The META tool optimizes metagenomic analyses across sequencing platforms and classifiers.

A major challenge in the field of metagenomics is the selection of the correct combination of sequencing platform and downstream metagenomic analysis algorithm, or "classifier". Here, we present the Metagenomic Evaluation Tool Analyzer (META), which produces simulated data and facilitates platform and algorithm selection for any given metagenomic use case. META-generated in silico read data are modular, scalable, and reflect user-defined community profiles, while the downstream analysis is done using a variety of metagenomic classifiers. Reported results include information on resource utilization, time-to-answer, and performance. Real-world data can also be analyzed using selected classifiers and results benchmarked against simulations. To test the utility of the META software, simulated data was compared to real-world viral and bacterial metagenomic samples run on four different sequencers and analyzed using 12 metagenomic classifiers. Lastly, we introduce "META Score": a unified, quantitative value which rates an analytic classifier's ability to both identify and count taxa in a representative sample.

The Fecal Metabolome Links Diet Composition, Foacidic positive ion conditions, chromatographicallyod Processing, and the Gut Microbiota to Gastrointestinal Health in a Randomized Trial of Adults Consuming a Processed Diet.

BACKGROUND: Food processing alters diet digestibility and composition, thereby influencing interactions between host biology, diet, and the gut microbiota. The fecal metabolome offers insight into those relations by providing a readout of diet-microbiota interactions impacting host health. OBJECTIVES: The aims were to determine the effects of consuming a processed diet on the fecal metabolome and to explore relations between changes in the fecal metabolome with fecal microbiota composition and gastrointestinal health markers. METHODS: This was a secondary analysis of a randomized controlled trial wherein healthy adults [94% male; 18-61 y; BMI (kg/m2): 26 ± 3] consumed their usual diet [control (CON), n = 27] or a Meal, Ready-to-EatTM (Ameriqual Packaging) military ration diet composed of processed, shelf-stable, ready-to-eat items for 21 d (MRE; n = 27). Fecal metabolite profiles, fecal microbiota composition, biomarkers of intestinal barrier function, and gastrointestinal symptoms were measured before and after the intervention. Between-group differences and associations were assessed using nonparametric t tests, partial least-squares discriminant analysis, correlation, and redundancy analysis. RESULTS: Fecal concentrations of multiple dipeptides [Mann-Whitney effect size (ES) = 0.27-0.50] and long-chain SFAs (ES = 0.35-0.58) increased, whereas plant-derived compounds (ES = 0.31-0.60) decreased in MRE versus CON (P < 0.05; q < 0.20). Changes in dipeptides correlated positively with changes in fecal concentrations of Maillard-reaction products (ρ = 0.29-0.70; P < 0.05) and inversely with changes in serum prealbumin (ρ = -0.30 to -0.48; P ≤ 0.03). Multiple bile acids, coffee and caffeine metabolites, and plant-derived compounds were associated with both fecal microbiota composition and gastrointestinal health markers, with changes in fecal microbiota composition explaining 26% of the variability within changes in gastrointestinal health-associated fecal metabolites (P = 0.001). CONCLUSIONS: Changes in the fecal metabolomes of adults consuming a Meal, Ready-to-EatTM diet implicate interactions between diet composition, diet digestibility, and the gut microbiota as contributing to variability within gastrointestinal responses to the diet. Findings underscore the need to consider both food processing and nutrient composition when investigating the impact of diet-gut microbiota interactions on health outcomes. This trial was registered at www. CLINICALTRIALS: gov as NCT02423551.

A novel canis lupus familiaris reference genome improves variant resolution for use in breed-specific GWAS.

Reference genome fidelity is critically important for genome wide association studies, yet most vary widely from the study population. A typical whole genome sequencing approach implies short-read technologies resulting in fragmented assemblies with regions of ambiguity. Further information is lost by economic necessity when genotyping populations, as lower resolution technologies such as genotyping arrays are commonly used. Here, we present a phased reference genome for Canis lupus familiaris using high molecular weight DNA-sequencing technologies. We tested wet laboratory and bioinformatic approaches to demonstrate a minimum workflow to generate the 2.4 gigabase genome for a Labrador Retriever. The de novo assembly required eight Oxford Nanopore R9.4 flowcells (∼23X depth) and running a 10X Genomics library on the equivalent of one lane of an Illumina NovaSeq S1 flowcell (∼88X depth), bringing the cost of generating a nearly complete reference genome to less than $10K (USD). Mapping of short-read data from 10 Labrador Retrievers against this reference resulted in 1% more aligned reads versus the current reference (CanFam3.1, P < 0.001), and a 15% reduction of variant calls, increasing the chance of identifying true, low-effect size variants in a genome-wide association studies. We believe that by incorporating the cost to produce a full genome assembly into any large-scale genotyping project, an investigator can improve study power, decrease costs, and optimize the overall scientific value of their study.

Complete Genome Sequence of Francisella tularensis Live Vaccine Strain NR-28537 (BEI Master Cell Bank).

The genome of Francisella tularensis live vaccine strain NR-28537 was sequenced by a hybrid approach utilizing an Oxford Nanopore Technologies R9 flow cell and an Illumina MiSeq platform. De novo assembly of the resulting long and short reads produced a single-contig whole-genome sequence.

Reference Genome for the Highly Transformable Setaria viridis ME034V.

Setaria viridis (green foxtail) is an important model system for improving cereal crops due to its diploid genome, ease of cultivation, and use of C4 photosynthesis. The S. viridis accession ME034V is exceptionally transformable, but the lack of a sequenced genome for this accession has limited its utility. We present a 397 Mb highly contiguous de novo assembly of ME034V using ultra-long nanopore sequencing technology (read N50 = 41kb). We estimate that this genome is largely complete based on our updated k-mer based genome size estimate of 401 Mb for S. viridis Genome annotation identified 37,908 protein-coding genes and >300k repetitive elements comprising 46% of the genome. We compared the ME034V assembly with two other previously sequenced Setaria genomes as well as to a diversity panel of 235 S. viridis accessions. We found the genome assemblies to be largely syntenic, but numerous unique polymorphic structural variants were discovered. Several ME034V deletions may be associated with recent retrotransposition of copia and gypsy LTR repeat families, as evidenced by their low genotype frequencies in the sampled population. Lastly, we performed a phylogenomic analysis to identify gene families that have expanded in Setaria, including those involved in specialized metabolism and plant defense response. The high continuity of the ME034V genome assembly validates the utility of ultra-long DNA sequencing to improve genetic resources for emerging model organisms. Structural variation present in Setaria illustrates the importance of obtaining the proper genome reference for genetic experiments. Thus, we anticipate that the ME034V genome will be of significant utility for the Setaria research community.

A diet of U.S. military food rations alters gut microbiota composition and does not increase intestinal permeability.

Interactions between gut microbes and dietary components modulate intestinal permeability (IP) and inflammation. Recent studies have reported altered fecal microbiota composition together with increased IP and inflammation in individuals consuming military food rations in austere environments, but could not isolate effects of the diet from environmental factors. To determine how the U.S. Meal, Ready-to-Eat food ration affects fecal microbiota composition, IP and inflammation, 60 adults (95% male,18-61 years) were randomized to consume their usual ad libitum diet for 31 days (CON) or a strictly controlled Meal, Ready-to-Eat-only diet for 21 days followed by their usual diet for 10 days (MRE). In both groups, fecal microbiota composition was measured before, during (INT, days 1-21) and after the intervention period. IP and inflammation [high-sensitivity C-reactive protein (hsCRP)] were measured on days 0, 10, 21 and 31. Longitudinal changes in fecal microbiota composition differed between groups (P=.005), and fecal samples collected from MRE during INT were identified with 88% accuracy using random forest models. The genera making the strongest contribution to that prediction accuracy included multiple lactic acid bacteria (Lactobacillus, Lactococcus, Leuconostoc), which demonstrated lower relative abundance in MRE, and several genera known to dominate the ileal microbiota (Streptococcus, Veillonella, Clostridium), the latter two demonstrating higher relative abundance in MRE. IP and hsCRP were both lower (34% and 41%, respectively) in MRE relative to CON on day 21 (P<.05) but did not differ otherwise. Findings demonstrate that a Meal, Ready-to-Eat ration diet alters fecal microbiota composition and does not increase IP or inflammation.