Uncovering the Counterfeit: A study of whiskey authenticity through volatile organic compound fingerprinting, aroma and color sensory analysis.

This study presents a method employing gas chromatography coupled with mass spectrometry and headspace solid-phase microextraction (HS-SPME-GC-MS), supplemented with chemometrics (Soft independent modelling of class analogies - SIMCA), to analyze volatile organic compound (VOCs) profiles in suspect whiskey samples. Furthermore, a sensory analysis of aroma and color was conducted with a panel of 52 non-trained volunteers to evaluate their ability to discriminate and preference for counterfeit whiskeys. The HS-SPME-GC-MS method successfully distinguished 41 seized samples from authentic beverages. Interestingly, sensory analysis revealed that panelists could differentiate between counterfeit and authentic samples with a reference standard but did not consistently show a preference for aroma. In some cases, there was even a preference for the color of counterfeit whiskeys. The findings suggest that sensorial tests alone may not effectively distinguish counterfeit from authentic whiskeys, especially for non-expert consumers, highlighting the need for analytical instrumentation methods in fraud detection.

Tonsils are major sites of persistence of SARS-CoV-2 in children.

In the present study, we show that SARS-CoV-2 can infect palatine tonsils, adenoids, and secretions in children without symptoms of COVID-19, with no history of recent upper airway infection. We studied 48 children undergoing tonsillectomy due to snoring/OSA or recurrent tonsillitis between October 2020 and September 2021. Nasal cytobrushes, nasal washes, and tonsillar tissue fragments obtained at surgery were tested by RT-qPCR, immunohistochemistry (IHC), flow cytometry, and neutralization assay. We detected the presence of SARS-CoV-2 in at least one specimen tested in 27% of patients. IHC revealed the presence of the viral nucleoprotein in epithelial surface and in lymphoid cells in both extrafollicular and follicular regions, in adenoids and palatine tonsils. Also, IHC for the SARS-CoV-2 non-structural protein NSP-16 indicated the presence of viral replication in 53.8% of the SARS-CoV-2-infected tissues. Flow cytometry showed that CD20+ B lymphocytes were the most infected phenotypes, followed by CD4+ lymphocytes and CD123 dendritic cells, CD8+ T lymphocytes, and CD14+ macrophages. Additionally, IF indicated that infected tonsillar tissues had increased expression of ACE2 and TMPRSS2. NGS sequencing demonstrated the presence of different SARS-CoV-2 variants in tonsils from different tissues. SARS-CoV-2 antigen detection was not restricted to tonsils but was also detected in nasal cells from the olfactory region. Palatine tonsils and adenoids are sites of prolonged RNA presence by SARS-CoV-2 in children, even without COVID-19 symptoms. IMPORTANCE This study shows that SRS-CoV-2 of different lineages can infect tonsils and adenoids in one quarter of children undergoing tonsillectomy. These findings bring advancement to the area of SARS-CoV-2 pathogenesis, by showing that tonsils may be sites of prolonged infection, even without evidence of recent COVID-19 symptoms. SARS-CoV-2 infection of B and T lymphocytes, macrophages, and dendritic cells may interfere with the mounting of immune responses in these secondary lymphoid organs. Moreover, the shedding of SARS-CoV-2 RNA in respiratory secretions from silently infected children raises concern about possible diagnostic confusion in the presence of symptoms of acute respiratory infections caused by other etiologies.

Mining novel cis-regulatory elements from the emergent host Rhodosporidium toruloides using transcriptomic data.

The demand for robust microbial cell factories that produce valuable biomaterials while resisting stresses imposed by current bioprocesses is rapidly growing. Rhodosporidium toruloides is an emerging host that presents desirable features for bioproduction, since it can grow in a wide range of substrates and tolerate a variety of toxic compounds. To explore R. toruloides suitability for application as a cell factory in biorefineries, we sought to understand the transcriptional responses of this yeast when growing under experimental settings that simulated those used in biofuels-related industries. Thus, we performed RNA sequencing of the oleaginous, carotenogenic yeast in different contexts. The first ones were stress-related: two conditions of high temperature (37 and 42°C) and two ethanol concentrations (2 and 4%), while the other used the inexpensive and abundant sugarcane juice as substrate. Differential expression and functional analysis were implemented using transcriptomic data to select differentially expressed genes and enriched pathways from each set-up. A reproducible bioinformatics workflow was developed for mining new regulatory elements. We then predicted, for the first time in this yeast, binding motifs for several transcription factors, including HAC1, ARG80, RPN4, ADR1, and DAL81. Most putative transcription factors uncovered here were involved in stress responses and found in the yeast genome. Our method for motif discovery provides a new realm of possibilities in studying gene regulatory networks, not only for the emerging host R. toruloides, but for other organisms of biotechnological importance.

Benchmarking Bacterial Promoter Prediction Tools: Potentialities and Limitations.

The promoter region is a key element required for the production of RNA in bacteria. While new high-throughput technology allows massively parallel mapping of promoter elements, we still mainly rely on bioinformatics tools to predict such elements in bacterial genomes. Additionally, despite many different prediction tools having become popular to identify bacterial promoters, no systematic comparison of such tools has been performed. Here, we performed a systematic comparison between several widely used promoter prediction tools (BPROM, bTSSfinder, BacPP, CNNProm, IBBP, Virtual Footprint, iPro70-FMWin, 70ProPred, iPromoter-2L, and MULTiPly) using well-defined sequence data sets and standardized metrics to determine how well those tools performed related to each other. For this, we used data sets of experimentally validated promoters from Escherichia coli and a control data set composed of randomly generated sequences with similar nucleotide distributions. We compared the performance of the tools using metrics such as specificity, sensitivity, accuracy, and Matthews correlation coefficient (MCC). We show that the widely used BPROM presented the worse performance among the compared tools, while four tools (CNNProm, iPro70-FMWin, 70ProPred, and iPromoter-2L) offered high predictive power. Of these tools, iPro70-FMWin exhibited the best results for most of the metrics used. We present here some potentials and limitations of available tools, and we hope that future work can build upon our effort to systematically characterize this useful class of bioinformatics tools.IMPORTANCE The correct mapping of promoter elements is a crucial step in microbial genomics. Also, when combining new DNA elements into synthetic sequences, predicting the potential generation of new promoter sequences is critical. Over the last years, many bioinformatics tools have been created to allow users to predict promoter elements in a sequence or genome of interest. Here, we assess the predictive power of some of the main prediction tools available using well-defined promoter data sets. Using Escherichia coli as a model organism, we demonstrated that while some tools are biased toward AT-rich sequences, others are very efficient in identifying real promoters with low false-negative rates. We hope the potentials and limitations presented here will help the microbiology community to choose promoter prediction tools among many available alternatives.

A Novel Cys2His2 Zinc Finger Homolog of AZF1 Modulates Holocellulase Expression in Trichoderma reesei.

Filamentous fungi are remarkable producers of enzymes dedicated to the degradation of sugar polymers found in the plant cell wall. Here, we integrated transcriptomic data to identify novel transcription factors (TFs) related to the control of gene expression of lignocellulosic hydrolases in Trichoderma reesei and Aspergillus nidulans Using various sets of differentially expressed genes, we identified some putative cis-regulatory elements that were related to known binding sites for Saccharomyces cerevisiae TFs. Comparative genomics allowed the identification of six transcriptional factors in filamentous fungi that have corresponding S. cerevisiae homologs. Additionally, a knockout strain of T. reesei lacking one of these TFs (S. cerevisiae AZF1 homolog) displayed strong reductions in the levels of expression of several cellulase-encoding genes in response to both Avicel and sugarcane bagasse, revealing a new player in the complex regulatory network operating in filamentous fungi during plant biomass degradation. Finally, RNA sequencing (RNA-seq) analysis showed the scope of the AZF1 homologue in regulating a number of processes in T. reesei, and chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) provided evidence for the direct interaction of this TF in the promoter regions of cel7a, cel45a, and swo Therefore, we identified here a novel TF which plays a positive effect in the expression of cellulase-encoding genes in T. reesei IMPORTANCE In this work, we used a systems biology approach to map new regulatory interactions in Trichoderma reesei controlling the expression of genes encoding cellulase and hemicellulase. By integrating transcriptomics related to complex biomass degradation, we were able to identify a novel transcriptional regulator which is able to activate the expression of these genes in response to two different cellulose sources. In vivo experimental validation confirmed the role of this new regulator in several other processes related to carbon source utilization and nutrient transport. Therefore, this work revealed novel forms of regulatory interaction in this model system for plant biomass deconstruction and also represented a new approach that could be easy applied to other organisms.