Biology subjects

Peterson, D.

Publications and source records attributed to Peterson, D..

9 recordsLinked to original sources

bioRxiv2025

The microbiota elicits compensatory adaptation in a seasonally-adapting animal host

Seasonal adaptation in Drosophila melanogaster is a model for understanding the evolutionary responses of organisms to cyclical environmental changes, including roles played by associated microorganisms ( microbiota). Here we examined how the microbiota influences D. melanogaster seasonal adaptation by rearing flies in outdoor mesocosms, fed diets inoculated with different bacterial strains that have distinct influences on the flies life history. The bacterial treatments influenced fly population dynamics and microbiota composition over a summer-to-fall season. The developmental phenotype of the treated flies initially differed but converged over time in flies reared with a complete microbial community. Conversely, rearing the flies free of their colonizing microorganisms revealed that the bacterial treatments led to evolution of distinct developmental phenotypes. The development time of flies from the different treatments consistently adapted to compensate for the direct influence of the bacteria on host development; e.g., flies evolved faster development times if they were inoculated with microbes that slowed development. This compensatory trend was apparent in flies reared in a second location and season, and is consistent with a previous report of wild-sampled flies whose development phenotype segregated with their microbiota composition. Together, these results reveal that microbiota-dependent selection consistently elicits compensatory adaptation in seasonally-evolving flies, which we conclude is a mechanism whereby horizontally-acquired, low-fidelity microbial partners can shape the evolution of their animal hosts. ImportanceUnderstanding how organisms adapt to seasonal change can model evolutionary responses in a broader changing world. Drosophila melanogaster is a powerful model for studying these dynamics, especially when considering the influence of transient yet impactful colonizing microorganisms. This study reveals that microbial partners can drive consistent, compensatory adaptation in host development across seasons and locations. By demonstrating that flies evolve faster development times in response to microbes that slow a model hosts period of growth and development, this work highlights one way that the microbiota can influence adaptation in their animal hosts. These findings also provide evidence that low-fidelity, horizontally-acquired microbes can exert selective pressures strong enough to shape host life history traits. These insights underscore the microbiotas role as an ecological and evolutionary force.

microbiology↗

bioRxiv2023

Time-resolved transcriptomics reveal a mechanism of host niche defense: beneficial root endophytes deploy a host-protective antimicrobial GH18-CBM5 chitinase

Associations between plants and beneficial root-endophytic fungi enhance plant performance by improving nutrient uptake, abiotic stress tolerance and disease resistance. To successfully colonize different host plants and defend their host niche against competing microbes, but also to cooperate with beneficial bacterial members of the microbiota, root endophytes such as Sebacinales secrete a multitude of tightly regulated effector-proteins and carbohydrate-active enzymes. However, the functions, specificity, and regulation of these proteins remain poorly understood. In this study, we employ time-resolved transcriptomics to analyse the gene expression profiles of two Sebacinales members interacting with organisms from different kingdoms of life. We identified crucial genes for plant colonization and intermicrobial competition, including a fungal GH18-CBM5 chitinase specifically upregulated in response to the phytopathogenic fungus Bipolaris sorokiniana. This chitinase protects the plant hosts against the pathogen, reducing fungal biomass and disease symptoms in barley and Arabidopsis thaliana. Our findings shed light on interaction partner specific gene expression in Sebacinales endophytes, with potential applications in enhancing plant health and resilience. Bullet pointsO_LIBoth Serendipita indica (Si) and Serendipita vermifera (Sv) show similar transcriptional responses to three host species and the phytopathogen Bipolaris sorokiniana (Bs), indicating common interaction principles between Sebacinales and plant hosts or fungi. C_LIO_LIThese shared mechanisms involve the activation of effector genes like small secreted proteins and carbohydrate-active enzymes. C_LIO_LICooperation with beneficial bacteria elicits only minimal transcriptomic alterations in Sebacinales compared to plants and Bs. C_LIO_LISebacinales respond to Bs by upregulating a specific GH18-CBM5 chitinase unique to Basidiomycota within the fungal kingdom, inhibiting Bs growth and reducing disease symptoms in Arabidopsis thaliana and barley. C_LI

microbiology↗

bioRxiv2023

Brain Charts for People Living with Multiple Sclerosis

Multiple sclerosis (MS) is associated with brain volume loss throughout the disease course. Currently available automated segmentation methods can measure total brain volume as well as ventricular volume, which has been advocated as a robust surrogate for brain volume based on clinically acquired magnetic resonance imaging (MRI). However, brain and ventricle volumes change naturally with age and may be susceptible to biases from differences in acquisition hardware, imaging protocol, and image quality, in addition to statistical biases such as regression to the mean. In this work, brain charts for people living with MS were established that account for patient biological sex, age, and differences in acquisition and image quality. 379 subjects were imaged longitudinally at 5 MS centers using 13 MRI scanner models from 2 scanner manufacturers employing a variety of protocols that included T1-weighted and T2-weighted FLAIR imaging. Generalized Additive Models for Location Scale and Shape (GAMLSS) were employed, and scanner metadata as well as automated assessments of image quality were modeled. Cross-sectional brain charts and conditional, longitudinal brain charts were estimated separately in female and male participants resulting in interpretable and intuitive centile estimates. These findings indicate that brain charts for people living with MS are a promising method for turning quantitative volumetrics into actionable knowledge about a patients disease. HighlightsO_LIInterpreting observed changes in brain volume can be challenging due to statistical biases including regression to the mean. C_LIO_LIBrain size changes naturally with age and may be susceptible to biases associated with acquisition hardware, imaging protocol, and image quality. C_LIO_LIBrain charts for people living with MS are a promising method for translating quantitative volumetrics into interpretable knowledge about a patients disease. C_LI

neuroscience↗

bioRxiv2022

Unsupervised Discovery of Ancestry Informative Markers and Genetic Admixture Proportions in Biobank-Scale Data Sets

Admixture estimation plays a crucial role in ancestry inference and genomewide association studies (GWAS). Computer programs such as ADMIXTURE and STRUCTURE are commonly employed to estimate the admixture proportions of sample individuals. However, these programs can be overwhelmed by the computational burdens imposed by the 105 to 106 samples and millions of markers commonly found in modern biobanks. An attractive strategy is to run these programs on a set of ancestry informative SNP markers (AIMs) that exhibit substantially different frequencies across populations. Unfortunately, existing methods for identifying AIMs require knowing ancestry labels for a subset of the sample. This supervised learning approach creates a chicken and the egg scenario. In this paper, we present an unsupervised, scalable framework that seamlessly carries out AIM selection and likelihood-based estimation of admixture proportions. Our simulated and real data examples show that this approach is scalable to modern biobank data sets. Our implementation of the method is called OpenADMIXTURE.

bioinformatics↗

bioRxiv2021

One Health Investigation of SARS-CoV-2 Infection and Seropositivity among Pets in Households with Confirmed Human COVID-19 Cases - Utah and Wisconsin, 2020

BackgroundApproximately 67% of U.S. households have pets. Limited data are available on SARS-CoV-2 in pets. We assessed SARS-CoV-2 infection in pet cohabitants as a sub-study of an ongoing COVID-19 household transmission investigation. MethodsMammalian pets from households with [≥]1 person with laboratory-confirmed COVID-19 were eligible for inclusion from April-May 2020. Demographic/exposure information, oropharyngeal, nasal, rectal, and fur swabs, feces, and blood were collected from enrolled pets and tested by rRT-PCR and virus neutralization assays. FindingsWe enrolled 37 dogs and 19 cats from 34 of 41 eligible households. All oropharyngeal, nasal, and rectal swabs tested negative by rRT-PCR; one dogs fur swabs (2%) tested positive by rRT-PCR at the first animal sampling. Among 47 pets with serological results from 30 households, eight (17%) pets (4 dogs, 4 cats) from 6 (20%) households had detectable SARS-CoV-2 neutralizing antibodies. In households with a seropositive pet, the proportion of people with laboratory-confirmed COVID-19 was greater (median 79%; range: 40-100%) compared to households with no seropositive pet (median 37%; range: 13-100%) (p=0.01). Thirty-three pets with serologic results had frequent daily contact ([≥]1 hour) with the human index patient before the persons COVID-19 diagnosis. Of these 33 pets, 14 (42%) had decreased contact with the human index patient after diagnosis and none (0%) were seropositive; of the 19 (58%) pets with continued contact, 4 (21%) were seropositive. InterpretationsSeropositive pets likely acquired infection from humans, which may occur more frequently than previously recognized. People with COVID-19 should restrict contact with animals. FundingCenters for Disease Control and Prevention, U.S. Department of Agriculture

microbiology↗

bioRxiv2021

Comparative analysis of 16S rRNA gene and metagenome sequencing in pediatric gut microbiomes

The colonization of the human gut microbiome begins at birth, and, over time, these microbial communities become increasingly complex. Most of what we currently know about the human microbiome, especially in early stages of development, was described using culture-independent sequencing methods that allow us to identify the taxonomic composition of microbial communities using genomic techniques, such as amplicon or shotgun metagenomic sequencing. Each method has distinct tradeoffs, but there has not been a direct comparison of the utility of these methods in stool samples from very young children, which have different features than those of adults. We compared the effects of profiling the human infant gut microbiome with 16S rRNA amplicon versus shotgun metagenomic sequencing techniques in 130 fecal samples; younger than 15, 15-30, and older than 30 months of age. We demonstrate that observed changes in alpha-diversity and beta-diversity with age occur to similar extents using both profiling methods. We also show that 16S rRNA profiling identified a larger number of genera and we find several genera that are missed or underrepresented by each profiling method. We present the link between alpha diversity and shotgun metagenomic sequencing depth for children of different ages. These findings provide a guide for selecting an appropriate method and sequencing depth for the three studied age groups.

microbiology↗

bioRxiv2020

Lymphocyte-Specific Biomarkers Associated with Preterm Birth and Bronchopulmonary Dysplasia

Many premature babies who are born with neonatal respiratory distress syndrome (RDS) go on to develop Bronchopulmonary Dysplasia (BPD) and later Post-Prematurity Respiratory Disease (PRD) at one year corrected age, characterized by persistent or recurrent lower respiratory tract symptoms frequently related to inflammation and viral infection. Transcriptomic profiles were generated from sorted peripheral blood CD8+ T cells of preterm and full-term infants enrolled with consent in the NHLBI Prematurity and Respiratory Outcomes Program (PROP) at the University of Rochester and the University at Buffalo. We identified outcome-related gene expression patterns following standard methods to identify markers for oxygen utilization and BPD as outcomes in extremely premature infants. We further identified predictor gene sets for BPD based on transcriptomic data adjusted for gestational age at birth (GAB). RNA-Seq analysis was completed for CD8+ T cells from 145 subjects. Among the subjects with highest risk for BPD (born at <29 weeks gestational age (GA); n=72), 501 genes were associated with oxygen utilization. In the same set of subjects, 571 genes were differentially expressed in subjects with a diagnosis of BPD and 105 genes were different in BPD subjects as defined by physiologic challenge. A set of 92 genes could predict BPD with a moderately high degree of accuracy. We consistently observed dysregulation of NRF2, HIPPO and CD40-associated pathways in BPD. Using gene expression data from both premature and full-term subjects (n=116), we identified a 28 gene set that predicted the PRD status with a moderately high level of accuracy. Transcriptomic data from sort-purified peripheral blood CD8+ T cells from 145 preterm and full-term infants identified sets of molecular markers associated with independent development of BPD in extremely premature infants at high risk for the disease and of PRD among the preterm and full-term subjects.

genomics↗

bioRxiv2019

Homoeologous gene expression and co-expression network analyses and evolutionary inference in allopolyploids

Polyploidy is a widespread phenomenon throughout eukaryotes. Due to the coexistence of duplicated genomes, polyploids offer unique challenges for estimating gene expression levels, which is essential for understanding the massive and various forms of transcriptomic responses accompanying polyploidy. Although previous studies have explored the bioinformatics of polyploid transcriptomic profiling, the causes and consequences of inaccurate quantification of transcripts from duplicated gene copies have not been addressed. Using transcriptomic data from the cotton genus (Gossypium) as an example, we present an analytical workflow to evaluate a variety of bioinformatic method choices at different stages of RNA-seq analysis, from homoeolog expression quantification to downstream analysis used to infer key phenomena of polyploid expression evolution. In general, GSNAP-PolyCat outperforms other quantification pipelines tested, and its derived expression dataset best represents the expected homoeolog expression and co-expression divergence. The performance of co-expression network analysis was less affected by homoeolog quantification than by network construction methods, where weighted networks outperformed binary networks. By examining the extent and consequences of homoeolog read ambiguity, we illuminate the potential artifacts that may affect our understanding of duplicate gene expression, including an over-estimation of homoeolog co-regulation and the incorrect inference of subgenome asymmetry in network topology. Taken together, our work points to a set of reasonable practices that we hope are broadly applicable to the evolutionary exploration of polyploids.

bioinformatics↗

bioRxiv2018

Adaptive strategies of the candidate probiotic E. coli Nissle in the mammalian gut

Probiotics are living microorganisms that are increasingly used as gastrointestinal therapeutics by virtue of their innate or engineered genetic function. Unlike abiotic therapeutics, probiotics can replicate in their intended site, subjecting their genomes and therapeutic properties to natural selection. By exposing the candidate probiotic E. coli Nissle (EcN) to the mouse gastrointestinal tract over several weeks, we uncovered the consequences of gut transit, inter-species competition, antibiotic pressure, and engineered genetic function on the processes under selective pressure during both within-genome and horizontal evolutionary modes. We then show the utility of EcN as a chassis for engineered function by achieving the highest reported reduction in serum phenylalanine levels in a mouse model of phenylketonuria using an engineered probiotic. Collectively, we demonstrate a generalizable pipeline which can be applied to other probiotic strains to better understand their safety and engineering potential.

evolutionary biology↗