Combined analysis of microbial metagenomic and metatranscriptomic sequencing data to assess in situ physiological conditions in the premature infant gut.

Microbes alter their transcriptomic profiles in response to the environment. The physiological conditions experienced by a microbial community can thus be inferred using meta-transcriptomic sequencing by comparing transcription levels of specifically chosen genes. However, this analysis requires accurate reference genomes to identify the specific genes from which RNA reads originate. In addition, such an analysis should avoid biases in transcript counts related to differences in organism abundance. In this study we describe an approach to address these difficulties. Sample-specific meta-genomic assembled genomes (MAGs) were used as reference genomes to accurately identify the origin of RNA reads, and transcript ratios of genes with opposite transcription responses were compared to eliminate biases related to differences in organismal abundance, an approach hereafter named the "diametric ratio" method. We used this approach to probe the environmental conditions experienced by Escherichia spp. in the gut of 4 premature infants, 2 of whom developed necrotizing enterocolitis (NEC), a severe inflammatory intestinal disease. We analyzed twenty fecal samples taken from four premature infants (4-6 time points from each infant), and found significantly higher diametric ratios of genes associated with low oxygen levels in samples of infants later diagnosed with NEC than in samples without NEC. We also show this method can be used for examining other physiological conditions, such as exposure to nitric oxide and osmotic pressure. These study results should be treated with caution, due to the presence of confounding factors that might also distinguish between NEC and control infants. Nevertheless, together with benchmarking analyses, we show here that the diametric ratio approach can be applied for evaluating the physiological conditions experienced by microbes in situ. Results from similar studies can be further applied for designing diagnostic methods to detect NEC in its early developmental stages

Constraints on profit income distribution and production efficiency in private ownership economies with Ramsey taxation

Author's draft published as discussion paper by University of Exeter Department of Economics. The original publication is available at www.springerlink.comIn economies with Ramsey taxation, decreasing returns to scale, and private ownership, we show that second-best production efficiency is desirable when the grouping of private firms induced by the profit taxation power of the government is at least as fine as the grouping of firms induced by the institutional rules of profit distribution in the economy. The classic results of Dasgupta and Stiglitz [1972] (of firm-specific profit taxation) and Diamond and Mirrlees [1971] and Guesnerie [1995] (of uniform one-hundred percent profit taxation) follow as special cases of our model. Moreover, second-best analysis shows that optimal profit taxation is a substitute for optimal intermediate input taxation. In smooth economies, proportional, lump-sum, and affine modes of profit taxation are equivalent. We rework Mirrlees [1972] counterexample, which is posed in the context of a non-smooth economy, to show that second-best production efficiency continues to remain desirable under an affine structure of profit taxation

Taxing the Informal Economy: The Current State of Knowledge and Agendas for Future Research

This paper reviews the literature on taxation of the informal economy, taking stock of key debates and drawing attention to recent innovations. Conventionally, the debate on whether to tax has frequently focused on the limited revenue potential, high cost of collection, and potentially adverse impact on small firms. Recent arguments have increasingly emphasised the more indirect benefits of informal taxation in relation to economic growth, broader tax compliance, and governance. More research is needed, we argue, into the relevant costs and benefits for all, including quasi-voluntary compliance, political and administrative incentives for reform, and citizen-state bargaining over taxation

Lactobacillus rhamnosus GG-supplemented formula expands butyrate-producing bacterial strains in food allergic infants.

Dietary intervention with extensively hydrolyzed casein formula supplemented with Lactobacillus rhamnosus GG (EHCF+LGG) accelerates tolerance acquisition in infants with cow's milk allergy (CMA). We examined whether this effect is attributable, at least in part, to an influence on the gut microbiota. Fecal samples from healthy controls (n=20) and from CMA infants (n=19) before and after treatment with EHCF with (n=12) and without (n=7) supplementation with LGG were compared by 16S rRNA-based operational taxonomic unit clustering and oligotyping. Differential feature selection and generalized linear model fitting revealed that the CMA infants have a diverse gut microbial community structure dominated by Lachnospiraceae (20.5±9.7%) and Ruminococcaceae (16.2±9.1%). Blautia, Roseburia and Coprococcus were significantly enriched following treatment with EHCF and LGG, but only one genus, Oscillospira, was significantly different between infants that became tolerant and those that remained allergic. However, most tolerant infants showed a significant increase in fecal butyrate levels, and those taxa that were significantly enriched in these samples, Blautia and Roseburia, exhibited specific strain-level demarcations between tolerant and allergic infants. Our data suggest that EHCF+LGG promotes tolerance in infants with CMA, in part, by influencing the strain-level bacterial community structure of the infant gut

Effect of promoter architecture on the cell-to-cell variability in gene expression

According to recent experimental evidence, the architecture of a promoter, defined as the number, strength and regulatory role of the operators that control the promoter, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect noise in gene expression in a systematic rather than case-by-case fashion. In this article, we make such a systematic investigation, based on a simple microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous) and how each of these affects the level of variability in transcription product from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can discriminate between different kinetic models of gene regulation.Comment: 35 pages, 6 figures, Submitte

Current understanding of the human microbiome

Author Posting. © The Author(s), 2018. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature Medicine 24 (2018): 392–400, doi:10.1038/nm.4517.Our understanding of the link between the human microbiome and disease, including obesity, inflammatory bowel disease, arthritis and autism, is rapidly expanding. Improvements in the throughput and accuracy of DNA sequencing of the genomes of microbial communities associated with human samples, complemented by analysis of transcriptomes, proteomes, metabolomes and immunomes, and mechanistic experiments in model systems, have vastly improved our ability to understand the structure and function of the microbiome in both diseased and healthy states. However, many challenges remain. In this Review, we focus on studies in humans to describe these challenges, and propose strategies that leverage existing knowledge to move rapidly from correlation to causation, and ultimately to translation.Many of the studies described here in our laboratories were supported by the NIH, NSF, DOE, and the Alfred P. Sloan Foundation.2018-10-1

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Redistributive taxation as social insurance

The modern literature on nonlinear optimal taxation treats differences in income as being due to unobserved differences in ability. A striking result of this assumption is that high income agents should face a zero marginal tax rate. In this paper I assume that differences in observed income are due to exogenous differences in luck. Hence the optimal redistributive tax involves trading off the benefits due to 'social insurance' with the costs due to reduced incentives. I derive the optimal forms for linear and nonlinear taxes, and compute some algebraic and numeric examples. Typically high income individuals will face quite high marginal tax rates.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23175/1/0000102.pd

The Size Effect in Value and Momentum Factors: Implications for the Cross-Section of International Stock Returns

We document a consistent and robust relation between expected equity premia and common risk factors constructed on the basis of small stocks. Empirically, we show that (i) small-stock components of traditional value and momentum factors capture patterns in returns on regional and global portfolios of stocks; (ii) size-effect models substantially outperform benchmark models in finance; (iii) global small-stock value and momentum components are priced but regional models lead to more accurate asset evaluations; (iv) funding liquidity risk is a partial explanation of these findings