurrence pattern demonstrated that the application of P fertilizer alone led to an increase in the distribution and dynamic movement of pqqC-harboring bacteria, but resulted in a decrease in complexity of network structure. On the other hand, rhizobium inoculation enhanced the distribution and dynamic movement of phoD-harboring bacteria, as well as the stability and complexity of the network structure. Pseudomonas and Nitrobacter, as well as Steptomyces, Stella, and Nonomuraea, may be crucial genera regulating the composition and function of pqqC- and phoD-harboring communities, respectively.ConclusionsThese findings affirm the crucial role of fertilization and rhizobium inoculation in regulating pqqC- and phoD-harboring bacterial communities, and highlight the significance of long-term phosphate-only fertilization and rhizobium inoculation in enhancing dissolved inorganic phosphorus and mineralized organophosphorus, respectively.

Energizing innovation: a bibliometric exploration of renewable energy entrepreneurship

Purpose This study aims to provide a thorough bibliometric analysis to illuminate the complex entrepreneurial environment in renewable energy. Design/methodology/approach The Biblioshiny package of the R programming language was considered for in-depth analysis of the papers. To determine the future course of research, the authors use SciVal data and prominence percentiles related to particular study areas. Findings The findings show a growing interest in renewable energy entrepreneurship, as seen by rising annual production and citation rates. By revealing the interconnection of themes throughout the subject, keyword co-occurrence patterns illustrate its interdisciplinary nature. Sustainable development goal alignment highlights the field’s critical role in tackling global sustainability issues. This analysis gives researchers, decision-makers and practitioners a framework for navigating the terrain of renewable energy entrepreneurship. Practical implications Practical advice for promoting innovation and sustainability in the renewable energy sector is provided through insights into interdisciplinary intersections and sustainability alignment. Originality/value This paper adds to the body of literature by providing a comprehensive analysis of renewable energy entrepreneurship and highlighting how it affects sustainability. Including SciVal data with prominence percentiles suggests future research avenues and highlights the field’s originality and importance.

Niche-specific evolution and gene exchange of Salmonella in retail pork and chicken

Salmonella exhibits extensive genetic diversity, facilitated by horizontal gene transfer occurring within and between species, playing a pivotal role in this diversification. Nevertheless, most studies focus on clinical and farm animal isolates, and research on the pangenome dynamics of Salmonella isolates from retail stage of the animal food supply chain is limited. Here, we investigated the genomes of 950 Salmonella isolates recovered from retail chicken and pork meats in seven provinces and one municipality of China in 2018. We observed a strong correlation between Salmonella sublineage diversity and the accessory genome with meat type, revealing reduced diversity associated with increased resistance. Importantly, genes associated with antibiotic, biocide, and heavy metal resistance were unevenly distributed in Salmonella from retail chicken and pork. Pork Salmonella isolates showed a higher prevalence of copper and silver resistance genes, while chicken Salmonella isolates displayed a significant predominance of genetic determinants associated with cephalosporin and ciprofloxacin resistance. Moreover, co-occurrence patterns of resistance determinants and their interaction with mobile genetic elements also correlated with meat type. In summary, our findings shed light on how Salmonella achieves their ecological niche success driven by evolution and gene changes in the retail stage of the animal food supply chain.

Analysis of 2019 Ohio Disease Intervention Specialist (DIS) Records for Syphilis Cases Using Clustering Algorithms.

Developments in natural language processing (NLP) and unsupervised machine learning methodologies (e.g., clustering) have given researchers new tools to analyze both structured and unstructured health data. We applied these methods to 2019 Ohio disease intervention specialist (DIS) syphilis records, to determine whether these methods can uncover novel patterns of co-occurrence of individual characteristics, risk factors, and clinical characteristics of syphilis that are not yet reported in the literature. The 2019 DIS syphilis records (n=1,996) contain both structured data (categorical and numerical variables) and unstructured notes. In the structured data, we examined case demographics, syphilis risk factors, and clinical characteristics of syphilis. For the unstructured text, we applied TF-IDF (term frequency multiplied by inverse document frequency) weights, a common way to convert text into numerical representations. We performed agglomerative clustering with cosine similarity using the CLUTO software. The cluster analysis yielded six clusters of syphilis cases based on patterns in the structured and unstructured data. The average internal similarities were much higher than the average external similarities, indicating that the clusters were well-formed. The factors underlying three of the clusters related to patterns of missing data. The factors underlying the other three clusters were sexual behaviors and partnerships. Notably, one of the three consisted of individuals who reported oral sex with male or anonymous partners while intoxicated, and one was comprised mainly of males who have sex with females. Our analysis resulted in clusters that were well-formed mathematically, but did not reveal novel epidemiological information about syphilis risk factors or transmission that were not already known.

Co-Occurrence Patterns Do Not Predict Mutualistic Interactions Between Plant and Butterfly Species.

Biotic interactions are crucial for determining the structure and dynamics of communities; however, direct measurement of these interactions can be challenging in terms of time and resources, especially when numerous species are involved. Inferring species interactions from species co-occurrence patterns is increasingly being used; however, recent studies have highlighted some limitations. To our knowledge, no attempt has been made to test the accuracy of the existing methods for detecting mutualistic interactions in terrestrial ecosystems. In this study, we compiled two literature-based, long-term datasets of interactions between butterflies and herbaceous plant species in two regions of Germany and compared them with observational abundance and presence/absence data collected within a year in the same regions. We tested how well the species associations generated by three different co-occurrence analysis methods matched those of empirically measured mutualistic associations using sensitivity and specificity analyses and compared the strength of associations. We also checked whether flower abundance data (instead of plant abundance data) increased the accuracy of the co-occurrence models and validated our results using empirical flower visitation data. The results revealed that, although all methods exhibited low sensitivity, our implementation of the Relative Interaction Intensity index with pairwise null models performed the best, followed by the probabilistic method and Spearman's rank correlation method. However, empirical data showed a significant number of interactions that were not detected using co-occurrence methods. Incorporating flower abundance data did not improve sensitivity but enhanced specificity in one region. Further analysis demonstrated incongruence between the predicted co-occurrence associations and actual interaction strengths, with many pairs exhibiting high interaction strength but low co-occurrence or vice versa. These findings underscore the complexity of ecological dynamics and highlight the limitations of current co-occurrence methods for accurately capturing species interactions.

Distribution of protoporphyrin IX during Prorocentrum donghaiense blooms and its relationship with particle-attached and free-living bacterial communities

Particle-attached (PA) and free-living (FL) bacterial communities are essential for nutrient cycles and metabolite production and serve as a food source in aquatic systems. However, our understanding of how biotic factors influence community interactions, co-occurrence patterns, and niche occupancy remains limited. This study investigated the influence of protoporphyrin IX (PPIX) on bacteria with different lifestyles during Prorocentrum donghaiense bloom. The findings revealed that PPIX distribution responded variably to changes in physicochemical parameters induced by red tide bloom. Large-sized or particle-attached (PA) phytoplankton (cell size >3 μm) were identified as the primary contributors to environmental PPIX, while small-sized plankton or free-living (FL) microorganisms (<3 μm) contributed less. In red tide-affected areas, PPIX and its derivatives were significantly more abundant than in non-red tide areas, indicating an increased demand for porphyrins by plankton during red tides. Additionally, the red tide also significantly influenced the preference of bacterial lineages for PA or FL lifestyles, highlighting a close interaction between bacteria with different lifestyles and PPIX levels. This study quantitatively analyzed the distribution of PPIX across different cell sizes in red tide and non-red tide marine environments, providing insights into microbial interactions and dynamics in changing ecosystems and offering a reference for using PPIX to predict red tide ecological disasters.

Microbial Community Analysis Offers Insight into the Complex Origins of Plant Disease in a Smallholder Farm Context

Classical approaches to plant disease diagnosis assume a single pathogen/single disease paradigm. Here, we revisit the presumed role of Fusarium oxysporum as the causal agent of wilting and yellowing of chickpea plants on smallholder farms in Ethiopia. Contrary to expectations, detection of Fusarium DNA using conserved PCR primers failed to associate the pathogen with symptomatic plants. Instead, culture-independent sequencing of microbial communities nominated unexpected pathogens and revealed patchiness in the assembly of common microbial consortia. Surprisingly, tests of differential enrichment identified Phytophthora as the most common disease-associated taxon. More generally, across all field sites, multilevel pattern analysis identified indicator taxa whose patterns of co-occurrence demarcate discrete microbial communities and are consistent with a range of specific interactions, including mutualism and antagonism. Taken together, these data indicate that soilborne chickpea disease in Ethiopia has heterogeneous origins and that despite decades of emphasis and disease resistance breeding, the role of Fusarium as the frequent agent of chickpea disease in Ethiopia remains enigmatic.

Discovering the common latent structure of commercial districts focusing on the spatial co-occurrence relationship between stores

Store agglomeration in a commercial district is considered to follow synergistic and complementary relationships between stores. The micro-interactions, that is, co-occurrence relationships, between stores are thought to create commercial districts’ universality and characteristics. This study aims to empirically identify latent attributes that can explain the mechanism of store agglomeration from the co-occurrence relationships between stores in commercial districts, and to identify universal characteristics in store agglomeration. We represented store agglomeration as a store co-occurrence network with stores as nodes and co-occurrence relationships between stores as links in 10 major commercial districts in Japan. We estimated latent attributes of stores that generated the store co-occurrence network and empirically clarified the quantitative and qualitative nature of store agglomeration. The co-occurrence networks of stores with estimated latent attributes were compared across those of districts, and the co-occurrence patterns common to latent attributes were clarified. The estimated latent attributes were empirically shown to have more explanatory power for the store agglomeration than the conventional business category classification, suggesting their usefulness as a new classification axis for stores. In addition, by comparing 10 districts, common co-occurrence relationships were extracted, and the universal spatial structure of store agglomeration was empirically clarified.

Linguistic variation in mediated diplomatic communication: a full multi-dimensional analysis of interpreted language in Chinese Regular Press Conferences

The integration of corpus linguistics within translation studies has revolutionised our understanding of mediated language. This study endeavours to advance this burgeoning field by employing a full multi-dimensional analysis to investigate linguistic variation in interpreted language within the specialised context of diplomatic discourse. Specifically, the research examines the co-occurring patterns of linguistic features in interpreted diplomatic language vis-à-vis its non-interpreted counterpart. Employing a multivariate statistical technique, this investigation conducted a factor analysis of 113 linguistic variables, yielding five distinct linguistic dimensions: (1) Involved vs. Informational Production, (2) Objective vs. Addressee-focused Narration, (3) Literate-Oral Continuum, (4) Information Elaboration, and (5) Narrative vs. Non-narrative Concerns. The resulting patterns demonstrate that interpreted diplomatic language tends to be more informative, objective, less elaborated, non-narrative, and aligns more closely with formal registers compared to its non-interpreted counterpart, although both navigate the literate-oral continuum. This study delineates the prevailing co-occurrence patterns in interpreted and non-interpreted diplomatic languages and seeks to elucidate the potential factors shaping these linguistic variations by situating these patterns within the context of diplomatic communication. In doing so, it contributes to a nuanced understanding of how specialised contexts influence mediated language use. The findings have significant implications for corpus-based interpreting studies, shedding light on the multi-dimensional nature of interpreted language and informing the development of targeted pedagogical approaches for diplomatic interpreter training.

Skin Bacterial and Fungal Microbiome Responses to Diet Supplementation and Rewilding in the Critically Endangered Southern Corroboree Frog.

The composition and dynamics of the skin bacterial and fungal microbiome is thought to influence host-pathogen defence. This microbial community is shaped by host captivity, diet, and microbial interactions between bacterial and fungal components. However, there remains little understanding of how specific micronutrients influence bacterial and fungal microbiome composition and their inter-domain interactions during rewilding of captive-bred animals. This study experimentally investigated the effect of dietary beta-carotene supplementation and subsequent field release on bacterial and fungal microbiome composition and dynamics using the Southern Corroboree frog (Pseudophryne corroboree) as a model system. We found large-scale diversification of bacterial communities post-release and similar diversification of fungal communities. The rewilded fungal mycobiome was more transient and demonstrated stronger temporal and micro-spatial fluctuations than the bacterial microbiome. Accounting for temporal and spatial factors, we found strong residual associations between bacterial members, yet limited evidence for inter-domain associations, suggesting that co-occurrence patterns between bacterial and fungal communities are largely a result of shared responses to the environment rather than direct interactions. Lastly, we found supplementation of dietary beta-carotene in captivity had no impact on post-release microbiome diversity, yet was associated with approximately 15% of common bacterial and fungal genera. Our research demonstrates that environmental factors play a dominant role over dietary beta-carotene supplementation in shaping microbiome diversity post-release, and suggest inter-domain interactions may also only exert a minor influence. Further research on the function and ecology of skin bacterial and fungal microbiomes will be crucial for developing strategies to support survival of endangered amphibian species.

Agricultural practices influence soil microbiome assembly and interactions at different depths identified by machine learning

Agricultural practices affect soil microbes which are critical to soil health and sustainable agriculture. To understand prokaryotic and fungal assembly under agricultural practices, we use machine learning-based methods. We show that fertility source is the most pronounced factor for microbial assembly especially for fungi, and its effect decreases with soil depths. Fertility source also shapes microbial co-occurrence patterns revealed by machine learning, leading to fungi-dominated modules sensitive to fertility down to 30 cm depth. Tillage affects soil microbiomes at 0-20 cm depth, enhancing dispersal and stochastic processes but potentially jeopardizing microbial interactions. Cover crop effects are less pronounced and lack depth-dependent patterns. Machine learning reveals that the impact of agricultural practices on microbial communities is multifaceted and highlights the role of fertility source over the soil depth. Machine learning overcomes the linear limitations of traditional methods and offers enhanced insights into the mechanisms underlying microbial assembly and distributions in agriculture soils.

Niche divergence mechanisms of closely related hybridising bird species. Modeling approach based on remote sensing data of forest habitats

Describing mechanisms that ensure stable co-occurrence of sympatric species is fundamental to understanding the complexity of ecological community dynamics. In this study, the Pied flycatcher and the Collared flycatcher were used as model species for the analysis of co-occurrence patterns of closely related hybridising species that inhabit overlapping forest habitats. I hypothesise that spatial niche partitioning between species emerges as a vital adaptive response to interspecific competition and manifests itself in significant shifts in habitat preferences in syntopic areas but not in the allotopic ones. The study leverages a comprehensive dataset that includes species density in 372 randomly selected 1 km² grid cells across the territory of Poland. The analysis of habitat preferences was performed with linear mixed-effect modeling, whereas a contrast analysis was used to investigate changes in habitat preferences resulting from the presence of a competitor. The findings indicate that both species modify their habitat preferences when transitioning between syntopic and allotopic sites. Remarkably, in regions without competitors, such shifts are significantly less pronounced, as demonstrated by the Pied flycatcher that prefers the same habitats both in allopatric regions and allotopic sites. When these results are compared with other studies on closely related hybridising and non-hybridising species, it turns out that what influences the degree and number of niches subjected to competition is the time that passes from species divergence. This study highlights the imperative need to incorporate co-occurrence parameters of closely related species into niche and species distribution models to enhance their ecological realism.

Glacier Retreat Induces Contrasting Shifts in Bacterial Biodiversity Patterns in Glacial Lake Water and Sediment

Glacial lake ecosystems are experiencing rapid changes due to accelerated glacier retreat. As glaciers recede, their influence on downstream habitats diminishes, potentially affecting the biodiversity of glacial lake microbial communities. However, there remains a knowledge gap regarding how bacterial biodiversity patterns in glacial lakes are altered by diminishing glacial influence. Here, we investigated shifts in bacterial communities in paired water and sediment samples collected from seven glacial lakes on the Tibetan Plateau, using a space-for-time substitution approach to understand the consequences of glacier retreat. Our findings reveal that bacterial diversity in lake water increases significantly with a higher glacier index (GI), whereas sediment bacterial diversity exhibits a negative correlation with GI. Both the water and sediment bacterial communities display significant structural shifts along the GI gradient. Notably, reduced glacial influence decreases the complexity of bacterial co-occurrence networks in lake water but enhances the network complexity in sediment. This divergence in diversity and co-occurrence patterns highlights that water and sediment bacterial communities respond differently to changes in glacial influence in these lake ecosystems. This study provides insights into how diminishing glacial influence impacts the bacterial biodiversity in glacial lake water and sediments, revealing contrasting patterns between the two habitats. These findings emphasize the need for comprehensive monitoring to understand the implications of glacier retreat on these fragile ecosystems.