Simultaneous Quantification of Multiple Bacteria by the BactoChip Microarray Designed to Target Species-Specific Marker Genes

Bacteria are ubiquitous throughout the environment, the most abundant inhabitants of the healthy human microbiome, and causal pathogens in a variety of diseases. Their identification in disease is often an essential step in rapid diagnosis and targeted intervention, particularly in clinical settings. At present, clinical bacterial detection and discrimination is primarily culture-based, requiring both time and microbiological expertise, especially for bacteria that are not easily cultivated. Higher-throughput molecular methods based on PCR amplification or, recently, microarrays are reaching the clinic as well. However, these methods are currently restricted to a small set of microbes or based on conserved phylogenetic markers such as the 16S rRNA gene, which are difficult to resolve at the species or strain levels. Here, we designed and experimentally validated the BactoChip, an oligonucleotide microarray for bacterial detection and quantification. The chip allows the culture-independent identification of bacterial species, also determining their relative abundances in complex communities as occur in the commensal microbiota or in clinical settings. The microarray successfully distinguished among bacterial species from 21 different genera using 60-mer probes targeting a novel set of in silico identified high-resolution marker genes. The BactoChip additionally proved accurate in determining species-level relative abundances over a 100-fold dynamic range in complex bacterial communities and with a low limit of detection (0.1%). In combination with the continually increasing number of sequenced bacterial genomes, future iterations of the technology could enable to highly accurate clinically-oriented tools for rapid assessment of bacterial community composition and relative abundances

Metagenomic microbial community profiling using unique clade-specific marker genes

Metagenomic shotgun sequencing data can identify microbes populating a microbial community and their proportions, but existing taxonomic profiling methods are inefficient for increasingly large datasets. We present an approach that uses clade-specific marker genes to unambiguously assign reads to microbial clades more accurately and >50× faster than current approaches. We validated MetaPhlAn on terabases of short reads and provide the largest metagenomic profiling to date of the human gu

New rutile Ga/V/Nb/Sb mixed oxides as catalysts for propane ammoxidation to acrylonitrile

Here we report on the chemical–physical characteristics and reactivity in propane ammoxidation to acrylonitrile of a new class of rutile-type, GaSbO4-based multicomponent oxides. The GaSbO4 rutile was much less active than the conventional VSbO4-based rutile systems, but showed a good selectivity to acrylonitrile. The incorporation of V in GaSbO4 allowed for an improvement in catalytic activity, but with decreased maximum selectivity to acrylonitrile. However, the further incorporation of Nb (thereby developing a Ga/V/Nb/Sb mixed oxide) led to a mixed oxide that presented an enhanced catalytic behavior, combining both high activity and high selectivity to acrylonitrile. The Nb presence also greatly improved the stability of the catalytic system, hindering the crystallization phenomena observed with rutile Ga/V/Sb/O systems

Dysbiosis in Pediatrics Is Associated with Respiratory Infections: Is There a Place for Bacterial-Derived Products?

Respiratory tract infections (RTIs) are common in childhood because of the physiologic immaturity of the immune system, a microbial community under development in addition to other genetic, physiological, environmental and social factors. RTIs tend to recur and severe lower viral RTIs in early childhood are not uncommon and are associated with increased risk of respiratory disorders later in life, including recurrent wheezing and asthma. Therefore, a better understanding of the main players and mechanisms involved in respiratory morbidity is necessary for a prompt and improved care as well as for primary prevention. The inter-talks between human immune components and microbiota as well as their main functions have been recently unraveled; nevertheless, more is still to be discovered or understood in the above medical conditions. The aim of this review paper is to provide the most up-to-date overview on dysbiosis in pre-school children and its association with RTIs and their complications. The potential role of non-harmful bacterial-derived products, according to the old hygiene hypothesis and the most recent trained-innate immunity concept, will be discussed together with the need of proof-of-concept studies and larger clinical trials with immunological and microbiological endpoints

Microbiota profiles in pre-school children with respiratory infections: Modifications induced by the oral bacterial lysate OM-85

To describe microbiota profiles considering potential influencing factors in pre-school children with recurrent respiratory tract infections (rRTIs) and to evaluate microbiota changes associated with oral bacterial lysate OM-85 treatment, we analyzed gut and nasopharynx (NP) microbiota composition in patients included in the OM-85-pediatric rRTIs (OMPeR) clinical trial (https://www.clinicaltrialsregister.eu/ctr-search/trial/2016-002705-19/IT). Relative percentage abundance was used to describe microbiota profiles in all the available biological specimens, grouped by age, atopy, and rRTIs both at inclusion (T0) and at the end of the study, after treatment with OM-85 or placebo (T1). At T0, Firmicutes and Bacteriodetes were the predominant genera in gut and Proteobacteria, Firmicutes, and Actinobacteria were the predominant genera in NP samples. Gut microbiota relative composition differed with age (<2 vs. >= 2 years) for Firmicutes, Proteobacteria, Actinobacteria (phyla) and Bifidobacterium, Ruminococcus, Lachnospiraceae (genera) (p < 0.05). Moraxella was more enriched in the NP of patients with a history of up to three RTIs. Intra-group changes in relative percentage abundance were described only for patients with gut and NP microbiota analysis available at both T0 and T1 for each study arm. In this preliminary analysis, the gut microbiota seemed more stable over the 6-month study in the OM-85 group, whose mean age was lower, as compared to the placebo group (p = 0.004). In this latter group, the relative abundance of Bacteroides decreased significantly in children >= 2 years. Some longitudinal significant differences in genera relative abundance were also detected in children of >= 2 years for NP Actinobacteria, Haemophilus, and Corynebacterium in the placebo group only. Due to the small number of patients in the different sub-populations, we could not identify significant differences in the clinical outcome and therefore no associations with microbiota changes were searched. The use of bacterial lysates might play a role in microbiota rearrangement, but further data and advanced analysis are needed to prove this in less heterogeneous populations with higher numbers of samples considering the multiple influencing factors such as delivery method, age, environment, diet, antibiotic use, and type of infections to ultimately show any associations with prevention of rRTIs

Quantification of the relative abundances of multiple species from the same genus contained within a single sample.

<p>True versus detected relative abundances for each of 6 <i>Staphylococcus</i> species are shown in blue (gold standard) and red (inferred), respectively. Even DNA relative abundances were targeted, with true experimental abundances of cell copy numbers varying due to differences in genome size. Mean Squared Error (MSE) of relative abundance over all predictions was below 0.0019.</p

Design of the BactoChip and its application for microbial species identification and quantification.

<p>(A) Schematic overview of computational design and its output. (A1) Complete genomes from 186 bacterial species were retrieved from the National Centre for Biotechnology Information microbial database. (A2) Gene sequences core to each target species were defined on the basis of sequence conservation within each clade. Red dots represent the distribution of core genes shared by strains within and outside a target clade. (A3) Core genes unique to each target species were selected by sequence alignment against all available archaeal and bacterial sequences. (A4) Oligonucleotide probes were designed for up to 10 identified unique genes for each target bacterial species. Each probe color represents specificity to a defined bacterial species. (B) Experimental design and example data. (B1) DNA from microbial communities was tested on the BactoChip. Green dots represent Cy3 bound to genomic DNA fragments from a sample hybridized to the chip. (B2) Species relative abundances are finally inferred by normalization of the fluorescence signal for each probe and species.</p