Dense time-series metabolomics data are essential for unraveling the underlying dynamic properties of metabolism. Here we extend high-resolution-magic angle spinning (HR-MAS) to enable continuous in vivo monitoring of metabolism by NMR (CIVM-NMR) and provide analysis tools for these data. First, we reproduced a result in human chronic lymphoid leukemia cells by using isotope-edited CIVM-NMR to rapidly and unambiguously demonstrate unidirectional flux in branched-chain amino acid metabolism. We then collected untargeted CIVM-NMR datasets for Neurospora crassa , a classic multicellular model organism, and uncovered dynamics between central carbon metabolism, amino acid metabolism, energy storage molecules, and lipid and cell wall precursors. Virtually no sample preparation was required to yield a dynamic metabolic fingerprint over hours to days at ~4-min temporal resolution with little noise. CIVM-NMR is simple and readily adapted to different types of cells and microorganisms, offering an experimental complement to kinetic models of metabolism for diverse biological systems.

Metabolomics is the study of the metabolome, the collection of small molecules in living organisms, cells, tissues, and biofluids. Technological advances in mass spectrometry, liquid- and gas-phase separations, nuclear magnetic resonance spectroscopy, and big data analytics have now made it possible to study metabolism at an omics or systems level. The significance of this burgeoning scientific field cannot be overstated: It impacts disciplines ranging from biomedicine to plant science. Despite these advances, the central bottleneck in metabolomics remains the identification of key metabolites that play a class-discriminant role. Because metabolites do not follow a molecular alphabet as proteins and nucleic acids do, their identification is much more time consuming, with a high failure rate. In this review, we critically discuss the state-of-the-art in metabolite identification with specific applications in metabolomics and how technologies such as mass spectrometry, ion mobility, chromatography, and nuclear magnetic resonance currently contribute to this challenging task.

Source attribution studies report that the consumption of contaminated poultry is the primary source for acquiring human campylobacteriosis. Oral administration of an engineered Escherichia coli strain expressing the Campylobacter jejuni N-glycan reduces bacterial colonization in specific-pathogen-free leghorn chickens, but only a fraction of birds respond to vaccination. Optimization of the vaccine for commercial broiler chickens has great potential to prevent the entry of the pathogen into the food chain. Here, we tested the same vaccination approach in broiler chickens and observed similar efficacies in pathogen load reduction, stimulation of the host IgY response, the lack of C. jejuni resistance development, uniformity in microbial gut composition, and the bimodal response to treatment. Gut microbiota analysis of leghorn and broiler vaccine responders identified one member of Clostridiales cluster XIVa, Anaerosporobacter mobilis, that was significantly more abundant in responder birds. In broiler chickens, coadministration of the live vaccine with A. mobilis or Lactobacillus reuteri, a commonly used probiotic, resulted in increased vaccine efficacy, antibody responses, and weight gain. To investigate whether the respondernonresponder effect was due to the selection of a C. jejuni "supercolonizer mutant" with altered phase-variable genes, we analyzed all poly(G)-containing loci of the input strain compared to nonresponder colony isolates and found no evidence of phase state selection. However, untargeted nuclear magnetic resonance (NMR)-based metabolomics identified a potential biomarker negatively correlated with C. jejuni colonization levels that is possibly linked to increased microbial diversity in this subgroup. The comprehensive methods used to examine the bimodality of the vaccine response provide several opportunities to improve the C. jejuni vaccine and the efficacy of any vaccination strategy.IMPORTANCE Campylobacter jejuni is a common cause of human diarrheal disease worldwide and is listed by the World Health Organization as a high-priority pathogen. C. jejuni infection typically occurs through the ingestion of contaminated chicken meat, so many efforts are targeted at reducing C. jejuni levels at the source. We previously developed a vaccine that reduces C. jejuni levels in egg-laying chickens. In this study, we improved vaccine performance in meat birds by supplementing the vaccine with probiotics. In addition, we demonstrated that C. jejuni colonization levels in chickens are negatively correlated with the abundance of clostridia, another group of common gut microbes. We describe new methods for vaccine op-

Glycosyltransferases (GTs) are prevalent across the tree of life and regulate nearly all aspects of cellular functions. The evolutionary basis for their complex and diverse modes of catalytic functions remain enigmatic. Here, based on deep mining of over half million GT-A fold sequences, we define a minimal core component shared among functionally diverse enzymes. We find that variations in the common core and emergence of hypervariable loops extending from the core contributed to GT-A diversity. We provide a phylogenetic framework relating diverse GT-A fold families for the first time and show that inverting and retaining mechanisms emerged multiple times independently during evolution. Using evolutionary information encoded in primary sequences, we trained a machine learning classifier to predict donor specificity with nearly 90% accuracy and deployed it for the annotation of understudied GTs. Our studies provide an evolutionary framework for investigating complex relationships connecting GT-A fold sequence, structure, function and regulation.