Biology subjects

Madan, J. C.

Publications and source records attributed to Madan, J. C..

6 recordsLinked to original sources

bioRxiv2025

Optimizing Protocols for MicroRNA Profiling of Infant and Toddler Stool

BackgroundMicroRNAs (miRNAs) are increasingly being investigated as potential biomarkers for child development and disease. Although a growing number of studies are utilizing infant and toddler stool for transcriptomic analyses, no studies have compared protocols for preserving and extracting miRNAs from this specimen type, despite unique challenges, including abundant levels of RNAses and microbial RNA. MethodsTo address this, we first compared three commercially available kits and four preservation methods for their ability to yield high quality RNA from infant and toddler stool (Phase 1). RNA quality was determined by fragment analyzer. ResultsOf the three RNA extraction kits compared, Zymo BIOMICs yielded the highest overall RNA Quality Number (RQN) (median (range) RQN 9.4 (5.7-10.0)). Of the four preservation methods tested, stool collected in RNAlater and Zymo DNA/RNA Shield Fecal Collection Tubes yielded the highest two RQNs (median (range) RQN 9.8 (5.7-10.0) and 9.4 (5.4-10.0), respectively), which did not differ significantly from each other (p = 0.47). Second, using miRNA-seq we directly compared miRNA profiles for RNA extracted using the Zymo BIOMICs kit from paired aliquots of the same stool sample from four infants collected into RNAlater and Zymo DNA/RNA Shield Fecal Collection Tubes (Phase 2). Given that microbial sequences greatly outnumber human miRNAs in stool, reads were first classified as human versus microbial prior to aligning human-classified reads to miRBase v22.1. The percentage of reads classified as human and the percentage of human reads aligning to miRBase did not differ for samples collected in RNAlater versus Zymo Shield (p = 0.12 and p = 0.86, respectively). Furthermore, after multiple testing correction, normalized miRNA counts did not differ significantly between the two preservatives for any of the 42 human miRNAs detected across the eight samples. ConclusionsCollecting infant and toddler stool in either RNAlater or Zymo DNA/RNA Shield Fecal Collection Tubes, when paired with RNA extraction using the Zymo BIOMICs extraction kit, yielded high-quality RNA with similar human miRNA profiles. Moreover, of the 42 miRNAs that were detected, several (i.e., miR-194a-3p, miR-200c-3p, miR-26a-5p) are thought to contribute to overall gut homeostasis. These findings may inform protocols for future studies that aim to profile miRNAs in infant and toddler stool to evaluate their potential utility as biomarkers for childrens health.

developmental biology↗

bioRxiv2023

Persistent delay in maturation of the developing gut microbiota in infants with cystic fibrosis

The healthy human infant gut microbiome undergoes stereotypical changes in taxonomic composition between birth and maturation to an adult-like stable state. During this time, extensive communication between microbiota and the host immune system contributes to health status later in life. Although there are many reported associations between microbiota compositional alterations and disease in adults, less is known about how microbiome development is altered in pediatric diseases. One pediatric disease linked to altered gut microbiota composition is cystic fibrosis (CF), a multi-organ genetic disease involving impaired chloride secretion across epithelia and heightened inflammation both in the gut and at other body sites. Here, we use shotgun metagenomics to profile the strain-level composition and developmental dynamics of the infant fecal microbiota from several CF and non-CF longitudinal cohorts spanning from birth to greater than 36 months of life. We identify a set of keystone species whose prevalence and abundance reproducibly define microbiota development in early life in non-CF infants, but are missing or decreased in relative abundance in infants with CF. The consequences of these CF-specific differences in gut microbiota composition and dynamics are a delayed pattern of microbiota maturation, persistent entrenchment in a transitional developmental phase, and subsequent failure to attain an adult-like stable microbiota. We also detect the increased relative abundance of oral-derived bacteria and higher levels of fungi in CF, features that are associated with decreased gut bacterial density in inflammatory bowel diseases. Our results define key differences in the gut microbiota during ontogeny in CF and suggest the potential for directed therapies to overcome developmental delays in microbiota maturation.

microbiology↗

bioRxiv2022

Predicting Clinical Outcomes in Infants With Cystic Fibrosis From Stool Microbiota using Random Forest Algorithms

The gut-lung axis describes the interaction between microbiota in the gut and health status of the airway, whereby there is a bidirectional relationship facilitated by systemic transport of microbially-derived metabolites and immune factors. Cystic fibrosis (CF) is a genetic disease that is associated with dysbiosis of the gut microbiota. Recent literature has shown that the microbial dysbiosis in the CF gut can alter the hosts inflammatory status and that there are distinct microbial compositions in children with CF who have low versus high intestinal inflammation. These distinct microbial profiles can be used as signatures in children with CF (cwCF) to predict health outcomes. Here, we use supervised machine learning to train a random forest model on the distinct microbial composition of cwCF to predict: age (as a validation of the method), frequency of upper respiratory infection (URIfreq), and neutrophil to lymphocyte ratio (NLR), a clinical marker for systemic inflammation that negatively correlates with lung function. We find that the out of bag error, a measure of model accuracy, is lower when predicting age for cwCF compared to children without CF, consistent with previous data. We are able to predict high URIfreq with only 16% error and high NLR with 27% error. This machine learning pipeline may allow physicians and microbiome researchers to use the stool microbiota of cwCF as a tool for identifying individuals with the more negative airway clinical outcomes from this population, and potentially allow for early intervention. ImportanceChildren with CF (cwCF) often experience chronic respiratory infections, leading to progressive, irreversible lung function decline and significant morbidity and premature mortality. Modulator therapy has revolutionized the treatment of eligible adults with CF. cwCF as young as age 6 are now eligible to receive modulator therapy, although by early childhood many children have already experienced pulmonary exacerbations. Here we show that for cwCF, stool microbiota composition is associated with higher upper respiratory infection frequency and increased systemic inflammation. Our findings may aid in developing diagnostic tools that can allow physicians further understanding of which intestinal microbiota profiles are associated with health outcomes and to identify targets for preventative treatment for cwCF.

microbiology↗

bioRxiv2022

Development of the Intestinal Microbiome in Cystic Fibrosis in Early Life

Cystic Fibrosis is a heritable disease that causes altered physiology at mucosal sites; these changes result in chronic infection in the lung, significant gastrointestinal complications as well as dysbiosis of the gut microbiome, although the latter has been less well explored. Here, we describe the longitudinal development of the gut microbiome in a cohort of children with cystic fibrosis (cwCF) from birth through early childhood (0-4 years of age) using 16S rRNA gene amplicon sequencing of stool samples as a surrogate for the gut microbiota. Similar to healthy populations, alpha diversity of the gut microbiome increases significantly with age, but diversity plateaus [~]2 years of age for this CF cohort. Several taxa that have been associated with dysbiosis in CF change with age towards a more healthy-like composition; notable exceptions include Akkermansia, which decreases with age, and Blautia, which increases with age. We also examined the relative abundance and prevalence of nine taxa associated with CF lung disease, several of which persist across early life, highlighting the possibility of the lung being seeded directly from the gut early in life. Finally, we applied the Crohns dysbiosis index to each sample, and found that high Crohns-associated dysbiosis early in life (<2 years) was associated with significantly lower Bacteroides in samples collected from 2-4 years of age. Together, these data indicate a persisting dysbiosis in the gut microbiota as well as markers associated with inflammatory bowel disease early in life for cwCF. IMPORTANCECystic Fibrosis is a heritable disease that disrupts ion transport at mucosal surfaces, causing a buildup of mucus and dysregulation of microbial communities in both the lungs and the intestines. Persons with CF are known to have dysbiotic gut microbial communities, but the development of these communities over time beginning at birth have not been thoroughly studied. Here, we describe the development of the gut microbiome of cwCF throughout the first four years of life, during the critical window of both gut microbiome and immune development. Our findings indicate a persisting dysbiosis, the possibility of the gut microbiota as a reservoir of airway pathogens and a surprisingly early indication of a microbiota associated with inflammatory bowel disease.

microbiology↗

bioRxiv2020

Estimating Microbial Interaction Network:Zero-inated Latent Ising Model Based Approach

MotivationThroughout their lifespans, humans continually interact with the microbial world, including those organisms which live in and on the human body. Research in this domain has revealed the extensive links between the human-associated microbiota and health. In particular, the microbiota of the human gut plays essential roles in digestion, nutrient metabolism, immune maturation and homeostasis, neurological signaling, and endocrine regulation. Microbial interaction networks are frequently estimated from data and are an indispensable tool for representing and understanding the relationships among the microbes of a microbiota. In this high-dimensional setting, the zero-inflated and compositional data structure (subject to unit-sum constraint) pose challenges to the accurate estimation of microbial interaction networks. MethodWe propose the zero-inflated latent Ising (ZILI) model for microbial interaction network which assumes that the distribution of relative abundance of microbiota is determined by finite latent states. This assumption is partly supported by the existing findings in literature [20]. The ZILI model can circumvents the unit-sum constraint and alleviates the zero-inflation problem under given assumptions. As for the model selection of ZILI, a two-step algorithm is proposed. ZILI and two-step algorithm are evaluated through simulated data and subsequently applied in our investigation of an infant gut microbiome dataset from New Hampshire Birth Cohort Study. The results are compared with results from traditional Gaussian graphical model (GGM) and dichotomous Ising model (DIS). ResultsThrough the simulation studies, provided that the ZILI model is the true generative model for the data, it is shown that the two-step algorithm can estimate the graphical structure effectively and is robust to a range of alternative settings of the related factors. Both GGM and DIS can not achieve a satisfying performance in these settings. For the infant gut microbiome dataset, we use both ZILI and GGM to estimate microbial interaction network. The final estimated networks turn out to share a statistically significant overlap in which the ZILI and two-step algorithm tend to select the sparser network than those modeled by GGM. From the shared subnetwork, a hub taxon Lachnospiraceae is identified whose involvement in human disease development has been discovered recently in literature. AvailabilityThe data and programs involved in Section 4 and 5 are available on request from the correspondence author. ContactAnne.G.Hoen@dartmouth.edu Supplementary informationSupplementary materials are available at Bioinformatics

bioinformatics↗

bioRxiv2018

Altered Stool Microbiota of Infants with Cystic Fibrosis Shows Reduction in Genera Associated with Immune Programming

Previous work from our group indicated a connection between the gastrointestinal microbiota of infants and children with cystic fibrosis (CF) and airway disease in this population. Here we examine the stool microbiota of infants with CF and from the general population who did not have CF over the first year of life. CF children had reduced gastrointestinal Bacteroides and Bifidobacterium beginning in infancy, even after adjusting for antibiotic treatment. We also identify several metabolic pathways that are enriched or under represented among the microbial communities in the stool of these young patients with CF as compared to children without CF. In vitro studies demonstrated that exposure of the apical face of a polarized Intestinal cell line to Bacteroides thetaiotaomicron significantly reduced production of IL-8 secreted from both the apical and basolateral face of these cells, suggesting a mechanism whereby changes in the intestinal microflora could impact systemic inflammation. This work further establishes a link between gastrointestinal microbiota, systemic inflammation and airway disease, and presents the opportunity for therapeutic probiotic interventions.\n\nSignificance statementThere is a surprising link between gastrointestinal microbial communities and airway disease progression in CF. Here we show that infants with CF [≤]1 year of age show a distinct stool microbiota compared with children of a comparable age from a general population cohort. We detect associations between stool microbes and airway exacerbation events in the cohort of infants with CF, and in vitro studies provide a possible mechanism for this observation. These data argue that current therapeutics do not establish a healthy-like gastrointestinal microbiota in young patients with CF, and we suggest that interventions that direct the gastrointestinal microbiota closer to a healthy state may provide benefit to these patients.

microbiology↗