Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies

In the past few years, many studies investigated the anaerobic digestion microbiome by means of 16S rRNA amplicon sequencing. Results obtained from these studies were compared to each other without taking into consideration the followed procedure for amplicons preparation and data analysis. This negligence was mainly due to the lack of knowledge regarding the biases influencing specific steps of the microbiome investigation process. In the present study, the main technical aspects of the 16S rRNA analysis were checked giving special attention to the approach used for high throughput sequencing. More specifically, the microbial compositions of three laboratory scale biogas reactors were analyzed before and after addition of sodium oleate by sequencing the microbiome with three different approaches: 16S rRNA amplicon sequencing, shotgun DNA and shotgun RNA. This comparative analysis revealed that, in amplicon sequencing, abundance of some taxa (Euryarchaeota and Spirochaetes) was biased by the inefficiency of universal primers to hybridize all the templates. Reliability of the results obtained was also influenced by the number of hypervariable regions under investigation. Finally, amplicon sequencing and shotgun DNA underestimated the Methanoculleus genus, probably due to the low 16S rRNA gene copy number encoded in this taxon

Single cell transcriptome analysis using next generation sequencing.

The heterogeneity of tissues, especially in cancer research, is a central issue in transcriptome analysis. In recent years, research has primarily focused on the development of methods for single cell analysis. Single cell analysis aims at gaining (novel) insights into biological processes of healthy and diseased cells. Some of the challenges in transcriptome analysis concern low abundance of sample starting material, necessary sample amplification steps and subsequent analysis. In this study, two fundamentally different approaches to amplification were compared using next-generation sequencing analysis: I. exponential amplification using polymerase-chain-reaction (PCR) and II. linear amplification. For both approaches, protocols for single cell extraction, cell lysis, cDNA synthesis, cDNA amplification and preparation of next-generation sequencing libraries were developed. We could successfully show that transcriptome analysis of low numbers of cells is feasible with both exponential and linear amplification. Using exponential amplification, the highest amplification rates up to 106 were possible. The reproducibility of results is a strength of the linear amplification method. The analysis of next generation sequencing data in single cell samples showed detectable expression in at least 16.000 genes. The variance between samples results in a need to work with a greater amount of biological replicates. In summary it can be said that single cell transcriptome analysis with next generation sequencing is possible but improvements leading to a higher yield of transcriptome reads is required. In the near future by comparing single cancer cells with healthy ones for example, a basis for improved prognosis and diagnosis can be realised

Effects of propidium monoazide (PMA) treatment on mycobiome and bacteriome analysis of cystic fibrosis airways during exacerbation

Introduction and Purpose : Propidium monoazide (PMA)-pretreatment has increasingly been applied to remove the bias from dead or damaged cell artefacts, which could impact the microbiota analysis by high-throughput sequencing. Our study aimed to determine whether a PMA-pretreatment coupled with high-throughput sequencing analysis provides a different picture of the airway mycobiome and bacteriome. Results and Discussion : We compared deep-sequencing data of mycobiota and microbiota of 15 sputum samples from 5 cystic fibrosis (CF) patients with and without prior PMA-treatment of the DNA-extracts. PMA-pretreatment had no significant effect on the entire and abundant bacterial community (genera expressed as operational taxonomic units (OTUs) with a relative abundance greater than or equal to 1%), but caused a significant difference in the intermediate community (less than 1%) when analyzing the alpha biodiversity Simpson index (p = 0.03). Regarding PMA impact on the airway mycobiota evaluated for the first time here; no significant differences in alpha diversity indexes between PMA-treated and untreated samples were observed. Regarding beta diversity analysis, the intermediate communities also differed more dramatically than the total and abundant ones when studying both mycobiome and bacteriome. Our results showed that only the intermediate (or low abundance) population diversity is impacted by PMA-treatment, and therefore that abundant taxa are mostly viable during acute exacerbation in CF. Given such a cumbersome protocol (PMA-pretreatment coupled with high-throughput sequencing), we discuss its potential interest within the follow-up of CF patients. Further studies using PMA-pretreatment are warranted to improve our "omic" knowledge of the CF airways

Dermatophytes’ identification by Matrix-assisted laser desorption ionization-time of flight mass spectrometry. (MALDI-TOF MS) - the experience of a clinical laboratory

Objectives: Dermatophytes are a challenging group of fungi that infect the keratinized tissues. The taxonomy of these fungi has changed recently with the reclassification of some species and description of new ones. However, many clinical laboratories still base the identification of dermatophytes on their phenotype. Since dermatophytes are very pleomorphic, macro and micromorphology are often insufficient to reach a correct classification and may lead to misidentifications. The identification based on MALDI-TOF relies on the protein profile of the microorganism. Thus, this study aims to summarize our current laboratorial experience of dermatophyte identification using MALDI-TOF MS. Methods: From january to april 2018, 95 dermatophytes isolates, collected from human keratinized samples and also from quality control programs were characterized by phenotypic analysis, and by VITEK MS V3.2 bioMerieux. Before identification procedure, isolates were inoculated on Sabouraud Dextrose agar plates and incubated at 27°C during 5 to 10 days. Species were identified taking into account clinical features, as well as cultural, microscopic and physiological characteristics. Prior to MALDI-TOF MS analysis, the samples were pre-treated according to the manufacturer’s protocol for filamentous fungi. Molecular identification by sequencing of the internal transcribed spacer 1 (ITS1) was performed in 34 of those isolates Results: Through phenotypic analysis eight different species were identified (54 Trichophyton rubrum; 4 T.soudanense; 22 T.interdigitale; 1 T.mentagrophytes; 3 T.tonsurans; 7 Microsporum canis; 3 M.audouinii; 1 Microsporum spp.- (non canis or audouinii). MALDI-TOF analysis showed an identification agreement in 80 cases (84,2%) with a confidence level of 99,9%. Eight isolates showed divergent identification results: three T.rubrum were identified as T.violaceum, three T.soudanense were identified as T.rubrum, one T.mentagrophytes was identified as T.interdigitale and one T.tonsurans was identified as T.rubrum. In four cases MALDI-TOF analysis did not get a profile. The ITS sequencing analysis of discrepant results corroborated the MALDI-TOF identification in five of them. On the other hand, T.soudanense was only identified by phenotypic analysis since MALDI-TOF and ITS sequencing result was T.rubrum. MALDITOF identification of T.violaceum was not confirmed by ITS sequencing that identified T. rubrum instead, in accordance with the phenotypic identification. Conclusion: Correct identification of dermatophytes to species level requires sequencing of the ITS, LSU, and/or betatubulin regions. The implementation of this methodology in a clinical laboratory is expensive and time consuming. MALDI-TOF identification is a good option for dermatophytes’ identification performed in laboratory routine, since costs of consumables as well as time of sample preparation are lower than for PCR analysis and doesn’t require long training period as phenotypic identification does. In this study, however, both methods failed to identify some species variants like Trichophyton soudanense or T. violaceum. The combined use of both MALDI-TOF and phenotypic methods seems to be the better approach for dermatophytes’ identification since some species show significant phenotypic and clinical differences.info:eu-repo/semantics/publishedVersio

The ChIP-seq-defined networks of Bcl-3 gene binding support its required role in skeletal muscle atrophy

NF-kappaB transcriptional activation is required for skeletal muscle disuse atrophy. We are continuing to study how the activation of NF-kB regulates the genes that encode the protein products that cause atrophy. Using ChIP-sequencing we found that Bcl-3, an NF-kB transcriptional activator required for atrophy, binds to the promoters of a number of genes whose collective function describes two major aspects of muscle wasting. By means of bioinformatics analysis of ChIP-sequencing data we found Bcl-3 to be directing transcription networks of proteolysis and energy metabolism. The proteolytic arm of the Bcl-3 networks includes many E3 ligases associated with proteasomal protein degradation, including that of the N-end rule pathway. The metabolic arm appears to be involved in organizing the change from oxidative phosphorylation to glycolysis in atrophying muscle. For one gene, MuRF1, ChIP-sequencing data identified the location of Bcl-3 and p50 binding in the promoter region which directed the creation of deletant and base-substitution mutations of MuRF1 promoter constructs to determine the effect on gene transcription. The results provide the first direct confirmation that the NF-kB binding site is involved in the muscle unloading regulation of MuRF1. Finally, we have combined the ChIP-sequencing results with gene expression microarray data from unloaded muscle to map several direct targets of Bcl-3 that are transcription factors whose own targets describe a set of indirect targets for NF-kB in atrophy. ChIP-sequencing provides the first molecular explanation for the finding that Bcl3 knockout mice are resistant to disuse muscle atrophy. Mapping the transcriptional regulation of muscle atrophy requires an unbiased analysis of the whole genome, which we show is now possible with ChIP-sequencing.R01 AR041705 - NIAMS NIH HHS; R01 AR060217 - NIAMS NIH HHS; AR041705 - NIAMS NIH HHS; AR060217 - NIAMS NIH HH

Rapid detection of copy number variations and point mutations in BRCA1/2 genes using a single workflow by ion semiconductor sequencing pipeline

Molecular analysis of BRCA1 (MIM# 604370) and BRCA2 (MIM #600185) genes is essential for familial breast and ovarian cancer prevention and treatment. An efficient, rapid, cost-effective accurate strategy for the detection of pathogenic variants is crucial. Mutations detection of BRCA1/2 genes includes screening for single nucleotide variants (SNVs), small insertions or deletions (indels), and Copy Number Variations (CNVs). Sanger sequencing is unable to identify CNVs and therefore Multiplex Ligation Probe amplification (MLPA) or Multiplex Amplicon Quantification (MAQ) is used to complete the BRCA1/2 genes analysis. The rapid evolution of Next Generation Sequencing (NGS) technologies allows the search for point mutations and CNVs with a single platform and workflow. In this study we test the possibilities of NGS technology to simultaneously detect point mutations and CNVs in BRCA1/2 genes, using the OncomineTM BRCA Research Assay on Personal Genome Machine (PGM) Platform with Ion Reporter Software for sequencing data analysis (Thermo Fisher Scientific). Comparison between the NGS-CNVs, MLPA and MAQ results shows how the NGS approach is the most complete and fast method for the simultaneous detection of all BRCA mutations, avoiding the usual time consuming multistep approach in the routine diagnostic testing of hereditary breast and ovarian cancers