A study determined the effects of supplementing corn-based diets for weaned pigs with multi-enzymes on growth performance, apparent total tract digestibility (ATTD) of nutrients, fecal score, and fecal microbial composition. A total of 132 pigs (initial body weight = 7.23 kg) that had been weaned at 21 d of age and fed a drug-free nursery diet for 7 d were housed in 33 pens of 4 barrows or gilts, blocked by body weight and gender, and fed 3 experimental diets at 11 pens per diet. The diets were corn-based diet without or with multi-enzyme A or B. Multi-enzyme A supplied 4,000 U of xylanase, 150 U of β-glucanase, 3,500 U of protease, and 1,500 U of amylase per kilogram of diet. Multi-enzyme B was the same as multi-enzyme A except that it supplied amylase at 150 U/kg, and that its source of amylase was different from that of multi-enzyme A. All diets contained phytase at 1,000 U/kg. The diets were fed for 35 d in 2 phases; phase 1 for the first 14 d and phase 2 for the last 21 d of the trial. Fecal score was determined daily during the first 7 d of the trial. Fecal samples were collected from rectum of 1 pig per pen on days 2, 7, 14, and 35 of the trial for determining bacterial composition. Also, fresh fecal samples were collected from each pen on days 41 and 42 to determine ATTD of nutrients. Multi-enzyme B increased (P < 0.05) average daily gain (ADG) for phases 1 and 2. For the overall study period, multi-enzyme B increased (P < 0.05) ADG from 262 to 313 g, and average daily feed intake (ADFI) from 419 to 504 g. Multi-enzyme A increased (P < 0.05) overall ADG from 262 to 290 g, but did not affect ADFI. Multi-enzyme A or B did not affect ATTD of gross energy, but increased (P < 0.05) the ATTD of ether extract from 30% to 36% or 37%, respectively. Multi-enzyme A did not affect fecal score; however, multi-enzyme B tended to decrease (P = 0.09) fecal score, implying that it tended to decrease diarrhea. Firmicutes were the most abundant phylum of fecal bacteria (its relative abundance ranged from 58% to 72%). Bacteroidetes and Actinobacteria were the 2nd and 3rd most abundant phyla of fecal bacteria. Neither multi-enzyme affected fecal bacterial composition. In conclusion, the addition of multi-enzyme A or B to phytase-supplemented corn-based diet for weaned pigs can improve their growth performance and fat digestibility. However, multi-enzyme B was more effective than multi-enzyme A in terms of improving the growth performance of weaned pigs fed corn-based diet.

Background

Metagenomics can provide important insight into microbial communities. However, assembling metagenomic datasets has proven to be computationally challenging. Current methods often assemble only fragmented partial genes.

Results

We present a novel method for targeting assembly of specific protein-coding genes. This method combines a de Bruijn graph, as used in standard assembly approaches, and a protein profile hidden Markov model (HMM) for the gene of interest, as used in standard annotation approaches. These are used to create a novel combined weighted assembly graph. Xander performs both assembly and annotation concomitantly using information incorporated in this graph. We demonstrate the utility of this approach by assembling contigs for one phylogenetic marker gene and for two functional marker genes, first on Human Microbiome Project (HMP)-defined community Illumina data and then on 21 rhizosphere soil metagenomic datasets from three different crops totaling over 800 Gbp of unassembled data. We compared our method to a recently published bulk metagenome assembly method and a recently published gene-targeted assembler and found our method produced more, longer, and higher quality gene sequences.

Conclusion

Xander combines gene assignment with the rapid assembly of full-length or near full-length functional genes from metagenomic data without requiring bulk assembly or post-processing to find genes of interest. HMMs used for assembly can be tailored to the targeted genes, allowing flexibility to improve annotation over generic annotation pipelines. This method is implemented as open source software and is available at https://github.com/rdpstaff/Xander_assembler.

Exposure to high air temperature in late pregnancy is increasingly recognized as a risk factor for preterm birth (PTB). However, the combined effects of heatwaves with air pollution and green space are still unexplored. In the context of climate change, investigating the interaction between environmental factors and identifying communities at higher risk is important to better understand the etiological mechanisms and design targeted interventions towards certain women during pregnancy. To examine the combined effects of heatwaves, air pollution and green space exposure on the risk of PTB. California birth certificate records for singleton births (2005-2013) were obtained. Residential zip code-specific daily temperature during the last week of gestation was used to create 12 definitions of heatwave with varying temperature thresholds and durations. We fit multi-level Cox proportional hazard models with time to PTB as the outcome and gestational week as the temporal unit. Relative risk due to interaction (RERI) was applied to estimate the additive interactive effect of air pollution and green space on the effect of heatwaves on PTB. In total, 1,967,300 births were included in this study. For PM2.5, PM10 and O3, we found positive additive interactions (RERIs >0) between heatwaves and higher air pollution levels. Combined effects of heatwaves and green space indicated negative interactions (RERIs <0) for less intense heatwaves (i.e., shorter duration or relatively low temperature), whereas there were potential positive interactions (RERIs >0) for more intense heatwaves. This study found synergistic harmful effects for heatwaves with air pollution, and potential positive interactions with lack of green space on PTB. Implementing interventions, such as heat warning systems and behavioral changes, targeted toward pregnant women at risk for high air pollution and low green space exposures may optimize the benefits of reducing acute exposure to extreme heat before delivery.

Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (rplB) and two N cycle genes (nifH and nirK). We measured their computational efficiency, sensitivity, specificity, and chimera rate and found Xander and MegaGTA, which both use a probabilistic graph structure to model the genes, have the best overall performance with all three datasets, although MEGAN, a reference matching assembler, had better sensitivity with synthetic and mock community members chosen from its reference collection. Also, Xander and MegaGTA are the only tools that include post-assembly scripts tuned for common molecular ecology and diversity analyses. Additionally, we provide a mathematical model for estimating the probability of assembling targeted genes in a metagenome for estimating required sequencing depth.

Ribosomal Database Project (RDP; http://rdp.cme.msu.edu/) provides the research community with aligned and annotated rRNA gene sequence data, along with tools to allow researchers to analyze their own rRNA gene sequences in the RDP framework. RDP data and tools are utilized in fields as diverse as human health, microbial ecology, environmental microbiology, nucleic acid chemistry, taxonomy and phylogenetics. In addition to aligned and annotated collections of bacterial and archaeal small subunit rRNA genes, RDP now includes a collection of fungal large subunit rRNA genes. RDP tools, including Classifier and Aligner, have been updated to work with this new fungal collection. The use of high-throughput sequencing to characterize environmental microbial populations has exploded in the past several years, and as sequence technologies have improved, the sizes of environmental datasets have increased. With release 11, RDP is providing an expanded set of tools to facilitate analysis of high-throughput data, including both single-stranded and paired-end reads. In addition, most tools are now available as open source packages for download and local use by researchers with high-volume needs or who would like to develop custom analysis pipelines.

Background

Both extreme heat and air pollution exposure during pregnancy have been associated with preterm birth; however, their combined effects are unclear.

Objectives

Our goal was to estimate the independent and joint effects of heatwaves and fine particulate matter [PM <2.5μm in aerodynamic diameter (PM2.5)], exposure during the final gestational week on preterm birth.

Methods

Using birth registry data from Guangzhou, China, we included 215,059 singleton live births in the warm season (1 May-31 October) between January 2015 and July 2017. Daily meteorological variables from 5 monitoring stations and PM2.5 concentrations from 11 sites were used to estimate district-specific exposures. A series of cut off temperature thresholds and durations (2, 3, and 4 consecutive d) were used to define 15 different heatwaves. Cox proportional hazard models were used to estimate the effects of heatwaves and PM2.5 exposures during the final week on preterm birth, and departures from additive joint effects were assessed using the relative excess risk due to interaction (RERI).

Results

Numbers of preterm births increased in association with heatwave exposures during the final gestational week. Depending on the heatwave definition used, hazard ratios (HRs) ranged from 1.10 (95% CI: 1.01, 1.20) to 1.92 (1.39, 2.64). Associations were stronger for more intense heatwaves. Combined effects of PM2.5 exposures and heatwaves appeared to be synergistic (RERIs>0) for less extreme heatwaves (i.e., shorter or with relatively low temperature thresholds) but were less than additive (RERIs<0) for more intense heatwaves.

Conclusions

Our research strengthens the evidence that exposure to heatwaves during the final gestational week can independently trigger preterm birth. Moderate heatwaves may also act synergistically with PM2.5 exposure to increase risk of preterm birth, which adds new evidence to the current understanding of combined effects of air pollution and meteorological variables on adverse birth outcomes. https://doi.org/10.1289/EHP5117.

Adipose tissue plays a major role in maintaining organismal metabolic equilibrium. Control over the fate decision from mesenchymal stem cells (MSCs) to adipocyte differentiation involves coordinated command of phosphorylation. Protein phosphatase 2A plays an important role in Wnt pathway and adipocyte development, yet how PP2A complexes actively respond to adipocyte differentiation signals and acquire specificity in the face of the promiscuous activity of its catalytic subunit remains unknown. Here, we report the PP2A phosphatase B subunit B56α is specifically induced during adipocyte differentiation and mediates PP2A to dephosphorylate GSK3β, thereby blocking Wnt activity and driving adipocyte differentiation. Using an inducible B56α knock-out mouse, we further demonstrate that B56α is essential for gonadal adipose tissue development in vivo and required for the fate decision of adipocytes over osteoblasts. Moreover, we show B56α expression is driven by the adipocyte transcription factor PPARγ thereby establishing a novel link between PPARγ signaling and Wnt blockade. Overall, our results reveal B56α is a necessary part of the machinery dictating the transition from pre-adipocyte to mature adipocyte and provide fundamental insights into how PP2A complex specifically and actively regulates unique signaling pathway in biology.

We analyzed the microbial community that developed after 4 years of testing different soil-crop management systems in the savannah–forest transition zone of Eastern Ghana where management systems can rapidly alter stored soil carbon as well as soil fertility. The agricultural managements were: (i) the local practice of fallow regrowth of native elephant grass (Pennisetum purpureum) followed by biomass burning before planting maize in the spring, (ii) the same practice but without burning and the maize receiving mineral nitrogen fertilizer, (iii) a winter crop of a legume, pigeon pea (Cajanus cajan), followed by maize, (iv) vegetation free winter period (bare fallow) followed by maize, and (v) unmanaged elephant grass-shrub vegetation. The mean soil organic carbon (SOC) contents of the soils after 4 years were: 1.29, 1.67, 1.54, 0.80 and 1.34%, respectively, differences that should affect resources for the microbial community.From about 290,000 sequences obtained by pyrosequencing the SSU rRNA gene, canonical correspondence analysis showed that SOC was the most important factor that explained differences in microbial community structure among treatments. This analysis as well as phylogenetic ecological network construction indicated that members of the Acidobacteria GP4 and GP6 were more abundant in soils with relatively high SOC whereas Acidobacteria GP1, GP7, and Actinobacteria were more prevalent in soil with lower SOC. Burning of winter fallow vegetation led to an increase in Bacillales, especially those belonging to spore-forming genera. Of the managements, pigeon-pea cultivation during the winter period promoted a higher microbial diversity and also sequestered more SOC, presumably improving soil structure, fertility, and resiliency.

We recently identified CD46 as a novel prostate cancer cell surface antigen that shows lineage independent expression in both adenocarcinoma and small cell neuroendocrine subtypes of metastatic castration resistant prostate cancer (mCRPC), discovered an internalizing human monoclonal antibody YS5 that binds to a tumor selective CD46 epitope, and developed a microtubule inhibitor-based antibody drug conjugate that is in a multi-center phase I trial for mCRPC (NCT03575819). Here we report the development of a novel CD46-targeted alpha therapy based on YS5. We conjugated ²¹²Pb, an in vivo generator of alpha-emitting ²¹²Bi and ²¹²Po, to YS5 through the chelator TCMC to create the radioimmunoconjugate, ²¹²Pb-TCMC-YS5. We characterized ²¹²Pb-TCMC-YS5 in vitro and established a safe dose in vivo. We next studied therapeutic efficacy of a single dose of ²¹²Pb-TCMC-YS5 using three prostate cancer small animal models: a subcutaneous mCRPC cell line-derived xenograft (CDX) model (subcu-CDX), an orthotopically grafted mCRPC CDX model (ortho-CDX), and a prostate cancer patient-derived xenograft model (PDX). In all three models, a single dose of 0.74 MBq (20 µCi) ²¹²Pb-TCMC-YS5 was well tolerated and caused potent and sustained inhibition of established tumors, with significant increases of survival in treated animals. A lower dose (0.37 MBq or 10 µCi ²¹²Pb-TCMC-YS5) was also studied on the PDX model, which also showed a significant effect on tumor growth inhibition and prolongation of animal survival. These results demonstrate that ²¹²Pb-TCMC-YS5 has an excellent therapeutic window in preclinical models including PDXs, opening a direct path for clinical translation of this novel CD46-targeted alpha radioimmunotherapy for mCRPC treatment.

Since nitrogen (N) is often limiting in permafrost soils, we investigated the N₂-fixing genetic potential and the inferred taxa harboring those genes by sequencing nifH gene fragments in samples taken along a permafrost thaw gradient in an Alaskan boreal soil. Samples from minimally, moderately and extensively thawed sites were taken to a depth of 79 cm to encompass zones above and below the depth of the water table. NifH reads were translated with frameshift correction and 112,476 sequences were clustered at 5% amino acid dissimilarity resulting in 1,631 OTUs. Sample depth in relation to water table depth was correlated to differences in the NifH sequence classes with those most closely related to group I nifH-harboring Alpha- and Beta-Proteobacteria in higher abundance above water table depth while those related to group III nifH-harboring Delta Proteobacteria more abundant below. The most dominant below water table depth NifH sequences, comprising 1/3 of the total, were distantly related to Verrucomicrobia-Opitutaceae. Overall, these results suggest that permafrost thaw alters the class-level composition of N₂-fixing communities in the thawed soil layers and that this distinction corresponds to the depth of the water table. These nifH data were also compared to nifH sequences obtained from a study at an Alaskan taiga site, and to those of other geographically distant, non-permafrost sites. The two Alaska sites were differentiated largely by changes in relative abundances of the same OTUs, whereas the non-Alaska sites were differentiated by the lack of many Alaskan OTUs, and the presence of unique halophilic, sulfate- and iron-reducing taxa in the Alaska sites.