Location: Animal Biosciences & Biotechnology Laboratory
2024 Annual Report
Objectives
Objective 1. Determine interactions occurring across kingdoms (bacterial, fungal, porcine) at the microbe-lumen interface of the gut.
Sub-objective 1A: Identify quorum sensing molecules used by K. slooffiae.
Sub-objective 1B: Use microbiome datasets to determine interactions occurring between taxa, identify keystone taxa, and identify molecules present in EV that may be mediating these interactions.
Sub-objective 1C. Identify the mechanism of action for the QSM identified in the pig intestinal tract for biological effects on the IPEC-J2 jejunal cell line.
Objective 2. Identify alternatives to antibiotics through bioinformatics-based approaches, including the microbiome, metagenome, and metatranscriptome approaches, and examine their effects on the innate immune response at the gut mucosa.
Sub-objective 2A: Use ML to model microbiome data to identify species that are critical determinants of good and poor growth.
Sub-objective 2B: Identify potential probiotic candidates through in vivo testing of hypotheses generated during network analyses in Objectives 1B and 2A.
Objective 3. Identify the role of Kazachstania slooffiae, a porcine fungal commensal, in pig performance through in vivo and in vitro studies.
Sub-objective 3A: IPEC-J2 cell line challenges with live or heat killed K. slooffiae to analyze innate immune response.
Sub-objective 3B: Dose-response feeding trial of K. slooffiae to post-weaning pigs.
Objective 4. Identify mechanisms of action of antibiotics and of their alternatives in promoting the growth and well-being of swine by examining metagenomes and metatranscriptomes in the swine GI tract.
Sub-objective 4A: Feeding trial in pigs with in-feed antibiotics.
Sub-objective 4B. Dietary probiotic effects on pre- and post-weaning growth and intestinal physiology.
Sub-objective 4C. Evaluate Clostridium scindens to promote the preweaning growth of pigs.
Sub-objective 4D: Use ML in conjunction with metagenomic data to identify species, genes, and pathways that are critical in microbiome response to low dose antibiotics.
Approach
This project aims to determine the mechanisms behind antibiotic-induced animal growth and identify potential alternative growth promotants in swine during the weaning transition. Weaning is a critical point in piglet development marked by elevated stress and a predisposition to infections by opportunistic pathogens. These infections result in financial loss to farmers and producers due to increased mortality rates, reduced growth performance, increased feed costs, and veterinary expenses. Previously, in-feed antibiotics were utilized to prevent infections with the added benefit of antibiotic-associated weight gain, but the ban of in-feed antibiotics for agricultural animals presents a new challenge. Identification of alternative interventions and improved production strategies are needed to increase animal growth and disease resilience, but the mechanism behind antibiotic-induced growth remains unknown. We propose to utilize a combinatorial approach of in vitro, in vivo, and bioinformatics-based methods to identify mechanisms behind antibiotic-induced growth performance in piglets and physiological pathways altered by in-feed antibiotics to allow targeted identification of alternatives to antibiotics (ATA). These data will be utilized to optimize machine learning (ML) methods to identify microbiome members and molecules of interest in growth performance. These findings will be used to clarify the mechanism of growth promotion, thus permitting educated targeting of species and physiological pathways as ATA. Further, the microbial interactions in the gut of piglets will be analyzed to determine mechanisms behind cross-kingdom signaling that alter piglet health and growth during the weaning transition. This project will enhance the scientific understanding of the microbial network in the porcine gut and its role in growth promotion. This proposal will also determine physiological pathways altered by in-feed antibiotics to allow targeted identification of ATA in swine during the weaning transition. Farmers and producers will directly benefit from implementing validated alternate production management practices that will directly impact swine growth efficiency.
Progress Report
Progress was made on all Objectives, all of which fall under National Programs NP101, Food Animal Production, Component 1, Food Animal Production Efficiencies, Food Animal Well-Being, and
Adaptation of Food Animals to Diverse Production Systems, and Component 2, Understanding, Improving, and Effectively Using Food Animal Genetic and Genomic Resources. The project aims to identify the mechanisms by which in-feed antibiotics confer positive health benefits in the weanling pig. Due to farrowing barn renovations, pig experiments were unable to be performed.
The intestinal epithelial barrier plays a critical role in piglet health and growth, and tight junction status is often used as an indicator of intestinal health. Kazachstania (K) slooffiae is a prominent commensal fungus in the gastrointestinal tract of piglets. Here, researchers used in vitro assays to test whether the fungus affects intestinal barrier function. K. slooffiae grown in liquid media was separated into supernatant (media with K. slooffiae secreted metabolites) and cellular fractions and applied to swine epithelial cells, IPEC-J2. Transepithelial electrical resistance (TEER) and FITC-dextran were used to assess cell permeability, and lactate dehydrogenase was assayed to measure cell viability. When subjected to a high dose of media from K. slooffiae, TEER measurements were significantly lower than controls, indicating a decrease in tight barrier function, but this relationship was also noted upon application of media without K. slooffiae (control). However, a high dose of media also significantly increased permeability of FITC-dextran while the control group was unaffected. At low media doses, likely comparable to typical physiological levels, permeability in both assays was not significantly altered. These results (which fulfill Sub-objective 3A), suggest that high concentrations of metabolites secreted by K. slooffiae into the media increase intestinal cell permeability, while normal physiological levels of these metabolites have no impact. Prior findings indicate that K. slooffiae augments the growth of health-promoting bacteria in vitro. Together, these findings suggest that the effects of K. slooffiae on piglet health are likely mediated via multiple mechanisms, and outcomes depend on fungal abundance. Additional in vivo experiments are needed to determine the effects of K. slooffiae and other commensal gut microbes on piglet health.
Multiple sequencing datasets were generated, and bioinformatics approaches were used to study the impact of microbiome taxa on piglet growth. There were 726 gastrointestinal organ and fecal samples sequenced using 16S (bacterial) and ITS (fungal) regions from a collaborative experiment at the ARS Research Center in Clay Center, Nebraska. These data were used to construct machine learning models to predict high and low growth pigs based on microbiome composition. Models achieved fair accuracy, and several rare taxa were identified as potential candidates to distinguish microbiomes from high and low growth animals. However, results were not always consistent across different models and data pre-processing methods. Thus, higher accuracy datasets will be used to determine whether model stability can be improved.
Fecal samples (420) were selected from pigs with a range of high and low growth and prepared for both short and long-read metagenomic sequencing. DNA extraction protocols were optimized for both read types. All 420 samples were sequenced with short read technology, and a subset of 30 samples were subjected to deep long-read Pacbio sequencing in collaboration with the U.S. Food and Drug Administration (FDA). All data are currently being curated and processed for additional machine learning analyses and traditional statistical analyses (Sub-objective 2A). Long read data, in conjunction with Hi-C technology (proximity ligation) are expected to produce dozens of novel bacterial genome assemblies (useful as references for additional analyses in Objective 2). Both datasets will provide high resolution taxonomic identifications and functional information (genes, pathways), and will also provide a foundation to assess associations between microbial taxa and piglet growth.
Alongside the production of high-resolution datasets, researchers are piloting strategies to circumvent challenging aspects of microbiome data analysis. Due to the constraints of high throughput sequencers, data are compositional, meaning that abundances of all taxa in a sample must sum to one. If the relative abundance of one taxon increases, then the relative abundances of all others necessarily decrease. This interdependence does not necessarily reflect true measures of absolute abundances in vivo and can thus lead to spurious results. Researchers in Beltsville, Maryland, are testing computational approaches to alleviate erroneous data interpretations, and also implementing several laboratory methods to obtain absolute, instead of relative abundance values. Microbial taxa were spiked into sequencing samples at specific concentrations and will be used to normalize abundance values. Also, qPCR methods were developed to approximate total microbial load in samples which will be used to convert relative to absolute abundances. These methods will facilitate the testing of hypotheses to determine whether abundances of specific microbes or total microbial load affects piglet growth and will also improve accuracy of other bioinformatics analyses in the 5-year plan.
To complement genomic studies, researchers also analyzed the total protein content from piglet fecal samples using mass spectrometry. Prior work described changes in total microbial protein expression before and after weaning and identified bacteria which play critical roles in digestion of carbohydrates and production of bioactive metabolites such as short chain fatty acids. Current work examines the role of the microbial community in amino acid metabolism (contributes to Objective 2). Proteins involved in the synthesis of several amino acids which are limiting for piglet growth including L-lysine and L-threonine were more abundant in the microbiome of post-weaned piglets, while the levels of proteins involved in the production of the amino acids L-serine/glycine, and the essential branched-chain amino acids L-valine and L-isoleucine remained abundant both before and after weaning. Microbial genera including Bacteroides, Subdoligranulum, and Eisenbergiella were the principal producers of amino acids in nursing pigs, whereas Mitsuokella, Muribaculum, and Prevotella contributed to amino acid synthesis after weaning. Additional studies which address the fate of amino acids produced by bacterial taxa will determine the utility of identified taxa as probiotic candidates to augment production of growth-limiting amino acids in swine.
Researchers in Beltsville, Maryland, are evaluating additional laboratory protocols which will be applied to fresh piglet samples once they become available. A flow cytometry method is under development to detect various immune markers in piglet blood. RNA-Scope, an in situ hybridization assay to visualize target RNAs in cells has been successfully applied to chicken intestinal tissue and will be applied to piglet intestinal tissue. Lastly, a method to section hypothalamus tissue from preserved piglet brains was developed based on fixative diffusion instead of traditional labor-intensive perfusion techniques.
Accomplishments