Chordicoccus furentiruminis, gen. nov., sp. nov., a novel succinic acid producing bacterium isolated from a steer on a high grain diet.

This study presents MP1D12T (=NRRL B-67553T=NCTC 14480T), an isolate from the ruminal content of an Angus steer fed a high grain diet. Phenotypic and genotypic traits of the isolate were explored. MP1D12T was found to be a strictly anaerobic, catalase-negative, oxidase-negative, coccoid bacterium that frequently grows in chains. Analysis of metabolic products as a result of carbohydrate fermentation showed succinic acid as the major organic acid produced with lactic acid and acetic acid as minor products. Phylogenetic analysis of MP1D12T based on 16S rRNA nucleotide sequence and amino acid sequences from the whole genome presents a divergent lineage from other members in the family Lachnospiraceae. 16S rRNA sequence comparison, whole genome average nucleotide identity digital DNA-DNA hybridization and average amino acid identity results suggest that MP1D12T represents a novel species in a novel genus within the family Lachnospiraceae. We propose the creation of the genus Chordicoccus in which MP1D12T represents the type strain for the novel species Chordicoccus furentiruminis.

Effect of supplementation with ruminal probiotics on growth performance, carcass characteristics, plasma metabolites, methane emissions, and the associated rumen microbiome changes in beef cattle.

To evaluate the effect of supplementing beef cattle with a ruminal probiotic consisting of native rumen microbes (NRM; Chordicoccus furentiruminis, Prevotella albensis, and Succinivibrio dextrinosolvens) on methane (CH4) emissions, growth performance, carcass characteristics, and plasma metabolites, Angus × SimAngus-crossbred steers (n = 32; 8 per pen) and heifers (n = 48; 12 per pen) with an initial body weight (BW) of 353 ± 64 kg were used in randomized complete block design. Cattle were blocked by sex and BW and randomly assigned to 1 of 2 treatments (2 pens per treatment). Treatments consisted of diets offered for ad libitum intake with (NRM) or without (CON) the inclusion of the ruminal probiotic. Cattle were fed a growing diet for 49 d followed by a ground corn-based diet for 124 ± 27 d until reaching the targeted final BW (635 kg for steers and 590 kg for heifers). Methane emissions were estimated using the GreenFeed system (n = 12 per treatment) prior to trial commencement (baseline; period 1), and on three (2, 3, and 4), and two (5 and 6) different sampling periods throughout the growing and finishing stage, respectively. All data were analyzed using the PROC MIXED procedure of SAS. For CH4 production (g/d), there was a tendency for an NRM supplementation × period interaction (P = 0.07) where cattle-fed diets with NRM had lower production of methane in periods 3 and 4. Including NRM in the diet decreased CH4 yield (g/kg of dry matter intake (DMI)) by 20%. For CH4 emission intensity (g/kg of average daily gain (ADG)), an interaction (P < 0.01) of NRM supplementation × period occurred. In periods 2 and 3, cattle-fed diets with NRM inclusion had lower CH4 emission intensity than CON cattle. During the 84-d period when all cattle were still on the finishing diet, feeding NRM increased (P = 0.02) ADG and tended to increase (P = 0.10) DMI. At the end of the 84-d period, cattle-fed NRM tended to be heavier (P = 0.06) than CON cattle. Cattle supplemented with NRM required less (P = 0.04) days on feed to reach the targeted final BW. No differences (P ≤ 0.11) were detected for gain-to-feed ratio and carcass characteristics. Cattle-fed NRM had greater abundance of uncultured rumen bacteria that may improve rumen digestion when fed a high grain diet and potentially promote the reduction of enteric CH4 production. Results from this study suggest that daily administration of NRM may be a strategy to mitigate methanogenesis and improve the growth performance of beef cattle.

Greenhouse gas emissions are a major concern in the beef industry. This study examined the effects of supplementation with ruminal probiotics consisting of three native ruminal microbes (NRM) for their influence on methane reduction and growth performance of beef cattle. Eighty Angus × SimAngus-crossbred cattle were grouped by sex and weight, randomly assigned to a treatment group, control or NRM supplementation, and subsequently fed commercially relevant diets for at least 134 d with or without NRM supplementation until they reached a target finishing weight. Methane emissions and growth performance metrics were recorded at regular intervals. Cattle-fed diets with NRM had a greater average daily gain during most part of the experimental period, required fewer days to reach the finishing weight, and emitted less methane than cattle in the control treatment. Supplementing NRM can be a viable method to reduce greenhouse gas emissions while improving the performance of beef cattle-fed concentrates-based diets.

Effects of rumen-native microbial feed supplementation on milk yield, composition, and feed efficiency in lactating dairy cows.

The objective of this study was to evaluate the effects of two rumen-native microbial feed supplements (MFS) on milk production, milk composition, and feed efficiency. A total of 90 multiparous cows between 40 and 60 d in milk were enrolled in a randomized block design study. Within each block (baseline milk yield), cows were randomly assigned to: control (no microbial feed supplementation), MFS1 (0.33 g/kg total mixed ration [TMR] of an MFS containing a minimum of Clostridium beijerinckii at 2 × 106 CFU/g and Pichia kudriavzevii at 2 × 107 CFU/g), or MFS2 (0.33 g/kg TMR of a MFS containing a minimum of C. beijerinckii at 2 × 106 CFU/g, P. kudriavzevii at 2 × 107 CFU/g, Ruminococcus bovis at 2 × 107 CFU/g, and Butyrivibrio fibrisolvens at 2 × 107 CFU/g). Cows were housed in a single group and fed the study diets ad libitum for 270 d. Individual milk yield was recorded using electronic milk meters, and milk fat and protein were measured using optical in-line analyzers at each of two daily milkings. Treatment and treatment by time effects were assessed through multiple linear regression analyses. Treatment effects were observed for milk and energy-corrected milk (ECM) yields, milk fat and protein yields and concentrations, dry matter intake (DMI), and feed efficiency; those effects were conditional to time for milk yield, DMI, and feed efficiency. Overall, milk, ECM, fat, and protein yields were higher for MFS2 compared with control cows (+3.0, 3.7, 0.12, and 0.12 kg/d, respectively). Compared with MFS1, milk yield was higher and protein yield tended to be higher for MFS2 cows (+2.9 and 0.09 kg/d, respectively). In contrast, MFS1 cows produced 0.17 and 0.08 units of percentage per day more fat and protein than MFS2 cows, and 0.07 units of percentage per day more protein than control cows. Dry matter intake and feed efficiency were higher for MFS2 cows compared with MFS1 cows (+1.3 kg/d and 0.06, respectively), and feed efficiency was higher for MFS2 cows compared with control cows (+0.04). Where observed, treatment by time effects suggest that the effects of MFS2 were more evident as time progressed after supplementation was initiated. No effects of microbial supplementation were observed on body weight, body condition score, somatic cell count, or clinical mastitis case incidence. In conclusion, the supplementation of MFS2 effectively improved economically important outcomes such as milk yield, solids, and feed efficiency.

This study evaluates the effects of two rumen-native microbial feed supplements (MFS) on milk yield, composition, and feed efficiency in lactating dairy cows. Ninety multiparous Holstein cows between 40 and 60 d in milk were assigned to control (no microbial feed supplementation), MFS1 (Clostridium beijerinckii and Pichia kudriavzevii), or MFS2 (C. beijerinckii, P. kudriavzevii, Ruminococcus bovis, and Butyrivibrio fibrisolvens) total mixed ration supplementation. Overall, MFS2 cows had higher milk and milk component yields than control and MFS1, while MFS1 cows had higher milk component concentrations than control and MFS2. Feed efficiency was higher for MFS2 compared with control and MFS1 cows. Microbial feed supplementation improved economically important outcomes such as milk yield, solids, and feed efficiency.

Ruminococcus bovis sp. nov., a novel species of amylolytic Ruminococcus isolated from the rumen of a dairy cow.

This study describes JE7A12T (=ATCC TSD-225T=NCTC 14479T), an isolate from the ruminal content of a dairy cow. Phenotypic and genotypic traits of the isolate were explored. JE7A12T was found to be a strictly anaerobic, catalase-negative, oxidase-negative, coccoid bacterium that grows in chains. The API 50 CH carbon source assay detected fermentation of d-glucose, d-fructose, d-galactose, glycogen and starch. HPLC showed acetate to be the major fermentation product as a result of carbohydrate fermentation. Phylogenetic analysis of JE7A12T based on 16S rRNA nucleotide sequence and amino acid sequences from the whole genome indicated a divergent lineage from the closest neighbours in the genus Ruminococcus. The results of 16S rRNA sequence comparison, whole genome average nucleotide identity (ANI) and DNA G+C content data indicate that JE7A12T represents a novel species which we propose the name Ruminococcus bovis with JE7A12T as the type strain.

Simultaneous compression and opacity data from time-series radiography with a Lagrangian marker.

Time-resolved radiography can be used to obtain absolute shock Hugoniot states by simultaneously measuring at least two mechanical parameters of the shock, and this technique is particularly suitable for one-dimensional converging shocks where a single experiment probes a range of pressures as the converging shock strengthens. However, at sufficiently high pressures, the shocked material becomes hot enough that the x-ray opacity falls significantly. If the system includes a Lagrangian marker such that the mass within the marker is known, this additional information can be used to constrain the opacity as well as the Hugoniot state. In the limit that the opacity changes only on shock heating, and not significantly on subsequent isentropic compression, the opacity of the shocked material can be determined uniquely. More generally, it is necessary to assume the form of the variation of opacity with isentropic compression or to introduce multiple marker layers. Alternatively, assuming either the equation of state or the opacity, the presence of a marker layer in such experiments enables the non-assumed property to be deduced more accurately than from the radiographic density reconstruction alone. An example analysis is shown for measurements of a converging shock wave in polystyrene at the National Ignition Facility.

Benchmarking boron carbide equation of state using computation and experiment.

Boron carbide (B_{4}C) is of both fundamental scientific and practical interest due to its structural complexity and how it changes upon compression, as well as its many industrial uses and potential for use in inertial confinement fusion (ICF) and high-energy density physics experiments. We report the results of a comprehensive computational study of the equation of state (EOS) of B_{4}C in the liquid, warm dense matter, and plasma phases. Our calculations are cross-validated by comparisons with Hugoniot measurements up to 61 megabar from planar shock experiments performed at the National Ignition Facility (NIF). Our computational methods include path integral Monte Carlo, activity expansion, as well as all-electron Green's function Korringa-Kohn-Rostoker and molecular dynamics that are both based on density functional theory. We calculate the pressure-internal energy EOS of B_{4}C over a broad range of temperatures (∼6×10^{3}-5×10^{8} K) and densities (0.025-50 g/cm^{3}). We assess that the largest discrepancies between theoretical predictions are ≲5% near the compression maximum at 1-2×10^{6} K. This is the warm-dense state in which the K shell significantly ionizes and has posed grand challenges to theory and experiment. By comparing with different EOS models, we find a Purgatorio model (LEOS 2122) that agrees with our calculations. The maximum discrepancies in pressure between our first-principles predictions and LEOS 2122 are ∼18% and occur at temperatures between 6×10^{3}-2×10^{5} K, which we believe originate from differences in the ion thermal term and the cold curve that are modeled in LEOS 2122 in comparison with our first-principles calculations. To account for potential differences in the ion thermal term, we have developed three new equation-of-state models that are consistent with theoretical calculations and experiment. We apply these new models to 1D hydrodynamic simulations of a polar direct-drive NIF implosion, demonstrating that these new models are now available for future ICF design studies.

Rumen Bacteria and Serum Metabolites Predictive of Feed Efficiency Phenotypes in Beef Cattle.

The rumen microbiome is critical to nutrient utilization and feed efficiency in cattle. Consequently, the objective of this study was to identify microbial and biochemical factors in Angus steers affecting divergences in feed efficiency using 16S amplicon sequencing and untargeted metabolomics. Based on calculated average residual feed intake (RFI), steers were divided into high- and low-RFI groups. Features were ranked in relation to RFI through supervised machine learning on microbial and metabolite compositions. Residual feed intake was associated with several features of the bacterial community in the rumen. Decreased bacterial α- (P = 0.03) and ß- diversity (P < 0.001) was associated with Low-RFI steers. RFI was associated with several serum metabolites. Low-RFI steers had greater abundances of pantothenate (P = 0.02) based on fold change (high/low RFI). Machine learning on RFI was predictive of both rumen bacterial composition and serum metabolomic signature (AUC ≥ 0.7). Log-ratio proportions of the bacterial classes Flavobacteriia over Fusobacteriia were enriched in low-RFI steers (F = 6.8, P = 0.01). Reductions in Fusobacteriia and/or greater proportions of pantothenate-producing bacteria, such as Flavobacteriia, may result in improved nutrient utilization in low-RFI steers. Flavobacteriia and Pantothenate may potentially serve as novel biomarkers to predict or evaluate feed efficiency in Angus steers.

Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads.

As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing.

Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease.

Although genetic approaches are the standard in microbiome analysis, proteome-level information is largely absent. This discrepancy warrants a better understanding of the relationship between gene copy number and protein abundance, as this is crucial information for inferring protein-level changes from metagenomic data. As it remains unknown how metaproteomic systems evolve during dynamic disease states, we leveraged a 4.5-year fecal time series using samples from a single patient with colonic Crohn's disease. Utilizing multiplexed quantitative proteomics and shotgun metagenomic sequencing of eight time points in technical triplicate, we quantified over 29,000 protein groups and 110,000 genes and compared them to five protein biomarkers of disease activity. Broad-scale observations were consistent between data types, including overall clustering by principal-coordinate analysis and fluctuations in Gene Ontology terms related to Crohn's disease. Through linear regression, we determined genes and proteins fluctuating in conjunction with inflammatory metrics. We discovered conserved taxonomic differences relevant to Crohn's disease, including a negative association of Faecalibacterium and a positive association of Escherichia with calprotectin. Despite concordant associations of genera, the specific genes correlated with these metrics were drastically different between metagenomic and metaproteomic data sets. This resulted in the generation of unique functional interpretations dependent on the data type, with metaproteome evidence for previously investigated mechanisms of dysbiosis. An example of one such mechanism was a connection between urease enzymes, amino acid metabolism, and the local inflammation state within the patient. This proof-of-concept approach prompts further investigation of the metaproteome and its relationship with the metagenome in biologically complex systems such as the microbiome. IMPORTANCE A majority of current microbiome research relies heavily on DNA analysis. However, as the field moves toward understanding the microbial functions related to healthy and disease states, it is critical to evaluate how changes in DNA relate to changes in proteins, which are functional units of the genome. This study tracked the abundance of genes and proteins as they fluctuated during various inflammatory states in a 4.5-year study of a patient with colonic Crohn's disease. Our results indicate that despite a low level of correlation, taxonomic associations were consistent in the two data types. While there was overlap of the data types, several associations were uniquely discovered by analyzing the metaproteome component. This case study provides unique and important insights into the fundamental relationship between the genes and proteins of a single individual's fecal microbiome associated with clinical consequences.

Evolutionary trends in host physiology outweigh dietary niche in structuring primate gut microbiomes.

Over the past decade several studies have reported that the gut microbiomes of mammals with similar dietary niches exhibit similar compositional and functional traits. However, these studies rely heavily on samples from captive individuals and often confound host phylogeny, gut morphology, and diet. To more explicitly test the influence of host dietary niche on the mammalian gut microbiome we use 16S rRNA gene amplicon sequencing and shotgun metagenomics to compare the gut microbiota of 18 species of wild non-human primates classified as either folivores or closely related non-folivores, evenly distributed throughout the primate order and representing a range of gut morphological specializations. While folivory results in some convergent microbial traits, collectively we show that the influence of host phylogeny on both gut microbial composition and function is much stronger than that of host dietary niche. This pattern does not result from differences in host geographic location or actual dietary intake at the time of sampling, but instead appears to result from differences in host physiology. These findings indicate that mammalian gut microbiome plasticity in response to dietary shifts over both the lifespan of an individual host and the evolutionary history of a given host species is constrained by host physiological evolution. Therefore, the gut microbiome cannot be considered separately from host physiology when describing host nutritional strategies and the emergence of host dietary niches.

A theoretical model of fuselage pressure levels due to fan tones radiated from the intake of an installed turbofan aero-engine.

An existing theoretical model to predict the pressure levels on an aircraft's fuselage is improved by incorporating a more physically realistic method to predict fan tone radiation from the intake of an installed turbofan aero-engine. Such a model can be used as part of a method to assess cabin noise. Fan tone radiation from a turbofan intake is modelled using the exact solution for the radiated pressure from a spinning mode exiting a semi-infinite cylindrical duct immersed in a uniform flow. This approach for a spinning duct mode incorporates scattering/diffraction by the intake lip, enabling predictions of the radiated pressure valid in both the forward and aft directions. The aircraft's fuselage is represented by an infinitely long, rigid cylinder. There is uniform flow aligned with the cylinder, except close to the cylinder's surface where there is a constant-thickness boundary layer. In addition to single mode calculations it is shown how the model may be used to rapidly calculate a multi-mode incoherent radiation from the engine intake. Illustrative results are presented which demonstrate the relative importance of boundary-layer shielding both upstream and downstream of the source, as well as examples of the fuselage pressure levels due to a multi-mode tonal source at high Helmholtz number.

Trans-Cinnamaldehyde and Eugenol Increase Acinetobacter baumannii Sensitivity to Beta-Lactam Antibiotics.

Multi-drug resistant (MDR) Acinetobacter baumannii is a major nosocomial pathogen causing a wide range of clinical conditions with significant mortality rates. A. baumannii strains are equipped with a multitude of antibiotic resistance mechanisms, rendering them resistant to most of the currently available antibiotics. Thus, there is a critical need to explore novel strategies for controlling antibiotic resistance in A. baumannii. This study investigated the efficacy of two food-grade, plant-derived antimicrobials (PDAs), namely trans-cinnamaldehyde (TC) and eugenol (EG) in decreasing A. baumannii's resistance to seven ß-lactam antibiotics, including ampicillin, methicillin, meropenem, penicillin, aztreonam, amoxicillin, and piperacillin. Two MDR A. baumannii isolates (ATCC 17978 and AB 251847) were separately cultured in tryptic soy broth (∼6 log CFU/ml) containing the minimum inhibitory concentration (MIC) of TC or EG with or without the MIC of each antibiotic at 37°C for 18 h. A. baumannii strains not exposed to the PDAs or antibiotics served as controls. Following incubation, A. baumannii counts were determined by broth dilution assay. In addition, the effect of PDAs on the permeability of outer membrane and efflux pumps in A. baumannii was measured. Further, the effect of TC and EG on the expression of A. baumannii genes encoding resistance to ß-lactam antibiotics (blaP), efflux pumps (adeABC), and multi-drug resistant protein (mdrp) was studied using real-time quantitative PCR (RT-qPCR). The experiment was replicated three times with duplicate samples of each treatment and control. The results from broth dilution assay indicated that both TC and EG in combination with antibiotics increased the sensitivity of A. baumannii to all the tested antibiotics (P < 0.05). The two PDAs inhibited the function of A. baumannii efflux pump, (AdeABC), but did not increase the permeability of its outer membrane. Moreover, RT-qPCR data revealed that TC and EG down-regulated the expression of majority of the genes associated with ß-lactam antibiotic resistance, especially blaP and adeABC (P < 0.05). The results suggest that TC and EG could potentially be used along with ß-lactam antibiotics for controlling MDR A. baumannii infections; however, their clinical significance needs to be determined using in vivo studies.

American Gut: an Open Platform for Citizen Science Microbiome Research.

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.

DNA extraction for streamlined metagenomics of diverse environmental samples.

A major bottleneck for metagenomic sequencing is rapid and efficient DNA extraction. Here, we compare the extraction efficiencies of three magnetic bead-based platforms (KingFisher, epMotion, and Tecan) to a standardized column-based extraction platform across a variety of sample types, including feces, oral, skin, soil, and water. Replicate sample plates were extracted and prepared for 16S rRNA gene amplicon sequencing in parallel to assess extraction bias and DNA quality. The data demonstrate that any effect of extraction method on sequencing results was small compared with the variability across samples; however, the KingFisher platform produced the largest number of high-quality reads in the shortest amount of time. Based on these results, we have identified an extraction pipeline that dramatically reduces sample processing time without sacrificing bacterial taxonomic or abundance information.

Fuselage boundary-layer refraction of fan tones radiated from an installed turbofan aero-engine.

A distributed source model to predict fan tone noise levels of an installed turbofan aero-engine is extended to include the refraction effects caused by the fuselage boundary layer. The model is a simple representation of an installed turbofan, where fan tones are represented in terms of spinning modes radiated from a semi-infinite circular duct, and the aircraft's fuselage is represented by an infinitely long, rigid cylinder. The distributed source is a disk, formed by integrating infinitesimal volume sources located on the intake duct termination. The cylinder is located adjacent to the disk. There is uniform axial flow, aligned with the axis of the cylinder, everywhere except close to the cylinder where there is a constant thickness boundary layer. The aim is to predict the near-field acoustic pressure, and in particular, to predict the pressure on the cylindrical fuselage which is relevant to assess cabin noise. Thus no far-field approximations are included in the modelling. The effect of the boundary layer is quantified by calculating the area-averaged mean square pressure over the cylinder's surface with and without the boundary layer included in the prediction model. The sound propagation through the boundary layer is calculated by solving the Pridmore-Brown equation. Results from the theoretical method show that the boundary layer has a significant effect on the predicted sound pressure levels on the cylindrical fuselage, owing to sound radiation of fan tones from an installed turbofan aero-engine.

From Sample to Multi-Omics Conclusions in under 48 Hours.

Multi-omics methods have greatly advanced our understanding of the biological organism and its microbial associates. However, they are not routinely used in clinical or industrial applications, due to the length of time required to generate and analyze omics data. Here, we applied a novel integrated omics pipeline for the analysis of human and environmental samples in under 48 h. Human subjects that ferment their own foods provided swab samples from skin, feces, oral cavity, fermented foods, and household surfaces to assess the impact of home food fermentation on their microbial and chemical ecology. These samples were analyzed with 16S rRNA gene sequencing, inferred gene function profiles, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics through the Qiita, PICRUSt, and GNPS pipelines, respectively. The human sample microbiomes clustered with the corresponding sample types in the American Gut Project (http://www.americangut.org), and the fermented food samples produced a separate cluster. The microbial communities of the household surfaces were primarily sourced from the fermented foods, and their consumption was associated with increased gut microbial diversity. Untargeted metabolomics revealed that human skin and fermented food samples had separate chemical ecologies and that stool was more similar to fermented foods than to other sample types. Metabolites from the fermented foods, including plant products such as procyanidin and pheophytin, were present in the skin and stool samples of the individuals consuming the foods. Some food metabolites were modified during digestion, and others were detected in stool intact. This study represents a first-of-its-kind analysis of multi-omics data that achieved time intervals matching those of classic microbiological culturing. IMPORTANCE Polymicrobial infections are difficult to diagnose due to the challenge in comprehensively cultivating the microbes present. Omics methods, such as 16S rRNA sequencing, metagenomics, and metabolomics, can provide a more complete picture of a microbial community and its metabolite production, without the biases and selectivity of microbial culture. However, these advanced methods have not been applied to clinical or industrial microbiology or other areas where complex microbial dysbioses require immediate intervention. The reason for this is the length of time required to generate and analyze omics data. Here, we describe the development and application of a pipeline for multi-omics data analysis in time frames matching those of the culture-based approaches often used for these applications. This study applied multi-omics methods effectively in clinically relevant time frames and sets a precedent toward their implementation in clinical medicine and industrial microbiology.

Phylogenetic and ecological factors impact the gut microbiota of two Neotropical primate species.

Recent studies suggest that variation in diet across time and space results in changes in the mammalian gut microbiota. This variation may ultimately impact host ecology by altering nutritional status and health. Wild animal populations provide an excellent opportunity for understanding these interactions. However, compared to clinical studies, microbial research targeting wild animals is currently limited, and many published studies focus only on a single population of a single host species. In this study we utilize fecal samples from two species of howler monkey (Alouatta pigra and A. palliata) collected at four sites to investigate factors influencing the gut microbiota at three scales: taxonomic (host species), ecosystemic (forest type), and local (habitat disturbance/season). The results demonstrate that the effect of host species on the gut microbiota is stronger than the effect of host forest type, which is stronger than the effect of habitat disturbance or seasonality. Nevertheless, within host species, gut microbiota composition differs in response to forest type, habitat disturbance, and season. Variations in the effect size of these factors are associated both with host species and environment. This information may be beneficial for understanding ecological and evolutionary questions associated with Mesoamerican howler monkeys, as well as determining conservation challenges facing each species. These mechanisms may also provide insight into the ecology of other species of howler monkeys, non-human primates, and mammals.

Near-field sound radiation of fan tones from an installed turbofan aero-engine.

The development of a distributed source model to predict fan tone noise levels of an installed turbofan aero-engine is reported. The key objective is to examine a canonical problem: how to predict the pressure field due to a distributed source located near an infinite, rigid cylinder. This canonical problem is a simple representation of an installed turbofan, where the distributed source is based on the pressure pattern generated by a spinning duct mode, and the rigid cylinder represents an aircraft fuselage. The radiation of fan tones can be modelled in terms of spinning modes. In this analysis, based on duct modes, theoretical expressions for the near-field acoustic pressures on the cylinder, or at the same locations without the cylinder, have been formulated. Simulations of the near-field acoustic pressures are compared against measurements obtained from a fan rig test. Also, the installation effect is quantified by calculating the difference in the sound pressure levels with and without the adjacent cylindrical fuselage. Results are shown for the blade passing frequency fan tone radiated at a supersonic fan operating condition.