Biology subjects

Fodor, A. A.

Publications and source records attributed to Fodor, A. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Winnow-tax: sensitive and precise taxonomic profiling of low-coverage organisms in shotgun metagenomes

Accurate species-level profiling of shotgun metagenomes becomes difficult when an organism is represented by only sparse sequence coverage. Per-read k-mer classifiers can retain sensitivity under these conditions, but short reads from conserved or shared genomic regions can generate false-positive calls among closely related references. More conservative marker-gene and genome-containment approaches generally provide stronger species-level specificity but may lose sensitivity as genomic sampling becomes sparse. We present winnow-tax, a two-stage taxonomic profiling pipeline that separates sensitive candidate nomination from genome-level confirmation. Candidate species are nominated using Sylph, Kraken2, and a branch-rescue procedure, then reads are competitively recruited to a sample-specific reference set. Species presence is evaluated using read support, observed genome breadth, and a Lander-Waterman-based breadth ratio that compares observed breadth with the breadth expected at the measured mean depth. In a controlled synthetic community of 82 genomes with human DNA background, winnow-tax maintained a stronger precision-sensitivity balance than Kraken2/Bracken, Sylph, and MetaPhlAn 4 as genome coverage decreased, with its advantage concentrated near the low-coverage detection boundary. In the CAMI III Toy Longitudinal Human Gut benchmark, winnow-tax had higher sensitivity than Sylph (0.803 versus 0.672), lower precision (0.923 versus 0.970), and a modestly but significantly higher F1 score (0.858 versus 0.793). In a clinical enteric stool cohort with culture/PCR reference testing, winnow-tax achieved the best composite performance for Salmonella, detecting 37 of 48 composite-positive samples with one false-positive call. Together, these results support a profiling strategy in which weak taxonomic signals are retained during candidate generation but require genomic evidence distributed as broadly as expected for their sequencing depth before species presence is accepted.

bioinformatics↗

bioRxiv2026

Circulating Microbial DNA as a Potential Cancer Biomarker: Technical Challenges and Controlled Evaluation

Abstract Background. Circulating microbial DNA (cmDNA) has been proposed as a non-invasive cancer biomarker, but most evidence comes from cancer-sequencing datasets not designed for microbial analysis and lacking contamination controls. Whether reported signatures reflect biology or artifact is unclear in low-biomass specimens, where standard taxonomic pipelines are prone to systematic error. Methods. In a tightly controlled pilot study of metastatic castration-resistant prostate cancer, we profiled plasma cell-free DNA (cfDNA) and buffy-coat genomic DNA (gDNA) from two patients and two healthy volunteers alongside mock blood-draw and reagent controls, each with and without host-DNA depletion. Reads were classified with Kraken2/Bracken and, independently, with the marker-gene classifier MetaPhlAn. As informatics controls, reads were per-base shuffled to randomize nucleotide order while preserving read length and guanine-cytosine (GC) content, and purely synthetic reads were generated from a four-base process matched only to an aggregate GC target; both were classified identically. Genus abundances were regressed against Kraken2 database k-mer representation and against GC content. Results. Across 40 samples, Kraken2 reported several thousand genera, samples clustered by specimen type in principal-coordinate analysis (PCoA), and pooled genus counts correlated strongly with a published cancer-microbiome catalog (The Cancer Genome Atlas lung adenocarcinoma, TCGA-LUAD; Spearman {rho} = 0.81 over 282 shared genera), a pattern readily interpreted as biological signal. However, these observations were also made in per-base shuffling, which preserves GC content and length but destroys all biological sequence: shuffled reads were still abundantly classified, still clustered by specimen type, and still correlated with the catalog ({rho} {approx} 0.7), as did every sample group, including pure reagent controls. Genus counts scaled tightly with each genus's k-mer representation in the Kraken2 database on real (r 2 = 0.74) and shuffled (r2 = 0.85) reads, and the same dependence appeared in the independent published cohort. Purely synthetic reads carrying no information beyond an aggregate GC target reproduced much of the cross-cohort agreement (synthetic TCGA-LUAD {rho} = 0.61 versus 0.81 for real reads; significant in 27 of 33 TCGA cancers), and replicate shuffles of a low-GC versus a high-GC plasma sample, for which the true difference is zero, produced spurious significant differences in about 46% of genera. Regressing observed counts against the shuffled baseline left 23 genera above the artifact floor at 5% false discovery rate (FDR), nearly all known kit contaminants, control-enriched viruses, or very-low-abundance taxa; a four-criterion validity filter reduced thousands of Kraken2 genera to a single defensible candidate, Klebsiella. Conclusions. Much of the apparent cmDNA structure, including its agreement with a published cancer-microbiome catalog, is explained by base composition and reference-database architecture rather than authentic biology, and short-read k-mer pipelines cannot separate the two on their own. We find little positive evidence of an authentic circulating microbial signal, though our small sample cannot prove its absence. To limit false discovery in low-biomass metagenomics, we recommend specimen-matched negative controls, corroboration with a conservative second classifier, per-base shuffling (with GC-matched synthetic reads as a stricter floor), and GC-aware analysis.

bioinformatics↗

bioRxiv2026

Benchmarking Short-Read ITS2 and Full-Length ITS Sequencing Reveals Pipeline-Dependent Biases in Indoor Fungal Community Profiling

Short-read amplicon sequencing is widely used for fungal surveys but can limit taxonomic resolution. Long-read sequencing enables recovery of the full internal transcribed spacer (ITS) region and may improve ecological and taxonomic inference. Here, we conducted a paired comparison of Illumina ITS2 and PacBio HiFi full-length ITS sequencing using identical DNA extracts from built-environmental air and surface samples (n = 68) collected across homes, a dormitory, and laboratories. Both datasets were taxonomically assigned using the same algorithm and reference database. We performed paired statistics, in-silico ITS2 trimming of long-read sequences, and cross-platform mapping at multiple identity thresholds. Full-length ITS provided higher taxonomic resolution, assigning a greater fraction of ASVs at the family (98% vs. 88%) and species (42% vs. 32%) ranks than ITS2 (paired Wilcoxon q = 0.002). Alpha-diversity comparisons showed similar Shannon diversity across pipelines, whereas richness metrics were consistently higher for full-length ITS. Beta-diversity analyses indicated broadly comparable community-level patterns, although full-length ITS revealed stronger sample-type- and location-associated structure (PERMANOVA R{superscript 2} [≥] 0.06, p = 0.0001). In-silico ITS2 trimming reduced these differences, indicating that amplicon length is a major contributor to enhanced taxonomic resolution and ecological inference. Cross-platform mapping further showed extensive one-to-many relationships between ITS2 and full-length ITS ASVs, consistent with increased sequence resolution in long-read data. Together, these results show that ITS2 sequencing provides robust community-level profiling, while full-length ITS enables improved richness estimates and finer ecological and taxonomic resolution. This paired, bias-aware framework provides a practical template for selecting fungal amplicon sequencing strategies in built-environment mycobiome studies. ImportanceFungal communities in built environments influence indoor air quality and human exposure, yet their characterization depends strongly on sequencing strategy. This study provides a controlled, paired comparison of short-read ITS2 and long-read full-length ITS sequencing, showing that differences in amplicon length substantially contribute to variation in taxonomic resolution and ecological inference. While both approaches yield comparable community-level patterns, full-length ITS improves richness estimates, species-level assignment, and environmental discrimination by resolving sequence variation collapsed in ITS2 surveys. By integrating paired diversity analyses, in-silico ITS2 trimming, and cross-platform ASV mapping, this work offers a bias-aware framework for evaluating fungal amplicon pipelines. Importantly, improved species-level resolution enables functional interpretation of indoor fungi, for example the identification of taxa associated with pathogenic traits, allergen production, or toxin synthesis, supporting the development of more informative exposure metrics and targeted assays relevant to human health in built environments.

microbiology↗

bioRxiv2026

From external-input sensitivity to resident persistence: community assembly in a sink p-trap model

Microbial habitats that receive repeated external input may not remain shaped by that input forever if local retention allows resident communities to build up over time. Here, we used a controlled bench-scale sink p-trap system to examine how community assembly unfolded during initial establishment in new, bleach-treated p-traps. Two p-traps received repeated handwashing-water input, while one received tap water as baseline. The treated p-traps, but not the control, showed clear successional change toward later resident-like states. Nested-model comparisons further showed that recent external input had its greatest influence early in succession, but the p-traps own prior state remained the stronger predictor throughout. Final-day post-flush trajectories indicated short-term displacement from pre-flush positions, with later time points tending to move back toward late-stage resident centroids. Together, these results show that repeated inoculation does not necessarily keep communities under continued outside influence. Instead, retentive microbial habitats can shift over time from early sensitivity to external input toward persistence shaped more by local history.

ecology↗

bioRxiv2026

Integrated analysis reveals strong reproducible signals within and across studies of the built environment

BackgroundBuilt environment microbiome studies have identified numerous factors that shape indoor microbiomes, yet the reproducibility of these findings across buildings, timepoints, and research groups remains unclear. Differences in sequencing protocols, sampling design, and environments pose major challenges for cross-study comparisons, particularly in low-biomass environments where technical variation can obscure biological signal. To address this gap, we constructed a simple ontology which groups samples into one of three categories: hand, hand-associated surfaces, and floor then applied it to four publicly available 16S rRNA gene datasets: a hospital, university dormitory, Air Force dormitory, and private residential houses. ResultsWe identified strong and reproducible separation between floors and surfaces with frequent human contact. We found that floors consistently harbored soil-associated taxa, including KD4-96, 67-14, Skermanella, and Sphingobacterium, whereas hands and hand-associated surfaces were enriched with skin-associated genera, such as Lawsonella and Cutibacterium. Within studies, these results were generally consistent across timepoints. Across studies, mixed-model PERMANOVA analysis revealed significant clustering by sample type, with modest effects of study, suggesting that biological signal outweighed differences in laboratory or sequencing methods. Leave-one-study-out random forest models achieved high AUCs for hand vs. floor comparisons (0.865 to 0.921), moderate AUCs for hand-associated vs. floor comparisons, and weaker performance for hand vs. hand-associated comparisons. Application of the batch-correction method DEBIAS-M did not improve effect sizes or classification performance, indicating that reproducible structure was already discernible without batch adjustment. ConclusionsDespite substantial temporal and environmental heterogeneity among studies, we found that the built environment microbiome has a reproducible bacterial signal. There was consistent enrichment of soil-derived taxa on floors and human-associated taxa on hands and hand-associated surfaces suggesting a stable microbiome despite differences in building type, occupancy, and methodology. These findings establish an important foundation for future studies, suggesting cross-study comparability, the accuracy of ecological inference, and the ability to support the development of predictive applications in indoor microbiome research.

microbiology↗

bioRxiv2026

A Permutation-Based Framework for Evaluating Bias in Microbiome Differential Abundance Analysis

BackgroundIn microbiome research, differential abundance analysis aids in identifying significant differences in microbial taxa across two or more conditions. Statistical approaches used for this purpose include classical tests such as the t-test and Wilcoxon test, as well as methods designed to account for the compositional nature of microbiome data, including ALDEx2, ANCOM-BC2, and metagenomeSeq. In addition, methods originally developed for RNA sequencing data, such as DESeq2 and edgeR, have been frequently applied to microbiome studies. However, the use of these methods has been controversial. One area of concern is whether different modeling frameworks produce accurate p-values when the null hypothesis is true. ResultsWe evaluated seven methods across six datasets. Four permutation strategies were applied to generate data under the null hypothesis: shuffling sample names, shuffling counts within samples, shuffling counts within taxa, and fully randomizing the counts table. Methods based on the negative binomial distribution (DESeq2 and edgeR) produced p-values that were consistently smaller than expected under the null hypothesis. In contrast, methods that attempt to correct for compositionality (ALDEx2, ANCOM-BC2, and metagenomeSeq) tended to produce larger-than-expected p-values, even when only sample labels were shuffled, a permutation strategy that does not alter compositional structure. These deviations were dependent on dataset characteristics and permutation strategy, suggesting complex interactions between underlying data structure and algorithm performance. Generating data to follow the expected negative binomial distribution did not eliminate the tendency of DESeq2 and edgeR to exaggerate statistical significance. Although similar patterns were observed in RNA sequencing (RNAseq) datasets, the deviations were less pronounced than in microbiome data. In contrast, the classical t-test and Wilcoxon test yielded p-value distributions consistent with theoretical expectations across datasets and permutation strategies. ConclusionsThese results indicate that the performance of several widely used differential abundance methods can be problematic under null conditions and may affect biological interpretation. Our findings emphasize the importance of careful method selection and highlight the robustness of simpler statistical approaches for reliable inference.

bioinformatics↗

bioRxiv2026

Temporal stability and niche partitioning of bacterial communities in paired residential sink P-traps

Sink P-traps harbor microbial communities derived from environmental and human sources, yet longitudinal studies examining their stability and assembly dynamics remain limited. Here, we present, to our knowledge, the longest continuous characterization of bacteria collected from residential sink P-traps, with daily sampling over two months (n = 61 days). Samples were collected from paired sinks in a shared bathroom to identify dominant taxa, quantify temporal stability, and determine how occupant usage patterns influence community assembly. Using full-length 16S rRNA gene sequencing, we identified 3,865 unique taxa, with both sinks dominated by common sink-associated genera, including Pseudomonas, Citrobacter, Klebsiella, and Arcobacter. Despite sharing identical plumbing, environmental conditions, and cleaning regimes, the two sinks maintained distinct communities (p < 0.001). Temporal stability analyses revealed notable differences: Sink A (male; hand washing, toothbrushing, shaving) exhibited deterministic dynamics with low variability (CV = 4.9%), significant temporal autocorrelation (p = 0.001), and predictable trajectories, with time explaining 49.9% of community variation. In contrast, Sink B (female; hand washing, toothbrushing, face washing, mouthwash use) displayed stochastic dynamics with high volatility (CV = 26.5%), no significant autocorrelation (p = 0.53), and minimal temporal predictability. Differential abundance analysis revealed that Sink B was enriched in anaerobes, biofilm-forming taxa, oral microbiome associates, and preservative-resistant and lipid-degrading bacteria, while Sink A harbored a more aerobic, skin-associated community. These findings demonstrate that individual usage patterns (particularly exposure to biocidal agents) can alter P-trap community structure and temporal dynamics, with implications for microbial community prediction in residential and healthcare settings. ImportanceSink drains are increasingly recognized as reservoirs for antimicrobial-resistant pathogens, yet we lack fundamental knowledge about what drives bacterial community dynamics in these environments. By sampling paired residential sink P-traps daily for two months, we show that individual-specific behaviors, such as using products with a biocidal effect, can alter community composition from a stable, predictable state to one characterized by stochastic fluctuations. The sink exposed to mouthwash and face wash harbored more anaerobes, biofilm formers, and oral bacteria, suggesting that repeated exposure promotes disturbance-tolerant taxa rather than reducing bacterial colonization. These results provide a baseline ecological framework for understanding P-trap microbiomes and suggest that predictive monitoring of sink-associated pathogens might be feasible in stable environments but more difficult when there is variable antimicrobial exposure -- a finding directly relevant to hospital infection control.

microbiology↗

bioRxiv2026

Consumption of processed foods impairs memory function through dietary advanced glycation end-products

Consumption of processed foods is associated with dementia, obesity, and other negative health outcomes. Sustained heat treatment, a common food processing approach to enhance flavor, induces the chemical Maillard reaction that promotes the formation of dietary advanced glycation end-products (AGEs). The neurocognitive impacts of consuming dietary AGEs are poorly understood. Here we modeled an AGE-rich diet through heat treatment fed to rats during adolescence, a critical period of neural development, to mechanistically evaluate the long-term impact of early life dietary AGEs on behavioral and neural processes. Consuming the AGE-rich diet impaired hippocampal-dependent memory function and altered the gut microbiome without inducing obesity or nonspecific behavioral deficits. AGE-induced memory deficits were coupled with impaired hippocampal glutamatergic synaptic neurotransmission and altered expression in the synapse-pruning complement system. Hippocampal synaptic deficits likely result from direct AGE-complement interactions, as our extended studies reveal competitive antagonist action of AGEs on complement receptors. Memory impairments were prevented by administration of the AGE-inhibitor, alagebrium, and by supplementation with an AGE-inhibiting bacterial taxon, Lactococcus lactis, which was depleted in the heat-treated diet. These findings reveal a functional connection between early life dietary AGEs, the microbiome, and memory impairments, thus illuminating mechanisms through which food processing negatively impacts neurocognition.

neuroscience↗

bioRxiv2025

Correction for spurious taxonomic assignments of k-mer classifiers in low microbial biomass samples using shuffled sequences

BackgroundWith the increased use of shotgun metagenome and metatranscriptome sequences in characterizing the microbiome, accurate taxonomic classification of sequencing reads is essential for interpreting microbial community composition and revealing differential microbial signature between groups. K-mer based classifiers such as Kraken2 provide high speed and sensitivity, and are commonly used for low microbial biomass samples. However, their performance can be compromised by specific sources of error without proper parameter settings and incorporation of controls. MethodsIn this study, we analyzed six sequencing datasets of human tumor biopsies with Kraken2 and investigated how shared compact hash codes (i.e., identical hash codes across different k-mers), hash collision and the structure of reference databases can contribute to false positive taxonomic assignments in low biomass samples. ResultsWe demonstrated that in samples with high non-microbial DNA noise, the classified taxa of Kraken2 in sequencing reads are significantly correlated with that of shuffled sequences using the default setting. These taxa showed a similar distribution as those overrepresented in the hash table construction of the reference database. Incorporation of controls using shuffled reads can separate significant taxa with more robust differences from those more affected by background noise. Although the confidence thresholds needed to minimize noise varied with taxa, a minimum value of 0.2 can also help reduce misclassifications. ConclusionOur findings highlighted the need for caution when interpreting low-abundance or unexpected taxa in sequencing datasets of low microbial biomass samples. This work contributes to a more comprehensive understanding of the limitations of k-mer based classification tools and provides practical guidance for improving accuracy in microbiome research.

bioinformatics↗

bioRxiv2024

The impact of transplant location on the gut microbiome and resistome in patients undergoing hematopoietic stem cell transplantation at home versus in the hospital

ObjectivesHome-based hematopoietic stem cell transplantation (HCT) is a novel approach that has the potential to improve outcomes, however, the impact of transplant location on the gut microbiome remains uncharacterized. We hypothesized that patients randomized to undergo home HCT would have higher gut taxonomic diversity and lower antimicrobial resistance (AMR) gene abundance compared to those undergoing standard hospital HCT. MethodsWe identified 28 patients enrolled in Phase II randomized trials of home (n=16) v. hospital (n=12) HCT at Duke and performed shotgun metagenomic sequencing of stools to compare taxonomic and AMR gene composition between groups. We performed a secondary analysis of patients from each group transplanted at an outpatient infusion clinic with those who underwent standard inpatient HCT ("outpatient" v. "inpatient"). ResultsNo significant differences in duration of hospitalization were found in those randomized to home v. hospital HCT. Taxonomic and AMR gene - and {beta}-diversity were comparable. In contrast, secondary analyses demonstrated that patients from both home and hospital groups transplanted at an outpatient infusion clinic spent significantly less time in the hospital and demonstrated higher taxonomic -diversity and differential {beta}-diversity compared to standard inpatient HCT, although AMR gene -diversity did not differ, and comparisons were confounded by both differences in transplant type and use of antibiotics. ConclusionsRandomization by transplant location did not impact the gut microbiota to the same extent as the duration of hospitalization, although secondary analyses were heavily confounded. Even when taxonomic differences were observed, AMR genes were similar between groups.

microbiology↗

bioRxiv2023

Western diet consumption impairs memory function via dysregulated hippocampus acetylcholine signaling

Western diet (WD) consumption during development yields long-lasting memory impairments, yet the underlying neurobiological mechanisms remain elusive. Here we developed an early life WD rodent model to evaluate whether dysregulated hippocampus (HPC) acetylcholine (ACh) signaling, a pathology associated with memory impairment in human dementia, is causally-related to WD-induced cognitive impairment. Rats received a cafeteria-style WD (access to various high-fat/high-sugar foods; CAF) or healthy chow (CTL) during the juvenile and adolescent periods (postnatal days 26-56). Behavioral, metabolic, and microbiome assessments were performed both before and after a 30-day healthy diet intervention beginning at early adulthood. Results revealed CAF-induced HPC-dependent contextual episodic memory impairments that persisted despite healthy diet intervention, whereas CAF was not associated with long-term changes in body weight, body composition, glucose tolerance, anxiety-like behavior, or gut microbiome. HPC immunoblot analyses after the healthy diet intervention identified reduced levels of vesicular ACh transporter in CAF vs. CTL rats, indicative of chronically reduced HPC ACh tone. To determine whether these changes were functionally related to memory impairments, we evaluated temporal HPC ACh binding via ACh-sensing fluorescent reporter in vivo fiber photometry during memory testing, as well as whether the memory impairments could be rescued pharmacologically. Results revealed dynamic HPC ACh binding during object-contextual novelty recognition was highly predictive of memory performance and was disrupted in CAF vs. CTL rats. Further, HPC alpha-7 nicotinic receptor agonist infusion during consolidation rescued memory deficits in CAF rats. Overall, these findings identify dysregulated HPC ACh signaling as a mechanism underlying early life WD-associated memory impairments.

neuroscience↗

bioRxiv2023

Calorie Restriction Outperforms Bariatric Surgery in a Murine Model of Obesity and Triple-Negative Breast Cancer

Obesity promotes triple-negative breast cancer (TNBC), and effective interventions are urgently needed to break the obesity-TNBC link. Epidemiologic studies indicate that bariatric surgery reduces TNBC risk, while evidence is limited or conflicted for weight loss via low-fat diet (LFD) or calorie restriction (CR). Using a murine model of obesity- driven TNBC, we compared the antitumor effects of vertical sleeve gastrectomy (VSG) with LFD, chronic CR, and intermittent CR. Each intervention generated weight and fat loss and suppressed tumor growth relative to obese mice (greatest suppression with CR). VSG and CR regimens exerted both similar and unique effects, as assessed using multi-omic approaches, in reversing obesity-associated transcriptional, epigenetic, secretome, and microbiota changes and restoring antitumor immunity. Thus, in a murine model of TNBC, bariatric surgery and CR each reverse obesity-driven tumor growth via shared and distinct antitumor mechanisms, and CR is superior to VSG in reversing obesitys procancer effects.

cancer biology↗

bioRxiv2022

An integrative analysis of the biological clock hypothesis in human gut microbiome

BackgroundWhile previous studies have explored the relationship between aging and the gut microbiome, it remains unclear how consistent and reproducible this association is across different cultures and groups. We performed an integrative analysis with 11 independent datasets from nine different countries to test the idea that the aging gut microbiome can be viewed as a biological clock, in which microbial changes associated with age are consistent and measurable across distinct datasets. ResultsAs expected, our Principal Coordinate Analysis found strong batch effects with study ID by far the strongest signal across datasets. Despite this large batch effect, we found a consistent signal across studies that was largely driven by sample size with only our larger cohorts showing taxa in common associated with age. Likewise, Shannon diversity and richness were not consistently associated with age across the 11 datasets, but some positive correlations with richness and host age were observed among the four largest cohorts. The taxon with the most potential as a biomarker for the aging human gut microbiome is genus Bifidobacterium, with significantly negative associations with host age in three out of the four datasets that had more than 200 samples. ConclusionThe driving force behind low reproducibility of association of age with the microbiome in previous studies appears to be inadequate sample size rather than structural differences in the microbial community based on cohort characteristics. Results from a power analysis suggest that future studies on the aging human gut microbiome consider on the order of 100-300 samples to consistently observe an age signal. With these larger sample sizes, parametric and non-parametric model yield broadly similar power.

bioinformatics↗

bioRxiv2021

Microbial associations with Microscopic Colitis

BACKGROUND AND OBJECTIVEMicroscopic colitis is a relatively common cause of chronic diarrhea and may be linked to luminal factors. Given the essential role of the microbiome in human gut health, analysis of microbiome changes associated with microscopic colitis could provide insights into the development of the disease. METHODSWe enrolled patients who underwent colonoscopy for diarrhea. An experienced pathologist classified patients as having microscopic colitis (n=52) or controls (n=153). Research biopsies were taken from the ascending and descending colon, and the microbiome was characterized with Illumina sequencing. We analyzed the associations between microscopic colitis and microbiome with a series of increasingly complex models adjusted for a range of demographic and health factors. RESULTSWe found that alpha-diversity was significantly lower in microscopic colitis cases compared to controls in the descending colon microbiome. In the descending colon, a series of models that adjusted for an increasing number of co-variates found taxa significantly associated with microscopic colitis, including Proteobacteria that was enriched in cases and Collinsella enriched in controls. While the alpha-diversity and taxa were not significantly associated with microscopic colitis in the ascending colon microbiome, the inference p-values based on ascending and descending microbiomes were highly correlated. CONCLUSIONOur study demonstrates an altered microbiome in microscopic colitis cases compared to controls. Because both the cases and controls had diarrhea, we have identified candidate taxa that could be mechanistically responsible for the development of microscopic colitis independent of changes to the microbial community caused by diarrhea. Significance of this studyO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIMicroscopic colitis is a common cause of chronic diarrhea. The exact etiology of microscopic colitis is unknown, but the gut microbiome is considered to play an important role. C_LIO_LIPrior studies have reported microbial changes associated with microscopic colitis, but the results are not consistent. Prior studies have generally involved small numbers of patients, fecal samples, and comparison to healthy controls. C_LI What are the new findings?O_LIThe microbiome was altered in microscopic colitis patients. C_LIO_LIMicroscopic colitis was associated with lower alpha-diversity, increase of inflammation related taxa and decrease of Collinsella in the descending colon microbiome independent of diarrhea status. C_LIO_LIThe changes of microbial features were consistent between ascending and descending colon microbiomes, but with smaller changes in the ascending colon microbiome. C_LI How might it impact on clinical practice in the foreseeable future?O_LIThe altered microbial communities in patients with microscopic colitis suggest that the patients might benefit from prevention or treatment with live biotherapeutic products. C_LI

microbiology↗

bioRxiv2021

Lasting effects of low-calorie sweeteners on glucose regulation, sugar intake, and memory

Low-calorie sweetener (LCS) consumption in children has increased due to widespread LCS presence in the food environment and efforts to mitigate obesity through sugar replacement. However, mechanistic studies on the impact of early-life LCS consumption are lacking. Therefore, we developed a rodent model to evaluate the effects of daily LCS consumption (acesulfame potassium, saccharin, or stevia) during adolescence on adult metabolic, gut microbiome, neural, and behavioral outcomes. Results reveal that habitual early-life LCS consumption disrupts post-oral glucose tolerance and impairs hippocampal-dependent memory in the absence of weight gain. Furthermore, LCS consumption reduces lingual sweet taste receptor expression and alters sugar-motivated appetitive and consummatory responses. RNA sequencing analyses reveal that LCS also impacts collagen- and synaptic signaling-related gene pathways in the hippocampus and nucleus accumbens, respectively, in a sex-dependent manner. Collectively, these results suggest that regular early-life LCS consumption yields long-lasting impairments in metabolism, sugar-motivated behavior, and hippocampal-dependent memory.

neuroscience↗

bioRxiv2021

Batch effects removal for microbiome data via conditional quantile regression (ConQuR)

Batch effects in microbiome data arise from differential processing of specimens and can lead to spurious findings and obscure true signals. Most existing strategies for mitigating batch effects rely on approaches designed for genomic analysis, failing to address the zero-inflated and over-dispersed microbiome data. Strategies tailored for microbiome data are restricted to association testing, failing to allow other analytic goals such as visualization. We develop the Conditional Quantile Regression (ConQuR) approach to remove microbiome batch effects using a two-part quantile regression model. It is a fundamental advancement in the field because it is the first comprehensive method that accommodates the complex distributions of microbial read counts, and it generates batch-removed zero-inflated read counts that can be used in and benefit all usual subsequent analyses. We apply ConQuR to real microbiome data sets and demonstrate its state-of-the-art performance in removing batch effects while preserving or even amplifying the signals of interest.

bioinformatics↗

bioRxiv2021

Early life Western diet-induced memory impairments and gut microbiome changes in female rats are long-lasting despite healthy dietary intervention

ObjectiveConsumption of a Western diet during adolescence results in hippocampus (HPC)-dependent memory impairments and gut microbiome dysbiosis. Whether these adverse outcomes are reversible in adulthood following intervention with a healthy diet is unknown. Here we assessed the short- and long-term effects of adolescent consumption of a Western diet enriched with either sugar alone, or sugar and fat on metabolic outcomes, HPC-dependent memory, and gut microbiota. MethodsAdolescent female rats (PN 26) were fed a standard chow diet (CTL), a chow diet with access to 11% sugar solution (SUG), or a junk food cafeteria-style diet (CAF) containing a variety of fat- and/or sugar-enriched foods. During adulthood (PN 65+), metabolic outcomes, HPC-dependent memory, and gut microbial populations were evaluated both before and after a 5-week dietary intervention period where all groups were fed a diet of water standard chow. ResultsPrior to the dietary intervention both the CAF and SUG groups demonstrated impaired HPC-dependent memory, increased adiposity, and altered gut microbial populations relative to controls. However, impaired peripheral glucose regulation was only observed in the SUG group. The dietary intervention reversed the metabolic dysfunction in both the CAF and SUG groups, whereas HPC-dependent memory impairments were reversed in the SUG, but not the CAF group. The composition of the gut microbiota remained distinct from controls in both groups after dietary intervention. ConclusionsWhile the metabolic impairments associated with adolescent cafeteria diet consumption are reversible in adulthood with dietary intervention, the HPC-dependent memory impairments and the gut microbiome dysbiosis persist.

developmental biology↗

bioRxiv2021

On the robustness of inference of association with the gut microbiota in stool, swab and mucosal tissue samples

The gut microbiota plays an important role in human health and disease. Stool, swab and mucosal tissue samples have been used in individual studies to survey the microbial community but the consequences of using these different sample types are not completely understood. We previously reported differences in microbial community composition with 16S rRNA amplicon sequencing between stool, swab and mucosal tissue samples. Here, we extended the previous study to a larger cohort and performed shotgun metagenome sequencing of 1,397 stool, swab and mucosal tissue samples from 240 participants. Consistent with previous results, taxonomic composition of stool and swab samples was distinct, but still more similar to each other than mucosal tissue samples, which had a substantially different community composition, characterized by a high relative abundance of the mucus metabolizers Bacteroides and Subdoligranulum, as well as bacteria with higher tolerance for oxidative stress such as Escherichia. As has been previously reported, functional profiles were more uniform across sample types than taxonomic profiles with differences between stool and swab samples smaller, but mucosal tissue samples remained distinct from the other two types. When the taxonomic and functional profiles of different sample types were used for inference in association with host phenotypes of age, sex, body mass index (BMI), antibiotics or non-steroidal anti-inflammatory drugs (NSAIDs) use, hypothesis testing using either stool or swab gave broadly similar results, but inference performed on mucosal tissue samples gave results that were generally less consistent with either stool or swab. Our study represents an important resource for the experimental design of studies aimed to understand microbiota perturbations specific to defined micro niches within the human intestinal tract.

microbiology↗