•Exposure to air pollutants is associated with the composition of the gut microbiome using whole-genome sequencing.•O3 exposure is associated with lower gut microbial diversity, higher Bacteroides ...caecimuris, and multiple gene pathways.•Air pollution may contribute to alterations in the composition and function of the human gut microbiome.
Animal work indicates exposure to air pollutants may alter the composition of the gut microbiota. This study examined relationships between air pollutants and the gut microbiome in young adults residing in Southern California. Our results demonstrate significant associations between exposure to air pollutants and the composition of the gut microbiome using whole-genome sequencing. Higher exposure to 24-hour O3 was associated with lower Shannon diversity index, higher Bacteroides caecimuris, and multiple gene pathways, including L-ornithine de novo biosynthesis as well as pantothenate and coenzyme A biosynthesis I. Among other pollutants, higher NO2 exposure was associated with fewer taxa, including higher Firmicutes. The percent variation in gut bacterial composition that was explained by air pollution exposure was up to 11.2% for O3 concentrations, which is large compared to the effect size for many other covariates reported in healthy populations. This study provides the first evidence of significant associations between exposure to air pollutants and the compositional and functional profile of the human gut microbiome. These results identify O3 as an important pollutant that may alter the human gut microbiome.
Batch effects in microbiome data arise from differential processing of specimens and can lead to spurious findings and obscure true signals. Strategies designed for genomic data to mitigate batch ...effects usually fail to address the zero-inflated and over-dispersed microbiome data. Most strategies tailored for microbiome data are restricted to association testing or specialized study designs, failing to allow other analytic goals or general designs. Here, we develop the Conditional Quantile Regression (ConQuR) approach to remove microbiome batch effects using a two-part quantile regression model. ConQuR is a comprehensive method that accommodates the complex distributions of microbial read counts by non-parametric modeling, and it generates batch-removed zero-inflated read counts that can be used in and benefit usual subsequent analyses. We apply ConQuR to simulated and real microbiome datasets and demonstrate its advantages in removing batch effects while preserving the signals of interest.
We implement a unique strategy for single molecule counting termed stochastic labeling, where random attachment of a diverse set of labels converts a population of identical DNA molecules into a ...population of distinct DNA molecules suitable for threshold detection. The conceptual framework for stochastic labeling is developed and experimentally demonstrated by determining the absolute and relative number of selected genes after stochastically labeling approximately 360,000 different fragments of the human genome. The approach does not require the physical separation of molecules and takes advantage of highly parallel methods such as microarray and sequencing technologies to simultaneously count absolute numbers of multiple targets. Stochastic labeling should be particularly useful for determining the absolute numbers of RNA or DNA molecules in single cells.
We present a search for the direct production of a light pseudoscalar a decaying into two photons with the Belle II detector at the SuperKEKB collider. We search for the process e+e−→γa, a→γγ in the ...mass range 0.2<ma<9.7 GeV/c2 using data corresponding to an integrated luminosity of (445±3) pb−1. Light pseudoscalars interacting predominantly with standard model gauge bosons (so-called axionlike particles or ALPs) are frequently postulated in extensions of the standard model. We find no evidence for ALPs and set 95% confidence level upper limits on the coupling strength gaγγ of ALPs to photons at the level of 10−3 GeV−1. The limits are the most restrictive to date for 0.2<ma<1 GeV/c2.
This study examined associations between the composition and diversity of the intestinal microbiota and measures of depression, anxiety, eating disorder psychopathology, stress, and personality in a ...group of healthy adult females.
Female participants (n = 91) ages 19-50 years with BMI 18.5-25 kg/m2 were recruited from central North Carolina between July 2014 and March 2015. Participants provided a single fecal sample and completed an online psychiatric questionnaire that included five measures: (i) Beck Anxiety Inventory; (ii) Beck Depression Inventory-II; (iii) Eating Disorder Examination-Questionnaire; (iv) Perceived Stress Scale; and (v) Mini International Personality Item Pool. Bacterial composition and diversity were characterized by Illumina sequencing of the 16S rRNA gene, and associations were examined using Kendall's tau-b correlation coefficient, in conjunction with Benjamini and Hochberg's False Discovery Rate procedure.
We found no significant associations between microbial markers of gut composition and diversity and scores on psychiatric measures of anxiety, depression, eating-related thoughts and behaviors, stress, or personality in a large cohort of healthy adult females.
This study was the first specifically to examine associations between the intestinal microbiota and psychiatric measures in healthy females, and based on 16S rRNA taxonomic abundances and diversity measures, our results do not suggest a strong role for the enteric microbe-gut-brain axis in normal variation on responses to psychiatric measures in this population. However, the role of the intestinal microbiota in the pathophysiology of psychiatric illness may be limited to more severe psychopathology.
Broad-spectrum antibiotics produced by symbiotic bacteria entomopathogenic bacterium (EPB) of entomopathogenic nematodes keep monoxenic conditions in insect cadavers in soil. This study evaluated ...antibiotics produced by EPB for their potential to control plant pathogenic bacteria and oomycetes. Entomopathogenic bacterium produce antibiotics effective against the fire blight bacterium Erwinia amylovora, including streptomycin resistant strains, and were as effective in phytotron experiments as kasugamycin or streptomycin. Xenorhabdus budapestensis and X. szentirmaii antibiotics inhibited colony formation and mycelial growth of Phytophthora nicotianae. From X. budapestensis, an arginine-rich fraction (bicornutin) was adsorbed by Amberlite® XAD 1180, and eluted with methanol : 1 n HCI (99 : 1). Bicornutin inactivated zoospores, and inhibited germination and colony formation of cystospores at <<25 ppm. An UV-active molecule (bicornutin-A, MW = 826), separated by HPLC and thin-layer chromatography, was identified as a novel hexa-peptide : RLRRRX. Xenorhabdus budapestensis produces metabolites with strong antibacterial and cytotoxic activity. Individual compounds can be isolated, identified and patented, but their full antimicrobial potential may be multiplied by synergic interactions. Active compounds of two new Xenorhabdus species might control plant diseases caused by pathogens of great importance to agriculture such as Erw. amylovora and P. nicotianae.
The sequences of the human chromosomes 21 and 22 indicate that there are approximately 770 well-characterized and predicted genes. In this study, empirically derived maps identifying active areas of ...RNA transcription on these chromosomes have been constructed with the use of cytosolic polyadenylated RNA obtained from 11 human cell lines. Oligonucleotide arrays containing probes spaced on average every 35 base pairs along these chromosomes were used. When compared with the sequence annotations available for these chromosomes, it is noted that as much as an order of magnitude more of the genomic sequence is transcribed than accounted for by the predicted and characterized exons.
Anaerobic bacteria are increasingly regarded as important in cystic fibrosis (CF) pulmonary infection. The aim of this study was to determine the effect of antibiotic treatment on aerobic and ...anaerobic microbial community diversity and abundance during exacerbations in patients with CF.
Sputum was collected at the start and completion of antibiotic treatment of exacerbations and when clinically stable. Bacteria were quantified and identified following culture, and community composition was also examined using culture-independent methods.
Pseudomonas aeruginosa or Burkholderia cepacia complex were detected by culture in 24/26 samples at the start of treatment, 22/26 samples at completion of treatment and 11/13 stable samples. Anaerobic bacteria were detected in all start of treatment and stable samples and in 23/26 completion of treatment samples. Molecular analysis showed greater bacterial diversity within sputum samples than was detected by culture; there was reasonably good agreement between the methods for the presence or absence of aerobic bacteria such as P aeruginosa (κ=0.74) and B cepacia complex (κ=0.92), but agreement was poorer for anaerobes. Both methods showed that the composition of the bacterial community varied between patients but remained relatively stable in most individuals despite treatment. Bacterial abundance decreased transiently following treatment, with this effect more evident for aerobes (median decrease in total viable count 2.3×10(7) cfu/g, p=0.005) than for anaerobes (median decrease in total viable count 3×10(6) cfu/g, p=0.046).
Antibiotic treatment targeted against aerobes had a minimal effect on abundance of anaerobes and community composition, with both culture and molecular detection methods required for comprehensive characterisation of the microbial community in the CF lung. Further studies are required to determine the clinical significance of and optimal treatment for these newly identified bacteria.
Normalization, as a pre-processing step, can significantly affect the resolution of machine learning analysis for microbiome studies. There are countless options for normalization scheme selection. ...In this study, we examined compositionally aware algorithms including the additive log ratio (alr), the centered log ratio (clr), and a recent evolution of the isometric log ratio (ilr) in the form of balance trees made with the PhILR R package. We also looked at compositionally naïve transformations such as raw counts tables and several transformations that are based on relative abundance, such as proportions, the Hellinger transformation, and a transformation based on the logarithm of proportions (which we call "lognorm").
In our evaluation, we used 65 metadata variables culled from four publicly available datasets at the amplicon sequence variant (ASV) level with a random forest machine learning algorithm. We found that different common pre-processing steps in the creation of the balance trees made very little difference in overall performance. Overall, we found that the compositionally aware data transformations such as alr, clr, and ilr (PhILR) performed generally slightly worse or only as well as compositionally naïve transformations. However, relative abundance-based transformations outperformed most other transformations by a small but reliably statistically significant margin.
Our results suggest that minimizing the complexity of transformations while correcting for read depth may be a generally preferable strategy in preparing data for machine learning compared to more sophisticated, but more complex, transformations that attempt to better correct for compositionality. Video Abstract.
We present a simple molecular indexing method for quantitative targeted RNA sequencing, in which mRNAs of interest are selectively captured from complex cDNA libraries and sequenced to determine ...their absolute concentrations. cDNA fragments are individually labeled so that each molecule can be tracked from the original sample through the library preparation and sequencing process. Multiple copies of cDNA fragments of identical sequence become distinct through labeling, and replicate clones created during PCR amplification steps can be identified and assigned to their distinct parent molecules. Selective capture enables efficient use of sequencing for deep sampling and for the absolute quantitation of rare or transient transcripts that would otherwise escape detection by standard sequencing methods. We have also constructed a set of synthetic barcoded RNA molecules, which can be introduced as controls into the sample preparation mix and used to monitor the efficiency of library construction. The quantitative targeted sequencing revealed extremely low efficiency in standard library preparations, which were further confirmed by using synthetic barcoded RNA molecules. This finding shows that standard library preparation methods result in the loss of rare transcripts and highlights the need for monitoring library efficiency and for developing more efficient sample preparation methods.