To examine the contributions of impaired gut microbial community development to childhood undernutrition, we combined metabolomic and proteomic analyses of plasma samples with metagenomic analyses of fecal samples to characterize the biological state of Bangladeshi children with severe acute malnutrition (SAM) as they transitioned, after standard treatment, to moderate acute malnutrition (MAM) with persistent microbiota immaturity. Host and microbial effects of microbiota-directed complementary food (MDCF) prototypes targeting weaning-phase bacterial taxa underrepresented in SAM and MAM microbiota were characterized in gnotobiotic mice and gnotobiotic piglets colonized with age- and growth-discriminatory bacteria. A randomized, double-blind controlled feeding study identified a lead MDCF that changes the abundances of targeted bacteria and increases plasma biomarkers and mediators of growth, bone formation, neurodevelopment, and immune function in children with MAM.

Metagenomic sequencing of bacterial samples has become the gold standard for profiling microbial populations, but 16S rRNA profiling remains widely used due to advantages in sample throughput, cost, and sensitivity even though the approach is hampered by primer bias and lack of specificity. We hypothesized that a hybrid approach, that combined targeted PCR amplification with high-throughput sequencing of multiple regions of the genome, would capture many of the advantages of both approaches. We developed a method that identifies and quantifies members of bacterial communities through simultaneous analysis of multiple variable regions of the bacterial 16S rRNA gene. The method combines high-throughput microfluidics for PCR amplification, short read DNA sequencing, and a custom algorithm named MVRSION (Multiple 16S Variable Region Species-Level IdentificatiON) for optimizing taxonomic assignment. MVRSION performance was compared to single variable region analyses (V3 or V4) of five synthetic mixtures of human gut bacterial strains using existing software (QIIME), and the results of community profiling by shotgun sequencing (COPRO-Seq) of fecal DNA samples collected from gnotobiotic mice colonized with a defined, phylogenetically diverse consortium of human gut bacterial strains. Positive predictive values for MVSION ranged from 65%−91% versus 44%−61% for single region QIIME analyses (p<0.01, p<0.001), while the abundance estimate r2 for MVRSION compared to COPRO-Seq was 0.77 vs. 0.46 and 0.45 for V3-QIIME and V4-QIIME, respectively. MVRSION represents a generally applicable tool for taxonomic classification that is superior to singleregion 16S rRNA methods, resource efficient, highly scalable for assessing the microbial composition of up to thousands of samples concurrently, with multiple applications ranging from whole community profiling to targeted tracking of organisms of interest in diverse habitats as a function of specified variables/perturbations.

This initial study using new high-resolution MALDI-TOF mass spectrometry coupled with bead fractionation is suitable for automated protein profiling and has the capability to simultaneously identify potential biomarker proteins for HNSCC. In addition, we were able to show improvement with the MALDI-TOF in identifying groups with HNSCC when compared with our prior data using SELDI-TOF. Using this MALDI-TOF technology as a discovery platform, we anticipate generating biomarker panels for use in more accurate prediction of prognosis and treatment efficacies for HNSCC.

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Aims Changes in serotonergic sensory modulation associated with overexpression of 5‐HT3 receptors in the central nervous system (CNS) have been implicated in the pathophysiology of neuropathic pain after peripheral nerve damage. 5‐HT3 receptor antagonists such as ondansetron can potentially alleviate neuropathic pain, but have limited effectiveness, due potentially to limited CNS access. However, there is currently limited information on CNS disposition of systemically‐administered 5‐HT3 receptor antagonists. This study evaluated the cerebrospinal fluid (CSF) disposition of ondansetron, as a surrogate of CNS penetration. Methods Fifteen patients were given a single 16 mg intravenous 15 minute infusion of ondansetron, followed by serial blood and a single CSF sampling. Population pharmacokinetic (PK) modelling was implemented to describe the average and individual plasma and CSF profiles of ondansetron. A two‐compartmental model was used to capture ondansetron plasma PK with a single CSF compartment to describe distribution to the CNS. Results The individual model‐estimated CSF to plasma partition coefficients of ondansetron were between 0.09 and 0.20. These values were mirrored in the calculated CSF penetration ratios, ranging from 0.08 to 0.26. Conclusions After intravenous administration, CSF concentrations of ondansetron were approximately 7‐fold lower than those observed in the plasma. A model could be developed to describe individual CSF concentration–time profiles of ondansetron based on a single CSF data point. The low CSF penetration of ondansetron may explain its limited analgesic effectiveness, and affords an opportunity to explore enhancing its CNS penetration for targeting conditions such as neuropathic pain.