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Zuccotti, G. V.

Publications and source records attributed to Zuccotti, G. V..

6 recordsLinked to original sources

Food-Allergic Children Harbour a Reduced Oral Bacterial Load, Giving Misleading 16S rRNA Amplicon Profiles

BackgroundFood allergies have become a major public health concern in Western countries due to their rising prevalence. The microbiota is increasingly recognized as a key factor in their pathogenesis. Using V3-V4 16S rRNA amplicon sequencing, our group previously reported alterations in the oral microbiota of children with food allergies compared to controls. Given growing awareness of biases associated with relative-abundance analyses in 16S rRNA studies, we re-analyzed the salivary DNA samples from our earlier work. MethodsTotal bacterial loads were quantified by qPCR using universal 16S rRNA primers, enabling the estimation of absolute abundances for each taxon in each sample.These data were then used to reassess key microbial community features and to directly compare conclusions derived from absolute versus relative abundance approaches. ResultsAllergic children exhibited a marked reduction in salivary bacterial load, a feature not detected in the original relative-abundance analysis. Incorporating absolute abundances also partially reshaped the previously defined taxonomic pictures. Similar distortions affected functional predictions, such as Short Chain Fatty Acids (SCFA)-producing capacity. ConclusionsOur data confirm that variations of the bacterial load across samples hinder efforts to associate microbiota features and disease phenotypes. We identify reduced oral bacterial load as a previously unrecognized characteristic of children with food allergies. This observation aligns with reports in other immune-mediated disorders, suggesting that overall microbiota depletion may represent a defining and potentially diagnostically feature of disease-associated ecosystems.

microbiology↗

Unraveling and quantifying "Candidatus Saccharibacteria": in silico and experimental evaluation of V3-V4 16S rRNA metagenomics and qPCR protocols

BackgroundCandidate Phyla Radiation (CPR) is a large monophyletic group thought to cover about 25% of bacterial diversity. Due to peculiar characteristics and unusual 16S rRNA gene structure, they are often under-represented or lost in 16S rRNA-based microbiota surveys. Among CPR, "Candidatus Saccharibacteria" is a phylum experimentally found to modulate the immune response and enriched in the oral microbiota of subjects suffering from several immune-mediated disorders, e.g. food allergies, as reported by us in a previous work. Due to the growing evidence of "Ca. Saccharibacteria"s role in clinical settings and in order to unravel its role in host physiology and pathology, it is crucial to have a reliable method to detect and quantify this lineage. Methods and ResultsFour qPCR protocols for quantifying "Ca. Saccharibacteria" (one targeting the 23S rRNA gene and three the 16S) were selected from the literature among the few available. Efficiency and coverage of primer pairs used in these protocols were preliminary evaluated via in silico analyses on the "Ca. Saccharibacteria" known taxonomic variability, and then tested in vitro on the salivary DNA previously investigated by 16S metagenomics in the food allergy study. In silico analyses evidenced that the 23S qPCR protocol covered more "Ca. Saccharibacteria" variability compared to the 16S-based ones, and that the 16S metagenomics primers were the most comprehensive. qPCR experiments confirmed that 16S-based protocols strongly underestimated "Ca. Saccharibacteria" while the 23S protocol was the only one to yield results comparable to 16S metagenomics both in terms of correlation and absolute quantification. However, only 16S metagenomics evidenced an expansion of "Ca. Saccharibacteria" in allergic subjects compared to controls, while none of the four qPCR protocols detected it. ConclusionThese results underline the current limits in experimentally approaching "Ca. Saccharibacteria". To obtain a more realistic picture of their abundance within bacterial communities, and to enable more efficient taxonomic resolution, it is essential to find novel experimental strategies. This is a necessary premise for more targeted and systematic functional studies to clarify the role of "Ca. Saccharibacteria" and, generally, CPR bacteria, in maintaining the health of the host.

microbiology↗

P-DOR, an easy-to-use pipeline to reconstruct outbreaks using pathogen genomics

Bacterial Healthcare Associated Infections (HAIs) are a major threat worldwide, which can be counteracted by establishing effective infection control measures, guided by constant surveillance and timely epidemiological investigations. Genomics is crucial in modern epidemiology but lacks standard methods and user-friendly software, accessible to users without a strong bioinformatics proficiency. To overcome these issues we developed P-DOR, a novel tool for rapid bacterial outbreak characterization. P-DOR accepts genome assemblies as input, it automatically selects a background of publicly available genomes using k-mer distances and adds it to the analysis dataset before inferring a SNP-based phylogeny. Epidemiological clusters are identified considering the phylogenetic tree topology and SNP distances. By analyzing the SNP-distance distribution, the user can gauge the correct threshold. Patient metadata can be inputted as well, to provide a spatio-temporal representation of the outbreak. The entire pipeline is fast and scalable and can be also run on low-end computers. Availability and implementationP-DOR is implemented in Python3 and R and can be installed using conda environments. It is available from GitHub https://github.com/SteMIDIfactory/P-DOR under the GPL-3.0 license.

microbiology↗

Hypervariable-Locus Melting Typing (HLMT): a novel, fast and inexpensive sequencing-free approach to pathogen typing based on High Resolution Melting (HRM) analysis

ObjectivesSubspecies pathogen typing is a pivotal tool to detect the emergence of high-risk clones in hospital settings and to limit their spreading among patients. Unfortunately, the most used subspecies typing methods (i.e. Pulsed-field Gel Electrophoresis - PFGE, Multi-Locus Sequence Typing - MLST and Whole Genome Sequencing - WGS) are too expensive and time consuming to be suitable for real-time surveillance. Here we present Hypervariable-Locus Melting Typing (HLMT), a novel subspecies typing approach based on High Resolution Melting (HRM) analysis, which allows pathogen typing in a few hours and with [~]5 euros per sample. MethodsHLMT types the strains by clustering them using melting temperatures (HLMT-clustering) and/or by assigning them to Melting Types (MTs) on the basis of a reference dataset (HLMT-assignment). We applied HLMT (clustering and typing) to 134 Klebsiella pneumoniae strains collected during outbreaks or surveillance programs in four hospitals. Then, we compared HLMT typing results to PFGE, MLST and WGS. ResultsHLMT-clustering distinguishes most of the K. pneumoniae high-risk clones with a sensitivity comparable to PFGE and MLST. It also drawed surveillance epidemiological curves comparable to those obtained by MLST, PFGE and WGS typing. Furthermore, the results obtained by HLMT-assignment were coherent to MLST for 96% of the typed strains with a Jaccard index of 0.912. ConclusionsHLMT is a fast and scalable method for pathogen typing, suitable for real-time hospital microbiological surveillance. HLMT is also inexpensive and thus it is applicable to infection control programs in low-middle income countries.

microbiology↗

Repeatability and reproducibility of the wzi High Resolution Melting-based clustering analysis for Klebsiella pneumoniae typing

AimsHigh Resolution Melting (HRM) is a fast closed-tube method for nucleotide variant scanning applicable for bacterial species identification or molecular typing. Recently a novel HRM-based method for Klebsiella pneumoniae typing has been proposed: it consists of an HRM protocol designed on the capsular wzi gene and an HRM-based algorithm of strains clustering. In this study, we evaluated the repeatability and reproducibility of this method. Methods and ResultsWe performed HRM typing of a set of K. pneumoniae strains, on three different instruments and by two different operators. The results showed that operators do not affect measured melting temperatures while different instruments can. Despite this, we found that strains clustering analysis remains perfectly consistent performing the analysis using the MeltingPlot tool separately on the data from the three instruments. ConclusionsThe HRM protocol under study was highly repeatable and thus reliable for large studies, even when several operators are involved. Significance and Impact of the StudyOur results show that the wzi-HRM protocol for K. pneumoniae typing is suitable for multicenter studies, even if different instruments are used.

microbiology↗

Fast Klebsiella pneumoniae typing for outbreak reconstruction: an highly discriminatory HRM protocol on wzi capsular gene developed using EasyPrimer tool

In this work we present EasyPrimer, a user-friendly online tool developed to assist pan-PCR and High Resolution Melting (HRM) primer design. The tool finds the most suitable regions for primer design in a gene alignment and returns a clear graphical representation of their positions on the gene. EasyPrimer is particularly useful in difficult contexts, e.g. on gene alignments of hundreds of sequences and/or on highly variable genes. HRM analysis is an emerging method for fast and cost saving bacterial typing and an HRM scheme of six primer sets on five Multi-Locus Sequence Type (MLST) genes is already available for Klebsiella pneumoniae. We validated the tool designing a scheme of two HRM primer sets on the hypervariable gene wzi of Klebsiella pneumoniae and compared the two schemes. The wzi scheme resulted to have a discriminatory power comparable to the HRM MLST scheme, using only one third of primer sets. Then we successfully used the wzi HRM primer scheme to reconstruct a Klebsiella pneumoniae nosocomial outbreak in few hours. The use of hypervariable genes reduces the number of HRM primer sets required for bacterial typing allowing to perform cost saving, large-scale surveillance programs.

epidemiology↗