Permutational Analysis Research Articles

Characterization of the transcriptional effects of the plastic additive dibutyl phthalate alone and in combination with microplastic on the green-lipped mussel Perna canaliculus.

The presence and persistence of microplastics (MPs) in diverse aquatic environments are of global concern. Microplastics can impact marine organisms via direct physical interaction and the release of potentially harmful chemical additives incorporated into the plastic. These chemicals are physically bound to the plastic matrix and can leach out. The hazards associated with chemical additives to exposed organisms is not well characterized. We investigated the hazards of plastic additives leaching from plastic. We used the common plasticizer dibutyl phthalate (DBP) as a chemical additive proxy and the New Zealand green-lipped mussel (Perna canaliculus) as a model. We used early-adult P. canaliculus exposed to combinations of virgin and DBP-spiked polyvinyl chloride (PVC), MPs, and DBP alone for 7 days. Whole transcriptome sequencing (RNA-seq) was conducted to assess whether leaching of DBP from MPs poses a hazard. The differences between groups were evaluated using pairwise permutational multivariate analysis of variance (PERMANOVA), and all treatments were significantly different from controls. In addition, a significant difference was seen between DBP and PVC MP treatment. Transcriptome analysis revealed that mussels exposed to DBP alone had the most differentially expressed genes (914), followed by PVC MP + DBP (448), and PVC MP (250). Gene ontology functional analysis revealed that the most enriched pathway types were in cellular metabolism, immune response, and endocrine disruption. Microplastic treatments enriched numerous pathways related to cellular metabolism and immune response. The combined exposure of PVC MP + DBP appears to cause combined effects, suggesting that DBP is bioavailable to the exposed mussels in the PVC MP + DBP treatment. Our results support the hypothesis that chemical additives are potentially an important driver of MP toxicity. Environ Toxicol Chem 2024;43:1604-1614. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Association of the oral microbiome with cognitive function among older adults: NHANES 2011–2012

BackgroundAn association between the gut microbiome and cognitive function has been demonstrated in prior studies. However, whether the oral microbiome, the second largest microbial habitant in humans, has a role in cognition remains unclear. Design, setting, participantsUsing weighted data from the 2011 to 2012 National Health and Nutrition Examination Survey, we examined the association between oral microbial composition and cognitive function in older adults. The oral microbiome was characterized by 16S ribosomal RNA gene sequencing. Cognitive status was assessed using the Consortium to Establish a Registry for Alzheimer’s Disease immediate recall and delayed recall, Animal Fluency Test, and Digit Symbol Substitution Test (DSST). Subjective memory changes over 12 months were also assessed. Linear and logistic regression models were conducted to quantify the association of α-diversity with different cognitive measurements controlling for potential confounding variables. Differences in β-diversity were analyzed using permutational analysis of variance. ResultsA total of 605 participants aged 60–69 years were included in the analysis. Oral microbial α-diversity was significantly and positively correlated with DSST (β, 2.92; 95% CI, 1.01–4.84). Participants with higher oral microbial α-diversity were more likely to have better cognitive performance status based on DSST (adjusted odds ratio, 2.35; 95% CI, 1.28–4.30) and were less likely to experience subjective memory changes (adjusted odds ratio, 0.43; 95% CI, 0.25–0.74). In addition, β-diversity was statistically significant for the cognitive performance status based on DSST (P = 0.031) and subjective memory changes (P = 0.023). ConclusionsOral microbial composition was associated with executive function and subjective memory changes among older adults among older U.S. adults in a nationally representative population sample. Oral dysbiosis is a potential biomarker or therapeutic target for cognitive decline. Further work is needed to elucidate the mechanisms underpinning the association between the oral microbiome and cognitive function.

Fatty acid composition of whale shark (Rhincodon typus), and zooplankton in two aggregation sites in the Gulf of California

The whale shark Rhincodon typus (Smith, 1828) is a filter-feeding species that feeds on zooplankton. There are whale shark aggregation sites in the Gulf of California, Bahia de La Paz in Baja California Sur, and Bahía de Los Angeles in Baja California. Whale shark ecotourism is an important and economically profitable activity for the coastal communities surrounding their habitat areas. Fatty acid (FA) profiles, including arachidonic acid (ARA), docosahexaenoic acid (DHA), and eicosapentaenoic acid (EPA), are used as trophic tracers in marine food webs because they are essential for marine fish and provide information on the nutritional quality of zooplankton. In the present study, we analyzed the FA profile of zooplankton to trace them in the stomach contents, blood, liver, and muscle of stranded male whale sharks and the subdermal tissue of live whale sharks. Total lipids were extracted to calculate the energy density. Then lipids were methylated to obtain FA methyl esters (FAMEs) and analyzed in a gas chromatograph with a flame ionization detector. Permutational multivariate analysis of variance was applied to compare FA profiles. Zooplankton of both aggregation sites had 70 % similarity in their FA profiles. The FA profile found in the liver of whale sharks was similar to that of zooplankton in both aggregation sites (DHA > EPA > ARA). However, muscle and subdermal tissue had FA profiles significantly different from zooplankton, and there was preferential ARA assimilation in the subdermal tissue of stranded and live whale sharks. Therefore, FA profiles reflected just 50–60 % of the diet, suggesting that whale shark tissues retain FA according to their metabolic requirements or that surficial zooplankton do not provide ARA detected in subdermal tissue. Future studies should consider night sampling and FA analysis of demersal zooplankton in each aggregation site.

Simultaneous MEG and EEG source imaging of electrophysiological activity in response to acute transcranial photobiomodulation.

Transcranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique that improves human cognition. The effects of tPBM of the right forehead on neurophysiological activity have been previously investigated using EEG in sensor space. However, the spatial resolution of these studies is limited. Magnetoencephalography (MEG) is known to facilitate a higher spatial resolution of brain source images. This study aimed to image post-tPBM effects in brain space based on both MEG and EEG measurements across the entire human brain. MEG and EEG scans were concurrently acquired for 6 min before and after 8-min of tPBM delivered using a 1,064-nm laser on the right forehead of 25 healthy participants. Group-level changes in both the MEG and EEG power spectral density with respect to the baseline (pre-tPBM) were quantified and averaged within each frequency band in the sensor space. Constrained modeling was used to generate MEG and EEG source images of post-tPBM, followed by cluster-based permutation analysis for family wise error correction (p < 0.05). The 8-min tPBM enabled significant increases in alpha (8-12 Hz) and beta (13-30 Hz) powers across multiple cortical regions, as confirmed by MEG and EEG source images. Moreover, tPBM-enhanced oscillations in the beta band were located not only near the stimulation site but also in remote cerebral regions, including the frontal, parietal, and occipital regions, particularly on the ipsilateral side. MEG and EEG results shown in this study demonstrated that tPBM modulates neurophysiological activity locally and in distant cortical areas. The EEG topographies reported in this study were consistent with previous observations. This study is the first to present MEG and EEG evidence of the electrophysiological effects of tPBM in the brain space, supporting the potential utility of tPBM in treating neurological diseases through the modulation of brain oscillations.

Investigating cortical excitability and inhibition in patients with schizophrenia: A TMS-EEG study

BackgroundTranscranial magnetic stimulation (TMS) combined with electromyography (EMG) has widely been used as a non-invasive brain stimulation tool to assess excitation/inhibition (E/I) balance. E/I imbalance is a putative mechanism underlying symptoms in patients with schizophrenia. Combined TMS-electroencephalography (TMS-EEG) provides a detailed examination of cortical excitability to assess the pathophysiology of schizophrenia. This study aimed to investigate differences in TMS-evoked potentials (TEPs), TMS-related spectral perturbations (TRSP) and intertrial coherence (ITC) between patients with schizophrenia and healthy controls. Materials and methodsTMS was applied over the motor cortex during EEG recording. Differences in TEPs, TRSP and ITC between the patient and healthy subjects were analysed for all electrodes at each time point, by applying multiple independent sample t-tests with a cluster-based permutation analysis to correct for multiple comparisons. ResultsPatients demonstrated significantly reduced amplitudes of early and late TEP components compared to healthy controls. Patients also showed a significant reduction of early delta (50–160 ms) and theta TRSP (30-250ms),followed by a reduction in alpha and beta suppression (220–560 ms; 190–420 ms). Patients showed a reduction of both early (50–110 ms) gamma increase and later (180–230 ms) gamma suppression. Finally, the ITC was significantly lower in patients in the alpha band, from 30 to 260 ms. ConclusionOur findings support the putative role of impaired GABA-receptor mediated inhibition in schizophrenia impacting excitatory neurotransmission. Further studies can usefully elucidate mechanisms underlying specific symptoms clusters using TMS-EEG biometrics.

Patterns of spontaneous neural activity associated with social communication abilities among infants and toddlers showing signs of autism.

Early disruptions to social communication development, including delays in joint attention and language, are among the earliest markers of autism spectrum disorder (autism, henceforth). Although social communication differences are a core feature of autism, there is marked heterogeneity in social communication-related development among infants and toddlers exhibiting autism symptoms. Neural markers of individual differences in joint attention and language abilities may provide important insight into heterogeneity in autism symptom expression during infancy and toddlerhood. This study examined patterns of spontaneous electroencephalography (EEG) activity associated with joint attention and language skills in 70 community-referred 12- to 23-month-olds with autism symptoms and elevated scores on an autism diagnostic instrument. Data-driven cluster-based permutation analyses revealed significant positive associations between relative alpha power (6-9Hz) and concurrent response to joint attention skills, receptive language, and expressive language abilities. Exploratory analyses also revealed significant negative associations between relative alpha power and measures of core autism features (i.e., social communication difficulties and restricted/repetitive behaviors). These findings shed light on the neural mechanisms underlying typical and atypical social communication development in emerging autism and provide a foundation for future work examining neural predictors of social communication growth and markers of intervention response.

Gestational diabetes-related gut microbiome dysbiosis is not influenced by different Asian ethnicities and dietary interventions: a pilot study.

Gut microbiome dysbiosis contributes to the pathophysiology of both gestational diabetes mellitus (GDM) and its associated adverse outcomes in the woman and offspring. Even though GDM prevalence, complications, and outcomes vary among different ethnic groups, limited information is available about the influence of ethnicity on gut microbiome dysbiosis in pregnancies complicated by GDM. This pilot prospective cohort study examined the impact of ethnicity on gut dysbiosis in GDM among three Asian ethnic groups (Chinese, Malay, Indian) living in Singapore, and investigated the potential modulatory roles of diet and lifestyle modifications on gut microbiome post-GDM diagnosis. Women with GDM (n = 53) and without GDM (n = 16) were recruited. Fecal samples were collected at 24-28- and 36-40-weeks' gestation and analyzed by targeted 16S rRNA gene-based amplicon sequencing. Permutational multivariate analysis of variance (PERMANOVA) analysis was performed to evaluate differences between groups. Differentially abundant taxa were identified by DeSeq2 based analysis. Functional prediction was performed using thephylogeneticinvestigation of communities by reconstruction of unobserved states (PICRUSt2). Among women with GDM, gut microbiome from different ethnicities harbored common microbial features. However, among those without GDM, there was contrasting microbiome composition between ethnic groups. Microbial members such as Collinsella, Blautia, Ruminococcus, Ruminococcus gnavus, Ruminococcus torques, and Eubacterium hallii groups were differentially enriched (p < 0.05) in women with GDM compared to those without. Among women with GDM, no differences in alpha- and beta- diversity were observed when comparing 24-28weeks' samples with 36-40weeks' samples, a period covering intense dietary and lifestyle modification, suggesting an inability to modulate gut microbiota through classic GDM management. Women with GDM have a distinct gut microbiome profile which harbours common features across different Asian ethnic groups, consistent with the notion that specific microbes are involved in the pathogenesis of insulin resistance, pro-inflammatory conditions, and other metabolic dysregulation known to be present in GDM.

The effect of non-Saccharomyces yeasts on biogenic amines in Sauvignon Blanc wine and Gewürztraminer wine

Biogenic amine (BA) is a class of nitrogen-containing small molecular organic compounds with biological activity. Excessive BAs in wine affect flavor and quality of wine and are hazardous to human health. However, little attention has been paid to the effect of non-Saccharomyces yeasts and Saccharomyces cerevisiae mixed fermentation on BAs in white wine. The effect of mixed fermentation on BAs and amino acids in wine was investigated using two white grapes of Sauvignon Blanc and Gewürztraminer. Higher levels of total amino acids and BAs in Gewürztraminer wine compared to Sauvignon Blanc wine may be due to different grape varieties. Mixed fermentation did not influence BA profiles in Sauvignon Blanc wine, while it increased total BAs content. VL3 (VL) fermented wine has 33.7% less BAs content than EC1118 (EC) single-strain fermented wine. Similar phenomenon was found in Gewürztraminer wine produced by different fermentation combinations except that cadaverine was only detected in wine produced by Hanseniaspora uvarum participated in mixed fermentations. Principal coordinate analysis (PCoA) and permutational multivariate analysis of variance (PERMANOVA) revealed that the effects on BAs were related to grape varieties and yeast species in white wine. Ethanolamine, tryptamine, isoamylamine and histamine content in wine were related to grape varieties. Collectively, mixed fermentation increased BAs content in Sauvignon Blanc and Gewürztraminer wine. The content of BAs in wine fermented by VL single-strain fermentation was lower than that fermented by EC single-strain fermentation, which is more suitable for the winemaking of white wine.

Fecal microbiota is associated with extraintestinal manifestations in inflammatory bowel disease

Introduction A large proportion of patients with inflammatory bowel disease (IBD) experience IBD-related inflammatory conditions outside of the gastrointestinal tract, termed extraintestinal manifestations (EIMs) which further decreases quality of life and, in extreme cases, can be life threatening. The pathogenesis of EIMs remains unknown, and although gut microbiota alterations are a well-known characteristic of patients with IBD, its relationship with EIMs remains sparsely investigated. This study aimed to compare the gut microbiota of patients with IBD with and without EIMs. Methods A total of 131 Danish patients with IBD were included in the study, of whom 86 had a history of EIMs (IBD-EIM) and 45 did not (IBD-C). Stool samples underwent 16S rRNA sequencing. Amplicon sequence variants (ASVs) were mapped to the Silva database. Diversity indices and distance matrices were compared between IBD-EIM and IBD-C. Differentially abundant ASVs were identified using a custom multiple model statistical analysis approach, and modules of co-associated bacteria were identified using sparse correlations for compositional data (SparCC) and related to patient EIM status. Results Patients with IBD and EIMs exhibited increased disease activity, body mass index, increased fecal calprotectin levels and circulating monocytes and neutrophils. Microbiologically, IBD-EIM exhibited lower fecal microbial diversity than IBD-C (Mann–Whitney’s test, p = .01) and distinct fecal microbiota composition (permutational multivariate analysis of variance; weighted UniFrac, R 2 = 0.018, p = .01). A total of 26 ASVs exhibited differential relative abundances between IBD-EIM and IBD-C, including decreased Agathobacter and Blautia and increased Eggerthella lenta in the IBD-EIM group. SparCC analysis identified 27 bacterial co-association modules, three of which were negatively related to EIM (logistic regression, p < .05) and included important health-associated bacteria, such as Agathobacter and Faecalibacterium. Conclusions The fecal microbiota in IBD patients with EIMs is distinct from that in IBD patients without EIM and could be important for EIM pathogenesis.

High-throughput sequencing-based analysis of the composition and diversity of the endophyte community in roots of Stellera chamaejasme

Stellera chamaejasme (S. chamaejasme) is an important medicinal plant with heat-clearing, detoxifying, swelling and anti-inflammatory effects. At the same time, it is also one of the iconic plants of natural grassland degradation in northwest China, playing a key role in the invasion process. Plant endophytes live in healthy plant tissues and can synthesize substances needed for plant growth, induce disease resistance in host plants, and enhance plant resistance to environmental stress. Therefore, studying the root endophytes of S. chamaejasme is of great significance for mining beneficial microbial resources and biological prevention and control of S. chamaejasme. This study used Illumina MiSeq high-throughput sequencing technology to analyze the composition and diversity of endophytes in the roots of S. chamaejasme in different alpine grasslands (BGC, NMC and XGYZ) in Tibet. Research results show that the main phylum of endophytic fungi in the roots of S. chamaejasme in different regions is Ascomycota, and the main phyla of endophytic bacteria are Actinobacteria, Proteobacteria and Firmicutes (Bacteroidota). Overall, the endophyte diversity of the NMC samples was significantly higher than that of the other two sample sites. Principal coordinate analysis (PCoA) and permutational multivariate analysis of variance (PERMANOVA) results showed significant differences in the composition of endophytic bacterial and fungal communities among BGC, NMC and XGYZ samples. Co-occurrence network analysis of endophytes showed that there were positive correlations between fungi and some negative correlations between bacteria, and the co-occurrence network of bacteria was more complex than that of fungi. In short, this study provides a vital reference for further exploring and utilizing the endophyte resources of S. chamaejasme and an in-depth understanding of the ecological functions of S. chamaejasme endophytes.

Intraspecific variation in fine-root traits is larger than in aboveground traits in European herbaceous species regardless of drought.

Differences within species (Intraspecific trait variation - ITV) contribute substantially to overall trait variability and environmental harshness can reduce among-species variation. While aboveground traits have received considerable attention, knowledge about ITV in fine-root traits and how it differs from ITV in aboveground traits remains limited. This study examined the partitioning of trait variation aboveground and fine-root traits in 52 European herbaceous species and how such proportions change in response to drought, offering valuable insights for accurate functional species characterization and inter-species comparisons. We studied seven morphological aboveground and fine-root traits under drought and well-watered conditions in a greenhouse experiment. Linear mixed effect models and permutational multivariate analysis of variance (PERMANOVA) were employed to decompose trait variation, ensuring the robustness of our results. We also calculated variance partitioning for the combination of aboveground traits and the combination of fine-root traits, as well as pairs of analogous leaf and fine-root traits (i.e., traits that fulfill similar functions) for each treatment (control and drought). Among-species trait differences explained a greater proportion of overall variance than within-species variation, except for root dry matter content (RDMC). Height and leaf area stood out, with species' identity accounting for 87-90% of total trait variation. Drought had no significant effect on the proportions of variation in any of the traits. However, the combination of fine-root traits exhibited higher intraspecific variability (44-44%) than aboveground traits (19-21%) under both drought and control. Analogous root traits also showed higher ITV (51-50%) than analogous leaf traits (27-31%). Our findings highlight substantial within-species variation and the nuanced responses of fine-root traits, particularly RDMC, suggesting root traits' flexibility to soil heterogeneity that fosters less differentiation among species. Among-species trait differences, especially aboveground, may underscore distinct strategies and competitive abilities for resource acquisition and utilization. This study contributes to elucidate the mechanisms underlying the multifunctionality of the above- and belowground plants compartments.

Sex-specific associations between AD genotype and the microbiome of human amyloid beta knock-in (hAβ-KI) mice.

Emerging evidence links changes in the gut microbiome to late-onset Alzheimer's disease (LOAD), necessitating examination of AD mouse models with consideration of the microbiome. We used shotgun metagenomics and untargeted metabolomics to study the human amyloid beta knock-in (hAβ-KI) murine model for LOAD compared to both wild-type (WT) mice and a model for early-onset AD (3xTg-AD). Eighteen-month female (but not male) hAβ-KI microbiomes were distinct from WT microbiomes, with AD genotype accounting for 18% of the variance by permutational multivariate analysis of variance (PERMANOVA). Metabolomic diversity differences were observed in females, however no individual metabolites were differentially abundant. hAβ-KI mice microbiomes were distinguishable from 3xTg-AD animals (81% accuracy by random forest modeling), with separation primarily driven by Romboutsia ilealis and Turicibacter species. Microbiomes were highly cage specific, with cage assignment accounting for more than 40% of the PERMANOVA variance between the groups. These findings highlight a sex-dependent variation in the microbiomes of hAβ-KI mice and underscore the importance of considering the microbiome when designing studies that use murine models for AD. Microbial diversity and theabundance of several species differed in human amyloid beta knock-in (hAβ-KI) females but not males. Correlations to Alzheimer's disease (AD) genotype were stronger for the microbiome than the metabolome. Microbiomes from hAβ-KI mice were distinct from 3xTg-AD mice. Cage effects accounted for most of the variance in the microbiome and metabolome.

OpenWMB: An open-source and automated working memory task battery for OpenSesame

Working memory capacity (WMC) has been measured with a plethora of cognitive tasks. Several preeminent automated batteries of working memory (WM) tasks have been developed recently. However, despite all their advantages, most batteries were programmed in paid platforms and/or only included a single WM paradigm. To address these issues, we developed the OpenWMB, an automated battery comprising seven tasks from three distinct paradigms (complex spans, updating tasks, and binding tasks) that tap into several functional aspects of WM (simultaneous storage and processing, updating, and binding). The battery runs on open-source software (OpenSesame) and is freely available online in a ready-to-download format. The OpenWMB possesses flexible features and includes a data processing script (that converts data into a format ready for statistical analysis). The instrument is available in Portuguese and English. However, we only assessed the psychometric properties of the former version. The Portuguese version presented good internal consistency and considerable internal and predictive validity: all tasks loaded into a single factor. Additionally, the WMC estimate was strongly correlated with a fluid intelligence factor. This study also tried to contribute to the ongoing debate regarding the best method to assess WMC. We computed a permutation analysis to compare the amount of variance shared between a fluid intelligence factor and (1) each WM task, (2) homogenous WMC factors (based on multiple tasks from the same paradigm), and (3) heterogeneous WMC factors (derived from triplets of tasks from different paradigms). Our results suggested that heterogeneous factors provided the best estimates of WMC.

Soil prokaryotic and fungal biome structures associated with crop disease status across the Japan Archipelago.

Archaea, bacteria, and fungi in the soil are increasingly recognized as determinants of agricultural productivity and sustainability. A crucial step for exploring soil microbiomes with important ecosystem functions is to perform statistical analyses on the potential relationship between microbiome structure and functions based on comparisons of hundreds or thousands of environmental samples collected across broad geographic ranges. In this study, we integrated agricultural field metadata with microbial community analyses by targeting 2,903 bulk soil samples collected along a latitudinal gradient from cool-temperate to subtropical regions in Japan (26.1-42.8 °N). The data involving 632 archaeal, 26,868 bacterial, and 4,889 fungal operational taxonomic units detected across the fields of 19 crop plant species allowed us to conduct statistical analyses (permutational analyses of variance, generalized linear mixed models, randomization analyses, and network analyses) on the relationship among edaphic factors, microbiome compositions, and crop disease prevalence. We then examined whether the diverse microbes form species sets varying in potential ecological impacts on crop plants. A network analysis suggested that the observed prokaryotes and fungi were classified into several species sets (network modules), which differed substantially in association with crop disease prevalence. Within the network of microbe-to-microbe coexistence, ecologically diverse microbes, such as an ammonium-oxidizing archaeon, an antibiotics-producing bacterium, and a potentially mycoparasitic fungus, were inferred to play key roles in shifts between crop-disease-promotive and crop-disease-suppressive states of soil microbiomes. The bird's-eye view of soil microbiome structure will provide a basis for designing and managing agroecosystems with high disease-suppressive functions.IMPORTANCEUnderstanding how microbiome structure and functions are organized in soil ecosystems is one of the major challenges in both basic ecology and applied microbiology. Given the ongoing worldwide degradation of agroecosystems, building frameworks for exploring structural diversity and functional profiles of soil microbiomes is an essential task. Our study provides an overview of cropland microbiome states in light of potential crop-disease-suppressive functions. The large data set allowed us to explore highly functional species sets that may be stably managed in agroecosystems. Furthermore, an analysis of network architecture highlighted species that are potentially used to cause shifts from disease-prevalent states of agroecosystems to disease-suppressive states. By extending the approach of comparative analyses toward broader geographic ranges and diverse agricultural practices, agroecosystem with maximized biological functions will be further explored.

Asymptomatic Enteric Virus Infections and Association with the Gut Microbiome in Rural Residents of Northern Laos.

Viral gastrointestinal infections are an important public health concern, and the occurrence of asymptomatic enteric virus infections makes it difficult to prevent and control their spread. This study aimed to determine the prevalence of and factors associated with asymptomatic enteric virus infection in adults in northern Laos. Fecal samples were collected from apparently healthy participants who did not report diarrhea or high fever at the time of the survey in northern Laos, and enteric viruses were detected using polymerase chain reaction (PCR) and reverse transcription (RT)-PCR. Individual characteristics, including the gut microbiome, were compared between asymptomatic carriers and noncarriers of each enteric virus. Of the participants (N = 255), 12 (4.7%) were positive for norovirus genogroup I (GI), 8 (3.1%) for human adenovirus, and 1 (0.4%) for norovirus GII; prevalence tended to be higher in less-modernized villages. Gut microbial diversity (evaluated by the number of operational taxonomic units) was higher in asymptomatic carriers of norovirus GI or human adenovirus than in their noncarriers. Gut microbiome compositions differed significantly between asymptomatic carriers and noncarriers of norovirus GI or human adenovirus (permutational analysis of variance, P <0.05). These findings imply an association between asymptomatic enteric virus infection and modernization and/or the gut microbiome in northern Laos.

Seasonal diet partition among top predators of a small island, Iriomote Island in the Ryukyu Archipelago, Japan

Small islands tend to lack predators because species at higher trophic levels often cannot survive. However, two exceptional top predators—the Iriomote cat Prionailurus bengalensis iriomotensis, and the Crested Serpent Eagle Spilornis cheela perplexus—live on the small Iriomote Island in the Ryukyu Archipelago. To understand how these predators coexist with limited resources, we focused on their seasonal diets between which conflicts are considered to occur. To compare the diets, we used DNA metabarcoding analysis of faecal samples. In the summer, we identified 16 unique prey items from Iriomote cat faecal samples and 15 unique prey items from Crested Serpent Eagle faecal samples. In the winter, we identified 37 and 14, respectively. Using a non-metric multidimensional scaling and a permutational multivariate analysis of variance, our study reveals significant differences in the diet composition at the order level between the predators during both seasons. Furthermore, although some prey items at the species-to-order level overlapped between them, the frequency of occurrence of most prey items differed in both seasons. These results suggest that this difference in diets is one of the reasons why the Iriomote cat and the Crested Serpent Eagle are able to coexist on such a small island.

Abstract 7286: Optimizing prediction of metastatic castration-resistant prostate cancer: Multimodal fusion of clinicopathological and genomic features with machine learning

Abstract Background: Transitioning from metastatic castration-sensitive prostate cancer (mCSPC) to its resistant variant poses risks of intensified medication, toxic side effects, and financial burdens for men undergoing treatment. Our study proposes a multimodal approach that integrates clinical, pathological, and genomic features to optimize prediction of metastatic castration-resistant prostate cancer (mCRPC) events. By applying machine learning (MML) techniques to multimodal data, we aim to stratify these patients based on the risk of developing mCRPC, contributing to the development of safer and personalized treatment strategies. Methods: We analyzed a large cohort of patients with mCSPC (n=399) with a minimum of 36 month follow-up, annotated with clinical, pathological, and genomic features, encompassing relevant variables such as disease volume, PSA, metastases timing, variant classification, Grade Group, fraction of genome altered, MSI score, mutation counts, karyotypes, tumor mutational burden, and purity. Using a multimodal machine learning framework, we extracted informative features and employed eight distinct machine learning algorithms: K-Nearest Neighbor, Support Vector Machine, Decision Tree, and Logistic Regression, Support Vector Machine with RBF Kernel, Random Forest, and Gradient Boosting, in addition to a Deep Neural Networks architecture for building predictive models in supervised binary classification experiments. The models' performance was evaluated on separate training (80%) and testing sets (20%), and standard evaluation metrics, such as the area under the receiver operating characteristic curve (AUROC), and accuracy, were computed. Correlations were utilized to explore the relationships between features, and permutation analysis was employed to determine the importance of predictors. All raw data included in the analysis are available on cBioPortal database. The study is supported by the NIH-NCI-T32 for Next Generation Pathologists Program at our institution. Results: Of the 399 mCSPC patients, 56% developed castration resistance, 50% had Grade Group 5 disease, and 69% exhibited missense mutations. In a series of 8 experiments, the Support Vector Machine with RBF Kernel ensemble model and SVC exhibited the highest performance with an AUROC score of 0.77, while the remaining models tested in the study demonstrated AUROC scores ranging from 0.62 to 0.75. Notably, the fraction of altered genome emerged as the top-ranked predictor, displaying the highest importance score. Conclusions: Our study demonstrates the strong predictive performance of MML models in accurately identifying mCRPC events by leveraging routine clinical, pathological, and genomic data, offering valuable guidance for optimizing patient stratification and tailoring personalized therapeutic interventions. Citation Format: Mohammad K. Alexanderani, Francesca Khani, Matthew Greenblatt, Brian Robinson, Massimo Loda, Luigi Marchionni. Optimizing prediction of metastatic castration-resistant prostate cancer: Multimodal fusion of clinicopathological and genomic features with machine learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7286.

Abstract 834: Farm animal exposures and the oral microbiome in the Agricultural Health Study

Abstract Raising farm animals involves a variety of exposures, including microbes, antimicrobial agents, bioaerosols, and pesticides that may influence the human microbiome. Exposure to farm animals has also been associated with some cancers including lower risk of lung cancer and elevated risks of certain hematologic malignancies, with heterogeneity by animal species. Increasing epidemiologic evidence suggests that changes in the oral microbiome contribute to cancer development. Few human studies have investigated the potential influence of farm animal exposures on the oral microbiome. We investigated associations between farm animal exposures and the oral microbiome in 1245 Iowa and North Carolina farmers and spouses from the Agricultural Health Study. Participants provided information on types and numbers of farm animals raised in telephone interviews close to the time of oral wash sample collection. DNA was extracted from oral wash specimens and analyzed using 16S rRNA gene (V4 region) sequencing. We evaluated associations between farm animal exposures and alpha diversity metrics [e.g., observed amplicon sequence variants (ASVs)] using linear regression and assessed differences in beta diversity metrics (e.g., weighted Unifrac) using permutational multivariate analysis of variance. In addition, we evaluated associations with the presence and relative abundance of specific genera using zero-inflated negative binomial regression. All analyses adjusted for potential confounders (e.g., sex, age, state of residence, smoking). Overall, 63% of participants reported raising any animals, most commonly cattle (46%) and hogs (20%). Raising sheep/goats was associated with lower alpha diversity [e.g., 18 (95% confidence interval: 3-33) fewer observed ASVs compared to not raising sheep/goats], with an exposure-response trend for increasing number of sheep/goats (13 and 24 fewer observed ASVs for 1-29 and ≥30 sheep/goats vs. none, respectively; Ptrend = 0.048). Increasing numbers of hogs and poultry were associated with higher and lower alpha diversity, respectively. Associations were similar after mutual adjustment for other farm animal types. Based on beta diversity analyses, we did not observe statistically significant differences in microbial compositions between participants with and without farm animals. After adjusting for multiple testing, having any farm animal was associated with an increased relative abundance of Porphyromonas, and several genera were more likely to be absent with specific animal exposures (e.g., Capnocytophaga for cattle and sheep/goats; Corynebacterium and Abiotrophia for sheep/goats). To our knowledge, this was the largest investigation of farm animal exposures and the human microbiome to date. Our preliminary findings suggest that animal farming may alter the oral microbiome and provide new insights into the potential role of animal exposures in cancer etiology. Citation Format: Vicky C. Chang, Vaishnavi Purandare, Rashmi Sinha, Gabriella Andreotti, Shilan Li, Xing Hua, Yukiko Yano, Kathryn R. Dalton, Mikyeong Lee, Christine G. Parks, Stephanie J. London, Dale P. Sandler, Mitchell H. Gail, Jianxin Shi, Jonathan N. Hofmann, Christian C. Abnet, Emily Vogtmann, Laura E. Beane Freeman. Farm animal exposures and the oral microbiome in the Agricultural Health Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 834.

Abstract 2905: Spatial analysis of neuropilin 2 expression in the microenvironment of melanoma

Abstract Background: Neuropilin 2 (NRP2) is a co-receptor that enhances signaling of growth factor and cytokine receptors and is expressed in tumor and microenvironment (TME) cells in melanoma and other tumors. Neuropilin 2 expression in tumor cells is associated with more aggressive tumors. Expression in tumor associated macrophages enhances efferocytosis and immunologically silent tumor cell death. Methods: Whole excisional lymph node biopsies were obtained from 10 treatment naïve patients with metastatic cutaneous melanoma who subsequently received anti-PD1 treatment. A single 5mm formalin-fixed paraffin embedded tissue section was used to assess a panel of 39 analytes by cyclic multiplex immunofluorescence (MxIF). Fields of view (~1mm2, n=288) were selected from pathologist-annotated regions of the tumor core, tumor-immune interface and adjacent lymphoid tissue. Pixel-based single cell segmentation and a supervised classifier approach was applied to resolve 12 distinct tumor, stromal and immune cell phenotypes and functional states (NRP2 positive or negative) in 1.5 million cells. Results: Tumor recurrence was observed in 6 patients (relapsed), whereas 4 patients were recurrence-free (non-relapsed) during follow up. Among the different cell types, NRP2 expression was more frequent in macrophages (44%), tumor cells (40%), dendritic cells (40%), followed by Tregs (31%) and T helper cells (29%), and less frequent in neutrophils (24%), cytotoxic T cells (23%) and B cells (15%). In colocalization permutation analysis, NRP2 expressing macrophages clustered away from tumor cells in non-relapsed patients while a random spatial distribution of NRP2 expressing macrophages with respect to tumor cells was observed in relapsed patients. In comparing the odds of tumor cell interactions with NRP2-expressing macrophages to those with NRP2 non-expressing macrophages, we found in the tumor:stromal interface (10% tumor cells) that cells from both non-relapsed and relapsed patients were more likely to interact with NRP2 non-expressing macrophages (OR = 0.73, 95% CI = [0.71, 0.75] and OR = 0.56, 95% CI = [0.55, 0.58] for non-relapsed and relapsed patients, respectively). However, in the tumor core (90% tumor cells), tumor cells from relapsed patients had significantly higher odds of interacting with NRP2 expressing macrophages, (OR = 1.15, 95% CI = [1.12, 1.18]), and this was not seen for non-relapsed patients (OR = 0.68, 95% CI = [0.66, 0.71]). In FOVs dominated by tumor cells (75% tumor), tumor cells from relapsed patients had 4.97 times the odds of expressing NRP2 compared to tumor cells from non-relapsed patients (95% CI = [2.23, 11.09], p = 0.0001). Conclusions: These spatial analytics suggest complex interactions among NRP2 expression in tumor and TME of melanoma determining risk for relapse with anti-PD1 treatment. Citation Format: Anastasios Dimou, Raymond M. Moore, Caitlin Ward, Alexey Leontovich, Ruifeng Guo, Chen Wang, Shankar Suman, Betty Dicke, Jill M. Schimke, Noah A. Stueven, Chathu A. Atherton, Wendy Nevala, Svetomir N. Markovic. Spatial analysis of neuropilin 2 expression in the microenvironment of melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2905.

Yeast heterochromatin stably silences only weak regulatory elements by altering burst duration

Transcriptional silencing in Saccharomyces cerevisiae involves the generation of a chromatin state that stably represses transcription. Using multiple reporter assays, a diverse set of upstream activating sequence enhancers and core promoters were investigated for their susceptibility to silencing. We show that heterochromatin stably silences only weak and stress-induced regulatory elements but is unable to stably repress housekeeping gene regulatory elements, and the partial repression of these elements did not result in bistable expression states. Permutation analysis of enhancers and promoters indicates that both elements are targets of repression. Chromatin remodelers help specific regulatory elements to resist repression, most probably by altering nucleosome mobility and changing transcription burst duration. The strong enhancers/promoters can be repressed if silencer-bound Sir1 is increased. Together, our data suggest that the heterochromatic locus has been optimized to stably silence the weak mating-type gene regulatory elements but not strong housekeeping gene regulatory sequences.