David Zeevi

Artificial sweeteners induce glucose intolerance by altering the gut microbiota

Non-caloric artificial sweeteners (NAS) are among the most widely used food additives worldwide, regularly consumed by lean and obese individuals alike. NAS consumption is considered safe and beneficial owing to their low caloric content, yet supporting scientific data remain sparse and controversial. Here we demonstrate that consumption of commonly used NAS formulations drives the development of glucose intolerance through induction of compositional and functional alterations to the intestinal microbiota. These NAS-mediated deleterious metabolic effects are abrogated by antibiotic treatment, and are fully transferrable to germ-free mice upon faecal transplantation of microbiota configurations from NAS-consuming mice, or of microbiota anaerobically incubated in the presence of NAS. We identify NAS-altered microbial metabolic pathways that are linked to host susceptibility to metabolic disease, and demonstrate similar NAS-induced dysbiosis and glucose intolerance in healthy human subjects. Collectively, our results link NAS consumption, dysbiosis and metabolic abnormalities, thereby calling for a reassessment of massive NAS usage.

Personalized Nutrition by Prediction of Glycemic Responses.

Elevated postprandial blood glucose levels constitute a global epidemic and a major risk factor for prediabetes and type II diabetes, but existing dietary methods for controlling them have limited efficacy. Here, we continuously monitored week-long glucose levels in an 800-person cohort, measured responses to 46,898 meals, and found high variability in the response to identical meals, suggesting that universal dietary recommendations may have limited utility. We devised a machine-learning algorithm that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in this cohort and showed that it accurately predicts personalized postprandial glycemic response to real-life meals. We validated these predictions in an independent 100-person cohort. Finally, a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postprandial responses and consistent alterations to gut microbiota configuration. Together, our results suggest that personalized diets may successfully modify elevated postprandial blood glucose and its metabolic consequences. VIDEO ABSTRACT.

Microbiota Diurnal Rhythmicity Programs Host Transcriptome Oscillations

The intestinal microbiota undergoes diurnal compositional and functional oscillations that affect metabolic homeostasis, but the mechanisms by which the rhythmic microbiota influences host circadian activity remain elusive. Using integrated multi-omics and imaging approaches, we demonstrate that the gut microbiota features oscillating biogeographical localization and metabolome patterns that determine the rhythmic exposure of the intestinal epithelium to different bacterial species and their metabolites over the course of a day. This diurnal microbial behavior drives, in turn, the global programming of the host circadian transcriptional, epigenetic, and metabolite oscillations. Surprisingly, disruption of homeostatic microbiome rhythmicity not only abrogates normal chromatin and transcriptional oscillations of the host, but also incites genome-wide de novo oscillations in both intestine and liver, thereby impacting diurnal fluctuations of host physiology and disease susceptibility. As such, the rhythmic biogeography and metabolome of the intestinal microbiota regulates the temporal organization and functional outcome of host transcriptional and epigenetic programs.

Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples

Estimating bacterial growth dynamics The pattern of sequencing read coverage of bacteria in metagenomic samples reflects the growth rate. This pattern is predictive of growth because bacterial genomes are circular, with a single origin of replication. So during growth, copies of the genome accumulate at the origin. Korem et al. use the ratio of copy number at the origin to the copy number at the terminus to detect the actively growing species in a microbiome (see the Perspective by Segre). They could spot the difference between virulent and avirulent strains, population diurnal oscillations, species that are growing in irritable bowel disease, and what happens when a hosts diet changes. Results were consistent in chemostats, in mice, and in human fecal samples. Science, this issue p. 1101; see also p. 1058 A new method provides a quantitative measure of the growth rate of multiple gut microbes in one go. [Also see Perspective by Segre] Metagenomic sequencing increased our understanding of the role of the microbiome in health and disease, yet it only provides a snapshot of a highly dynamic ecosystem. Here, we show that the pattern of metagenomic sequencing read coverage for different microbial genomes contains a single trough and a single peak, the latter coinciding with the bacterial origin of replication. Furthermore, the ratio of sequencing coverage between the peak and trough provides a quantitative measure of a species’ growth rate. We demonstrate this in vitro and in vivo, under different growth conditions, and in complex bacterial communities. For several bacterial species, peak-to-trough coverage ratios, but not relative abundances, correlated with the manifestation of inflammatory bowel disease and type II diabetes.

Environment dominates over host genetics in shaping human gut microbiota

Human gut microbiome composition is shaped by multiple factors but the relative contribution of host genetics remains elusive. Here we examine genotype and microbiome data from 1,046 healthy individuals with several distinct ancestral origins who share a relatively common environment, and demonstrate that the gut microbiome is not significantly associated with genetic ancestry, and that host genetics have a minor role in determining microbiome composition. We show that, by contrast, there are significant similarities in the compositions of the microbiomes of genetically unrelated individuals who share a household, and that over 20% of the inter-person microbiome variability is associated with factors related to diet, drugs and anthropometric measurements. We further demonstrate that microbiome data significantly improve the prediction accuracy for many human traits, such as glucose and obesity measures, compared to models that use only host genetic and environmental data. These results suggest that microbiome alterations aimed at improving clinical outcomes may be carried out across diverse genetic backgrounds.

Phosphatidylserine Increases IKBKAP Levels in Familial Dysautonomia Cells

Familial Dysautonomia (FD) is an autosomal recessive congenital neuropathy that results from abnormal development and progressive degeneration of the sensory and autonomic nervous system. The mutation observed in almost all FD patients is a point mutation at position 6 of intron 20 of the IKBKAP gene; this gene encodes the IκB kinase complex-associated protein (IKAP). The mutation results in a tissue-specific splicing defect: Exon 20 is skipped, leading to reduced IKAP protein expression. Here we show that phosphatidylserine (PS), an FDA-approved food supplement, increased IKAP mRNA levels in cells derived from FD patients. Long-term treatment with PS led to a significant increase in IKAP protein levels in these cells. A conjugate of PS and an omega-3 fatty acid also increased IKAP mRNA levels. Furthermore, PS treatment released FD cells from cell cycle arrest and up-regulated a significant number of genes involved in cell cycle regulation. Our results suggest that PS has potential for use as a therapeutic agent for FD. Understanding its mechanism of action may reveal the mechanism underlying the FD disease.

A day in the life of the meta-organism: diurnal rhythms of the intestinal microbiome and its host

Life on Earth is dictated by circadian changes in the environment, caused by the planets rotation around its own axis. All forms of life have evolved clock systems to adapt their physiology to the daily variations in geophysical parameters. The intestinal microbiome serves as a signaling hub in the communication between the host and its environment. We recently discovered that the microbiota undergoes diurnal oscillations in composition and function, and that these oscillations are required for metabolic homeostasis of the host. Here, we highlight these findings from the perspectives of microbial system stability and meta-organismal metabolic health. We also discuss the contribution of nutrition and biotic interventions on diurnal processes of the microbiota and their potential involvement in diseases commonly associated with circadian disruption.

Environmental factors dominate over host genetics in shaping human gut microbiota composition

Human gut microbiome composition is shaped by multiple host intrinsic and extrinsic factors, but the relative contribution of host genetic compared to environmental factors remains elusive. Here, we genotyped a cohort of 696 healthy individuals from several distinct ancestral origins and a relatively common environment, and demonstrate that there is no statistically significant association between microbiome composition and ethnicity, single nucleotide polymorphisms (SNPs), or overall genetic similarity, and that only 5 of 211 (2.4%) previously reported microbiome-SNP associations replicate in our cohort. In contrast, we find similarities in the microbiome composition of genetically unrelated individuals who share a household. We define the term biome-explainability as the variance of a host phenotype explained by the microbiome after accounting for the contribution of human genetics. Consistent with our finding that microbiome and host genetics are largely independent, we find significant biome-explainability levels of 16-33% for body mass index (BMI), fasting glucose, high-density lipoprotein (HDL) cholesterol, waist circumference, waist-hip ratio (WHR), and lactose consumption. We further show that several human phenotypes can be predicted substantially more accurately when adding microbiome data to host genetics data, and that the contribution of both data sources to prediction accuracy is largely additive. Overall, our results suggest that human microbiome composition is dominated by environmental factors rather than by host genetics.

Talking about cross-talk: the immune system and the microbiome

A report on the first EMBO conference entitled “Next Gen Immunology—From Host Genome to the Microbiome: Immunity in the Genomic Era”, held at the Weizmann Institute of Science, Israel, 14–16 February, 2016.

The operonic location of auto-transcriptional repressors is highly conserved in bacteria.

Bacterial genes are commonly encoded in clusters, known as operons, which share transcriptional regulatory control and often encode functionally related proteins that take part in certain biological pathways. Operons that are coregulated are known to colocalize in the genome, suggesting that their spatial organization is under selection for efficient expression regulation. However, the internal order of genes within operons is believed to be poorly conserved, and hence expression requirements are claimed to be too weak to oppose gene rearrangements. In light of these opposing views, we set out to investigate whether the internal location of the regulatory genes within operons is under selection. Our analysis shows that transcription factors (TFs) are preferentially encoded as either first or last in their operons, in the two diverged model bacteria Escherichia coli and Bacillus subtilis. In a higher resolution, we find that TFs that repress transcription of the operon in which they are encoded (autorepressors), contribute most of this signal by specific preference of the first operon position. We show that this trend is strikingly conserved throughout highly diverged bacterial phyla. Moreover, these autorepressors regulate operons that carry out highly diverse biological functions. We propose a model according to which autorepressors are selected to be located first in their operons in order to optimize transcription regulation. Specifically, the first operon position helps autorepressors to minimize leaky transcription of the operon structural genes, thus minimizing energy waste. Our analysis provides statistically robust evidence for a paradigm of bacterial autorepressor preferential operonic location. Corroborated with our suggested model, an additional layer of operon expression control that is common throughout the bacterial domain is revealed.