A Microbiome DNA Enrichment Method for Next-Generation Sequencing Sample Preparation

HAMLET, a human milk protein-lipid complex, modulates amoxicillin induced changes in an ex vivo biofilm model of the oral microbiome

Challenges from infections caused by biofilms and antimicrobial resistance highlight the need for novel antimicrobials that work in conjunction with antibiotics and minimize resistance risk. In this study we investigated the composite effect of HAMLET (human alpha-lactalbumin made lethal to tumor cells), a human milk protein-lipid complex and amoxicillin on microbial ecology using an ex vivo oral biofilm model with pooled saliva samples. HAMLET was chosen due to its multi-targeted antimicrobial mechanism, together with its synergistic effect with antibiotics on single species pathogens, and low risk of resistance development. The combination of HAMLET and low concentrations of amoxicillin significantly reduced biofilm viability, while each of them alone had little or no impact. Using a whole metagenomics approach, we found that the combination promoted a remarkable shift in overall microbial composition compared to the untreated samples. A large proportion of the bacterial species in the combined treatment were Lactobacillus crispatus, a species with probiotic effects, whereas it was only detected in a minor fraction in untreated samples. Although resistome analysis indicated no major shifts in alpha-diversity, the results showed the presence of TEM beta-lactamase genes in low proportions in all treated samples but absence in untreated samples. Our study illustrates HAMLET's capability to alter the effects of amoxicillin on the oral microbiome and potentially favor the growth of selected probiotic bacteria when in combination. The findings extend previous knowledge on the combined effects of HAMLET and antibiotics against target pathogens to include potential modulatory effects on polymicrobial biofilms of human origin.

Carotenoids in Health as Studied by Omics-Related Endpoints

Carotenoids have been associated with risk reduction for several chronic diseases, including the association of their dietary intake/circulating levels with reduced incidence of obesity, type 2 diabetes, certain types of cancer, and even lower total mortality. In addition to some carotenoids constituting vitamin A precursors, they are implicated in potential antioxidant effects and pathways related to inflammation and oxidative stress, including transcription factors such as nuclear factor κB and nuclear factor erythroid 2-related factor 2. Carotenoids and metabolites may also interact with nuclear receptors, mainly retinoic acid receptor/retinoid X receptor and peroxisome proliferator-activated receptors, which play a role in the immune system and cellular differentiation. Therefore, a large number of downstream targets are likely influenced by carotenoids, including but not limited to genes and proteins implicated in oxidative stress and inflammation, antioxidation, and cellular differentiation processes. Furthermore, recent studies also propose an association between carotenoid intake and gut microbiota. While all these endpoints could be individually assessed, a more complete/integrative way to determine a multitude of health-related aspects of carotenoids includes (multi)omics-related techniques, especially transcriptomics, proteomics, lipidomics, and metabolomics, as well as metagenomics, measured in a variety of biospecimens including plasma, urine, stool, white blood cells, or other tissue cellular extracts. In this review, we highlight the use of omics technologies to assess health-related effects of carotenoids in mammalian organisms and models.

Microbial DNA extraction of high-host content and low biomass samples: Optimized protocol for nasopharynx metagenomic studies

Introduction

Low microbial biomass and high human DNA content in nasopharyngeal aspirate samples hinder comprehensive characterization of microbiota and resistome. We obtained samples from premature infants, a group with increased risk of developing respiratory disorders and infections, and consequently frequent exposure to antibiotics. Our aim was to devise an optimal protocol for handling nasopharyngeal aspirate samples from premature infants, focusing on host DNA depletion and microbiome and resistome characterization.

Methods

Three depletion and three DNA extraction protocols were compared, using RT-PCR and whole metagenome sequencing to determine the efficiency of human DNA removal, taxonomic profiling and assignment of antibiotic resistance genes. Protocols were tested using mock communities, as well as pooled and individual patient samples.

Results

The only extraction protocol to retrieve the expected DNA yield from mock community samples was based on a lytic method to improve Gram positive recovery (MasterPure™). Host DNA content in non-depleted aliquots from pooled patient samples was 99%. Only samples depleted with MolYsis™ showed satisfactory, but varied reduction in host DNA content, in both pooled and individual patient samples, allowing for microbiome and resistome characterisation (host DNA content from 15% to 98%). Other depletion protocols either retrieved too low total DNA yields, preventing further analysis, or failed to reduce host DNA content. By using Mol_MasterPure protocol on aliquots from pooled patient samples, we increased the number of bacterial reads by 7.6 to 1,725.8-fold compared to non-depleted reference samples. PCR results were indicative of achieved microbial enrichment. Individual patient samples processed with Mol_MasterPure protocol varied greatly in total DNA yield, host DNA content (from 40% to 98%), species and antibiotic resistance gene richness.

Discussion

Despite high human DNA and low microbial biomass content in nasopharynx aspirates of preterm infants, we were able to reduce host DNA content to levels compatible with downstream shotgun metagenomic analysis, including bacterial species identification and coverage of antibiotic resistance genes. Whole metagenomic sequencing of microbes colonizing the nasopharynx may contribute to explaining the possible role of airway microbiota in respiratory conditions and reveal carriage of antibiotic resistance genes.

Intestinal Microbiota and Liver Diseases: Insights into Therapeutic Use of Traditional Chinese Medicine

Liver disease is a leading cause of global morbidity and mortality, for which inflammation, alcohol use, lipid metabolic disorders, disturbance to bile acid metabolism, and endotoxins are common risk factors. Traditional Chinese Medicine (TCM) with its "holistic approach" is widely used throughout the world as a complementary, alternative therapy, due to its clinical efficacy and reduced side effects compared with conventional medicines. However, due to a lack of reliable scientific evidence, the role of TCM in the prevention and treatment of liver disease remains unclear. Over recent years, with the rapid development of high-throughput sequencing, 16S rRNA detection, and bioinformatics methodology, it has been gradually recognized that the regulation of intestinal microbiota by TCM can play a substantial role in the treatment of liver disease. To better understand how TCM regulates the intestinal microbiota and suppresses liver disease, we have reviewed and analyzed the results of existing studies and summarized the relationship and risk factors between intestinal microbiota and liver disease. The present review summarizes the related mechanisms by which TCM affects the composition and metabolites of the intestinal microbiome.

Sampling Strategies for Three-Dimensional Spatial Community Structures in IBD Microbiota Research

Identifying intestinal microbiota is arguably an important task that is performed to determine the pathogenesis of inflammatory bowel diseases (IBD); thus, it is crucial to collect and analyze intestinally-associated microbiota. Analyzing a single niche to categorize individuals does not enable researchers to comprehensively study the spatial variations of the microbiota. Therefore, characterizing the spatial community structures of the inflammatory bowel disease microbiome is critical for advancing our understanding of the inflammatory landscape of IBD. However, at present there is no universally accepted consensus regarding the use of specific sampling strategies in different biogeographic locations. In this review, we discuss the spatial distribution when screening sample collections in IBD microbiota research. Here, we propose a novel model, a three-dimensional spatial community structure, which encompasses the x-, y-, and z-axis distributions; it can be used in some sampling sites, such as feces, colonoscopic biopsy, the mucus gel layer, and oral cavity. On the basis of this spatial model, this article also summarizes various sampling and processing strategies prior to and after DNA extraction and recommends guidelines for practical application in future research.