Biology subjects

Sprockett, D.

Publications and source records attributed to Sprockett, D..

3 recordsLinked to original sources

bioRxiv2022

Adaptive remodeling of the gut microbiome over long-distance migration

The gut microbiome can be thought of as a forgotten organ, owing to its profound effects on host phenotypes. Long-distance migratory birds are capable of adaptively modulating their physiology, raising the hypothesis that the microbiome of migratory birds may undergo a parallel remodeling process that helps to meet the energetic demands of long-distance migration. To test this hypothesis, we investigated changes in gut microbiome composition and function over the fall migration of a Neotropical-Nearctic migratory Blackpoll Warbler (Setophaga striata), which exhibits one of the longest known autumnal migratory routes of any songbird and rapidly undergoes extensive physiological remodeling during migration. Overall, our results showed that the Blackpoll warbler microbiome differed significantly across phases of fall migration. This pattern was driven by a dramatic increase in the relative abundance of Proteobacteria, and more specifically a single ASV belonging to the family Enterobacteriaceae. Further, blackpolls exhibited a progressive reduction in microbiome phylogenetic diversity and within-group variances over migration, indicating convergence of microbiome composition among individuals during long-distance migration. Metagenomic analysis revealed that the gut microbiome of staging blackpolls was enriched in bacterial pathways involved in vitamin, amino acid, and fatty acid biosynthesis, as well as carbohydrate metabolism, and that these pathways were in turn positively associated with host body mass and subcutaneous fat deposits. Together, these results provide evidence that the gut microbiome of migratory birds may undergo adaptive remodeling to meet the physiological and energetic demands of long-distance migration.

ecology↗

bioRxiv2019

Strategies for understanding dynamic, personalized profiles of host-derived proteins and microbes from human stool

Measuring host proteins through noninvasive stool-based assays opens new avenues for characterizing states of gastrointestinal health. However, the extent to which these proteins vary over time and between healthy subjects is poorly characterized. Here, we characterize technical and biological sources of variability in mass spectrometry-based measurements of host proteins in stool. We identify the proteins that most vary over time within an individual, and among different individuals. Finally, we examine and compare temporal and inter-individual variation in host protein and bacterial taxonomic profiles of the same fecal specimens. To address these issues, five self-reported healthy individuals were each sampled eight times over four weeks. First, we demonstrate that mass spectrometry-based identification and label-free quantification of stool proteins exhibit non-significant variability (p>0.05) between both technical and preparative replicates for a subset of 78 proteins, supporting the utility of this method for biomarker measurement. Second, although 13 human stool proteins varied significantly in relative abundance over time within individuals, 58 proteins varied significantly (at least four-fold) between subjects. The average pair-wise difference between individuals was greater than the average within-subject difference for both the proteome and microbiome datasets (p<0.0001). Fecal host proteins, like the traditional fecal protein marker, calprotectin, unambiguously pointed to innate and adaptive immune responses. For example, one subjects fecal protein profile suggested a sub-clinical inflammatory state. From these data, we conclude that host-centric protein measurements in stool reveal a wide range of variation during states of apparent health, and add a valuable complementary insight into host-microbiota relationships. IMPORTANCEHuman proteins in stool hold untapped potential for characterizing gastrointestinal health. To fully harness this potential and create a baseline of healthy stool protein abundances and identifications, it will be important to establish the extent to which these proteins might vary in the absence of disease. This study quantifies the major sources of variation in stool protein abundance data. We assessed technical, preparative, temporal, and inter-subject variability of human protein abundances in stool and found that among these sources, differences between subjects accounted for the greatest amount of variation, followed by temporal differences, and then technical factors. Our paired microbiome analysis found matching patterns of temporal and inter-subject variability. By characterizing multiple variance parameters in host stool protein abundances, our analysis helps to contextualize a wide range of future disease-focused stool studies as well as elucidate host-microbe interactions.

molecular biology↗

bioRxiv2018

Treatment-Specific Composition of Gut Microbiota Is Associated with Disease Remission in a Pediatric Crohn’s Disease Cohort

BackgroundThe beneficial effects of antibiotics in Crohns disease (CD) depend in part on the gut microbiota but are inadequately understood. We investigated the impact of metronidazole (MET) and metronidazole plus azithromycin (MET+AZ) on the microbiota in pediatric CD, and the use of microbiota features as classifiers or predictors of disease remission.\n\nMethods16S rRNA-based microbiota profiling was performed on stool samples from 67 patients in a multinational, randomized, controlled, longitudinal, 12-week trial of MET vs. MET+AZ in children with mild to moderate CD. Profiles were analyzed together with disease activity, and then used to construct Random Forest models to classify remission or predict treatment response.\n\nResultsBoth MET and MET+AZ significantly decreased diversity of the microbiota and caused large treatment-specific shifts in microbiota structure at week 4. Disease remission was associated with a treatment-specific microbiota configuration. Random Forest models constructed from microbiota profiles pre- and during antibiotic treatment with metronidazole accurately classified disease remission in this treatment group (AUC of 0.879, 95% CI 0.683, 0.9877; sensitivity 0.7778; specificity 1.000, P < 0.001). A Random Forest model trained on preantibiotic microbiota profiles predicted disease remission at week 4 with modest accuracy (AUC of 0.8, P = 0.24).\n\nConclusionsMET and MET+AZ antibiotic regimens in pediatric CD lead to distinct gut microbiota structures at remission. It may be possible to classify and predict remission based in part on microbiota profiles, but larger cohorts will be needed to realize this goal.\n\nSummaryWe investigated the impact of metronidazole and metronidazole plus azithromycin on the gut microbiota in pediatric Crohns disease. Disease remission was associated with a treatment-specific microbiota configuration, and could be predicted based on pre-antibiotic microbiota profiles.

microbiology↗