StrainIQ: A Novel n-Gram-Based Method for Taxonomic Profiling of Human Microbiota at the Strain Level.

The emergence of next-generation sequencing (NGS) technology has greatly influenced microbiome research and led to the development of novel bioinformatics tools to deeply analyze metagenomics datasets. Identifying strain-level variations in microbial communities is important to understanding the onset and progression of diseases, host-pathogen interrelationships, and drug resistance, in addition to designing new therapeutic regimens. In this study, we developed a novel tool called StrainIQ (strain identification and quantification) based on a new n-gram-based (series of n number of adjacent nucleotides in the DNA sequence) algorithm for predicting and quantifying strain-level taxa from whole-genome metagenomic sequencing data. We thoroughly evaluated our method using simulated and mock metagenomic datasets and compared its performance with existing methods. On average, it showed 85.8% sensitivity and 78.2% specificity on simulated datasets. It also showed higher specificity and sensitivity using n-gram models built from reduced reference genomes and on models with lower coverage sequencing data. It outperforms alternative approaches in genus- and strain-level prediction and strain abundance estimation. Overall, the results show that StrainIQ achieves high accuracy by implementing customized model-building and is an efficient tool for site-specific microbial community profiling.

Microbiome diversity in African American, European American, and Egyptian colorectal cancer patients.

Purpose: Although there is an established role for microbiome dysbiosis in the pathobiology of colorectal cancer (CRC), CRC patients of various race/ethnicities demonstrate distinct clinical behaviors. Thus, we investigated microbiome dysbiosis in Egyptian, African American (AA), and European American (EA) CRC patients. Patients and methods: CRCs and their corresponding normal tissues from Egyptian (n = 17) patients of the Alexandria University Hospital, Egypt, and tissues from AA (n = 18) and EA (n = 19) patients at the University of Alabama at Birmingham were collected. DNA was isolated from frozen tissues, and the microbiome composition was analyzed by 16S rRNA sequencing. Differential microbial abundance, diversity, and metabolic pathways were identified using linear discriminant analysis (LDA) effect size analyses. Additionally, we compared these profiles with our previously published microbiome data derived from Kenyan CRC patients. Results: Differential microbiome analysis of CRCs across all racial/ethnic groups showed dysbiosis. There were high abundances of Herbaspirillum and Staphylococcus in CRCs of Egyptians, Leptotrichia in CRCs of AAs, Flexspiria and Streptococcus in CRCs of EAs, and Akkermansia muciniphila and Prevotella nigrescens in CRCs of Kenyans (LDA score >4, adj. p-value <0.05). Functional analyses showed distinct microbial metabolic pathways in CRCs compared to normal tissues within the racial/ethnic groups. Egyptian CRCs, compared to normal tissues, showed lower l-methionine biosynthesis and higher galactose degradation pathways. Conclusions: Our findings showed altered mucosa-associated microbiome profiles of CRCs and their metabolic pathways across racial/ethnic groups. These findings provide a basis for future studies to link racial/ethnic microbiome differences with distinct clinical behaviors in CRC.

Transcriptome profile changes in the jejunum of nonhuman primates exposed to supralethal dose of total- or partial-body radiation.

The risk of exposure of the general public or military personnel to high levels of ionizing radiation from nuclear weapons or radiological accidents is a dire national security matter. The development of advanced molecular biodosimetry methods, those that measure biological response, such as transcriptomics, to screen large populations of radiation-exposed victims is key to improving survival outcomes during radiological mass casualty scenarios. In this study, nonhuman primates were exposed to either 12.0 Gy cobalt-60 gamma (total-body irradiation, TBI) or X-ray (partial-body irradiation, PBI) 24 h after administration of a potential radiation medical countermeasure, gamma-tocotrienol (GT3). Changes in the jejunal transcriptomic profiles in GT3-treated and irradiated animals were compared to healthy controls to assess the extent of radiation damage. No major effect of GT3 on radiation-induced transcriptome at this radiation dose was identified. About 80% of the pathways with a known activation or repression state were commonly observed between both exposures. Several common pathways activated due to irradiation include FAK signaling, CREB signaling in the neurons, phagosome formation, and G-protein coupled signaling pathway. Sex-specific differences associated with excessive mortality among irradiated females were identified in this study, including Estrogen receptor signaling. Differential pathway activation was also identified across PBI and TBI, pointing towards altered molecular response for different degrees of bone marrow sparing and radiation doses. This study provides insight into radiation-induced changes in jejunal transcriptional profiles, supporting the investigation for the identification of biomarkers for radiation injury and countermeasure efficacy.

A signature of Prevotella copri and Faecalibacterium prausnitzii depletion, and a link with bacterial glutamate degradation in the Kenyan colorectal cancer patients.

Background: Colorectal cancer (CRC) is the fifth most diagnosed cancer in Sub-Saharan Africa. In Kenya, CRC incidence rates tripled from 1997 to 2017. In the Moi Teaching and Referral Hospital, Moi University, there has been an increase in CRC cases, notably for younger patients. A suggested pathobiology for this increase is gut microbiome dysbiosis. Since, for the Kenyan CRC patient population, microbiome studies are rare, there is a need for a better understanding of how microbiome dysbiosis influences CRC epidemiology in Kenya. In this single-center study, the focus was on profiling the gut microbiome of Kenyan CRC patients and healthy volunteers and evaluating associations between microbiome profiles and the age of CRC patients. Methods: The gut mucosa-associated microbiome of 18 CRC patients and 18 healthy controls were determined by 16S rRNA sequencing and analyzed for alpha and beta diversity, differential abundance, and microbial metabolic profiling. Results: Alpha diversity metrics showed no significant differences, but beta diversity metrics showed dissimilarities in the microbial communities between CRC patients and healthy controls. The most underrepresented species in the CRC group were Prevotella copri (P. copri) and Faecalibacterium prausnitzii (F. prausnitzii), although Bacteroides fragilis (B. fragilis) and Prevotella nigrescens were overrepresented (linear discriminant analysis, LDA score >2, P<0.05). Also, for CRC patients, significant metagenomic functional alterations were evident in microbial glutamate metabolic pathways (L-glutamate degradation VIII was enriched, and L-glutamate and L-glutamine biosynthesis were diminished) (P<0.05, log2 Fold Change >1). Moreover, the microbiome composition was different for patients under 40 years of age compared to older patients (LDA score >2, P<0.05). Conclusions: Microbiome and microbial metabolic profiles of CRC patients are different from those of healthy individuals. CRC microbiome dysbiosis, particularly P. copri and F. prausnitzii depletion and glutamate metabolic alterations, are evident in Kenyan CRC patients.

Meta-Analysis of Altered Gut Microbiota Reveals Microbial and Metabolic Biomarkers for Colorectal Cancer.

Colorectal cancer (CRC) is the second leading cause of cancer mortality worldwide. The dysbiotic gut microbiota and its metabolite secretions play a significant role in CRC development and progression. In this study, we identified microbial and metabolic biomarkers applicable to CRC using a meta-analysis of metagenomic datasets from diverse geographical regions. We used LEfSe, random forest (RF), and co-occurrence network methods to identify microbial biomarkers. Geographic dataset-specific markers were identified and evaluated using area under the ROC curve (AUC) scores and random effect size. Co-occurrence networks analysis showed a reduction in the overall microbial associations and the presence of oral pathogenic microbial clusters in CRC networks. Analysis of predicted metabolites from CRC datasets showed the enrichment of amino acids, cadaverine, and creatine in CRC, which were positively correlated with CRC-associated microbes (Peptostreptococcus stomatis, Gemella morbillorum, Bacteroides fragilis, Parvimonas spp., Fusobacterium nucleatum, Solobacterium moorei, and Clostridium symbiosum), and negatively correlated with control-associated microbes. Conversely, butyrate, nicotinamide, choline, tryptophan, and 2-hydroxybutanoic acid showed positive correlations with control-associated microbes (P < 0.05). Overall, our study identified a set of global CRC biomarkers that are reproducible across geographic regions. We also reported significant differential metabolites and microbe-metabolite interactions associated with CRC. This study provided significant insights for further investigations leading to the development of noninvasive CRC diagnostic tools and therapeutic interventions. IMPORTANCE Several studies showed associations between gut dysbiosis and CRC. Yet, the results are not conclusive due to cohort-specific associations that are influenced by genomic, dietary, and environmental stimuli and associated reproducibility issues with various analysis approaches. Emerging evidence suggests the role of microbial metabolites in modulating host inflammation and DNA damage in CRC. However, the experimental validations have been hindered by cost, resources, and cumbersome technical expertise required for metabolomic investigations. In this study, we performed a meta-analysis of CRC microbiota data from diverse geographical regions using multiple methods to achieve reproducible results. We used a computational approach to predict the metabolomic profiles using existing CRC metagenomic datasets. We identified a reliable set of CRC-specific biomarkers from this analysis, including microbial and metabolite markers. In addition, we revealed significant microbe-metabolite associations through correlation analysis and microbial gene families associated with dysregulated metabolic pathways in CRC, which are essential in understanding the vastly sporadic nature of CRC development and progression.

Effect of Nora virus infection on native gut bacterial communities of Drosophila melanogaster.

Gastrointestinal microflora is a key component in the maintenance of health and longevity across many species. In humans and mice, nonpathogenic viruses present in the gastrointestinal tract enhance the effects of the native bacterial microbiota. However, it is unclear whether nonpathogenic gastrointestinal viruses, such as Nora virus that infects Drosophila melanogaster, lead to similar observations. Longevity analysis of Nora virus infected (NV+) and uninfected (NV-) D. melanogaster in relationship to presence (B+) or absence (B-) of the native gut bacteria using four different treatment groups, NV+/B+, NV+/B-, NV-/B+, and NV-/B-, was conducted. Data from the longevity results were tested via Kaplan-Meier analysis and demonstrated that Nora virus can be detrimental to the longevity of the organism, whereas bacterial presence is beneficial. These data led to the hypothesis that gastrointestinal bacterial composition varies from NV+ to NV- flies. To test this, NV+ and NV- virgin female flies were collected and aged for 4 days. Surface sterilization followed by dissections of the fat body and the gastrointestinal tract, divided into crop (foregut), midgut, and hindgut, were performed. Ribosomal 16S DNA samples were sequenced to determine the bacterial communities that comprise the microflora in the gastrointestinal tract of NV+ and NV- D. melanogaster. When analyzing operational taxonomic units (OTUs), the data demonstrate that the NV+ samples consist of more OTUs than NV- samples. The NV+ samples were both more rich and diverse in OTUs compared to NV-. When comparing whole body samples to specific organs and organ sections, the whole fly was more diverse in OTUs, whereas the crop was the most rich. These novel data are pertinent in describing where Nora virus infection may be occurring within the gastrointestinal tract, as well as continuing discussion between the relationship of persistent viral and bacterial interaction.

Gut Microbiota and Metabolic Specificity in Ulcerative Colitis and Crohn's Disease.

Background: Inflammatory bowel disease (IBD) represents multifactorial chronic inflammatory conditions in the gastrointestinal tract and includes Crohn's disease (CD) and ulcerative colitis (UC). Despite similarities in pathobiology and disease symptoms, UC and CD represent distinct diseases and exhibit diverse therapeutic responses. While studies have now confirmed that IBD is associated with dramatic changes in the gut microbiota, specific changes in the gut microbiome and associated metabolic effects on the host due to CD and UC are less well-understood. Methods: To address this knowledge gap, we performed an extensive unbiased meta-analysis of the gut microbiome data from five different IBD patient cohorts from five different countries using QIIME2, DIAMOND, and STAMP bioinformatics platforms. In-silico profiling of the metabolic pathways and community metabolic modeling were carried out to identify disease-specific association of the metabolic fluxes and signaling pathways. Results: Our results demonstrated a highly conserved gut microbiota community between healthy individuals and IBD patients at higher phylogenetic levels. However, at or below the order level in the taxonomic rank, we found significant disease-specific alterations. Similarly, we identified differential enrichment of the metabolic pathways in CD and UC, which included enriched pathways related to amino acid and glycan biosynthesis and metabolism, in addition to other metabolic pathways. Conclusions: In conclusion, this study highlights the prospects of harnessing the gut microbiota to improve understanding of the etiology of CD and UC and to develop novel prognostic, and therapeutic approaches.

Role of Small Intestine and Gut Microbiome in Plant-Based Oral Tolerance for Hemophilia.

Fusion proteins, which consist of factor VIII or factor IX and the transmucosal carrier cholera toxin subunit B, expressed in chloroplasts and bioencapsulated within plant cells, initiate tolerogenic immune responses in the intestine when administered orally. This approach induces regulatory T cells (Treg), which suppress inhibitory antibody formation directed at hemophilia proteins induced by intravenous replacement therapy in hemophilia A and B mice. Further analyses of Treg CD4+ lymphocyte sub-populations in hemophilia B mice reveal a marked increase in the frequency of CD4+CD25-FoxP3-LAP+ T cells (but not of CD4+CD25+FoxP3+ T cells) in the lamina propria of the small but not large intestine. The adoptive transfer of very small numbers of CD4+CD25-LAP+ Treg isolated from the spleen of tolerized mice was superior in suppression of antibodies directed against FIX when compared to CD4+CD25+ T cells. Thus, tolerance induction by oral delivery of antigens bioencapsulated in plant cells occurs via the unique immune system of the small intestine, and suppression of antibody formation is primarily carried out by induced latency-associated peptide (LAP) expressing Treg that likely migrate to the spleen. Tolerogenic antigen presentation in the small intestine requires partial enzymatic degradation of plant cell wall by commensal bacteria in order to release the antigen. Microbiome analysis of hemophilia B mice showed marked differences between small and large intestine. Remarkably, bacterial species known to produce a broad spectrum of enzymes involved in degradation of plant cell wall components were found in the small intestine, in particular in the duodenum. These were highly distinct from populations of cell wall degrading bacteria found in the large intestine. Therefore, FIX antigen presentation and Treg induction by the immune system of the small intestine relies on activity of a distinct microbiome that can potentially be augmented to further enhance this approach.