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Appl. Microbiol., Volume 4, Issue 2 (June 2024) – 28 articles

Cover Story (view full-size image): Applied Microbiology (ISSN 2673-8007) provides an advanced forum for studies related to the application of microorganisms, with a strong emphasis on biotechnology, environment, medicine, and food. It publishes original scientific research articles, comprehensive reviews, comments, commentaries, perspectives, etc. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the maximum length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files and software regarding the full details of the calculation or experimental procedure, if unable to be published in a normal way, can be deposited as supplementary electronic material.
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14 pages, 883 KiB  
Review
Changes in the Skin Microbiome Following Dermatological Procedures: A Scoping Review
by Jeremy R. Ellis, Eron J. Powell, Luke M. Tomasovic, Rachel L. Marcheskie, Vishruth Girish, Anmol Warman and Darshan Sivaloganathan
Appl. Microbiol. 2024, 4(2), 972-985; https://doi.org/10.3390/applmicrobiol4020066 - 18 Jun 2024
Viewed by 667
Abstract
The skin microbiome consists of bacteria, fungi, viruses, and mites, which play a crucial role in maintaining skin health and immune function. Imbalances in this microbial community, known as dysbiosis, are implicated in various dermatological conditions. While skincare products are known to influence [...] Read more.
The skin microbiome consists of bacteria, fungi, viruses, and mites, which play a crucial role in maintaining skin health and immune function. Imbalances in this microbial community, known as dysbiosis, are implicated in various dermatological conditions. While skincare products are known to influence the skin microbiome, the effects of dermatological procedures have not been extensively studied. Here, we perform a scoping review to outline the studies investigating the impacts of dermatological interventions on the skin microbiome. Phototherapy emerged as the most studied intervention, encompassing UV phototherapy, light therapy, laser therapy, and photodynamic therapy. Chemical interventions, such as chemical peels, micropigmentation, and debridement, have comparatively limited studies describing their impacts on the skin microbiome. To date, no studies have been done on a wide variety of common dermatological procedures such as cryotherapy, skin grafts, and dermabrasion, which may have stronger likelihoods of affecting the skin microbiome. This underscores the need for further research on the influences of dermatological procedures, especially chemical and physical interventions, on the skin microbiome. More comprehensive pre-clinical and clinical studies are essential not only for understanding the long-term consequences of these procedures, but also for optimizing patient outcomes in dermatological care. Full article
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<p>Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) flow chart of the study selection algorithm.</p>
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13 pages, 1679 KiB  
Article
Valorisation of Spent Yeast Fermentation Media through Compositional-Analysis-Directed Supplementation
by Laura Murphy, Ciara D. Lynch and David J. O’Connell
Appl. Microbiol. 2024, 4(2), 959-971; https://doi.org/10.3390/applmicrobiol4020065 - 12 Jun 2024
Viewed by 696
Abstract
Spent fermentation media from bioprocessing represent a significant waste stream, and interest in recycling them as part of the developing circular bioeconomy is growing. The potential to reuse yeast spent culture media (YSM) to feed secondary bacterial fermentations producing recombinant protein was investigated [...] Read more.
Spent fermentation media from bioprocessing represent a significant waste stream, and interest in recycling them as part of the developing circular bioeconomy is growing. The potential to reuse yeast spent culture media (YSM) to feed secondary bacterial fermentations producing recombinant protein was investigated in this study. Elemental and amino acid compositional analysis using inductively coupled plasma mass spectrometry (ICP-MS) and LC-MS/MS identified significant differences in the concentrations of 6 elements and 18/20 amino acids in YSM compared with rich microbiological media (LB). Restoration of levels of magnesium and sodium through addition of their salts and amino acids from tryptone supplementation led to the expression of equivalent titres of recombinant proteins by E. coli (0.275 g/L), compared to that in LB media (0.296 g/L) and BMMY media (0.294 g/L) in shake flask culture. When this supplementation strategy was employed in a bioreactor system, we observed a significant increase in recombinant protein titre using the supplemented YSM (2.29 (±0.02) g/L) over that produced using LB media (1.29 (±0.09) g/L). This study demonstrates through highly sensitive compositional analysis and identification of supplementation strategies the potential to valorise spent media from yeast fermentations that underpin industrial processes of significant scale, creating a circular approach to waste stream management. Full article
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<p>Growth curves of <span class="html-italic">E</span>. <span class="html-italic">coli</span> BL21 DE3 in culture media. Cultures grown in triplicate, LB (solid circles), BMMY (solid squares), YSM (solid triangles), YSM + magnesium (inverted triangles), YSM + sodium (diamonds), YSM + magnesium + sodium (stars), YSM + tryptone (open circles), YSM + magnesium and tryptone (open squares). * Tryptone amino acid donor. Error bars are representative of the standard deviation of triplicate cultures for each condition.</p>
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<p>Titres of recombinant mCherry-EF2 protein following purification of triplicate cultures of each media condition. 1. LB, 2. BMMY, 3. YSM, 4. YSM + magnesium, 5. YSM + sodium, 6. YSM + magnesium and sodium, 7. YSM + tryptone, 8. YSM + magnesium and tryptone. Significance is determined using a two-way ANOVA with Tukey’s post-analysis test, where the mean of each sample is compared. <span class="html-italic">p</span>-values are represented as follows: <span class="html-italic">p</span> ≥ 0.05, ns (not significant) ** <span class="html-italic">p</span> ≤ 0.01; **** <span class="html-italic">p</span> ≤ 0.0001.</p>
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<p>Recombinant protein expression in bioreactor fermentation with optimised supplementation. (<b>A</b>) Growth curves of <span class="html-italic">E. coli</span> cultures fed in supplemented media and in LB. (<b>B</b>) Titres of mCherry-EF2 expressed in each media condition, ns (not significant); ** <span class="html-italic">p</span> ≤ 0.01; *** <span class="html-italic">p</span> ≤ 0.001. (<b>C</b>) Calculations of percentage yield and productivity of each culture in terms of cell dry weight at the end of fermentation.</p>
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<p>Bioreactor dissolved oxygen over time and HPLC analysis of carbon sources. (<b>A</b>) YSM + magnesium condition and (<b>B</b>) YSM + magnesium + tryptone. Bioreactor timelapse of dissolved oxygen (DO in percentage, orange line) and carbon source consumption measured by HPLC (glycerol and glucose, green and blue, respectively). IPTG induction of protein expression was carried out along with addition of 2% glycerol once cultures reached OD<sub>600 nm</sub> of 10, marked with a dashed line, from which point expression was carried out over 18.5 further hours.</p>
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11 pages, 1567 KiB  
Article
Predicting Microbiome Growth Dynamics under Environmental Perturbations
by George Sun and Yi-Hui Zhou
Appl. Microbiol. 2024, 4(2), 948-958; https://doi.org/10.3390/applmicrobiol4020064 - 10 Jun 2024
Viewed by 545
Abstract
MicroGrowthPredictor is a model that leverages Long Short-Term Memory (LSTM) networks to predict dynamic changes in microbiome growth in response to varying environmental perturbations. In this article, we present the innovative capabilities of MicroGrowthPredictor, which include the integration of LSTM modeling with a [...] Read more.
MicroGrowthPredictor is a model that leverages Long Short-Term Memory (LSTM) networks to predict dynamic changes in microbiome growth in response to varying environmental perturbations. In this article, we present the innovative capabilities of MicroGrowthPredictor, which include the integration of LSTM modeling with a novel confidence interval estimation technique. The LSTM network captures the complex temporal dynamics of microbiome systems, while the novel confidence intervals provide a robust measure of prediction uncertainty. We include two examples—one illustrating the human gut microbiota composition and diversity due to recurrent antibiotic treatment and the other demonstrating the application of MicroGrowthPredictor on an artificial gut dataset. The results demonstrate the enhanced accuracy and reliability of the LSTM-based predictions facilitated by MicroGrowthPredictor. The inclusion of specific metrics, such as the mean square error, validates the model’s predictive performance. Our model holds immense potential for applications in environmental sciences, healthcare, and biotechnology, fostering advancements in microbiome research and analysis. Moreover, it is noteworthy that MicroGrowthPredictor is applicable to real data with small sample sizes and temporal observations under environmental perturbations, thus ensuring its practical utility across various domains. Full article
(This article belongs to the Special Issue Microbiome in Ecosystem 3.0)
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<p>Long Short-Term Memory (LSTM) architecture: (<b>A</b>) A zoom-in on an LSTM cell, showing its three gates: the input gate, forget gate, and output gate. (<b>B</b>) The flow of the input and output data in an LSTM network from time step <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>−</mo> <mn>1</mn> </mrow> </semantics></math> to time step <span class="html-italic">t</span>.</p>
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<p>Contour plot of the mean square error over <span class="html-italic">p</span> and <span class="html-italic">t</span> for Subject D EU766613: The darker the contour plot is, the smaller the error is. We can identify the best combination of dropout probability and sequence length.</p>
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<p>Contour plot of the mean square error over <math display="inline"><semantics> <msub> <mi>n</mi> <mrow> <mi>f</mi> <mi>c</mi> </mrow> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>n</mi> <mi>h</mi> </msub> </semantics></math> for Subject D EU766613: The x-axis represents the number of hidden states in the single LSTM layer, and the y-axis represents the number of nodes in the fully connected layer. With different combinations, the mean square value changes. The contour plot basically gives us a direct impression of the smallest MSE, which is represented by the darkest area on the figure.</p>
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<p>Trajectories of relative abundance of Bacteroid EU766613 for subject D. The chosen parameters are <math display="inline"><semantics> <mrow> <mi>p</mi> <mo>=</mo> <mn>0.05</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>6</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <msub> <mi>n</mi> <mi>h</mi> </msub> <mo>=</mo> <mn>256</mn> </mrow> </semantics></math>, and <math display="inline"><semantics> <mrow> <msub> <mi>n</mi> <mi>f</mi> </msub> <mo>=</mo> <mn>256</mn> </mrow> </semantics></math>. The blue vertical bands represent the two antibiotic treatment periods, and the red dotted line splits the data into training and testing.</p>
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<p>Trajectories of the relative abundance of Rikenellaceae in Vessels 1 and 2. The entire trajectory of Vessel 2 is predicted by the MicroGrowthPredictor model trained on data from Vessel 1. Confidence intervals are provided for the testing data of Vessel 2. In this experiment, the optimal dropout probability <span class="html-italic">p</span> of 0.25 was used. The model utilized the preceding five time points to identify four parameters and achieve optimal predictions. The fully connected layer was equipped with 256 nodes, and the LSTM layer comprised 128 nodes. The model underwent training for 800 epochs.</p>
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14 pages, 2841 KiB  
Article
Evaluation of Solid-State Fermentation Conditions from Pineapple Peel Waste for Release of Bioactive Compounds by Aspergillus niger spp.
by A. Danitza Casas-Rodríguez, Juan A. Ascacio-Valdés, Miriam Desirée Dávila-Medina, Miguel A. Medina-Morales, Liliana Londoño-Hernández and Leonardo Sepúlveda
Appl. Microbiol. 2024, 4(2), 934-947; https://doi.org/10.3390/applmicrobiol4020063 - 8 Jun 2024
Viewed by 843
Abstract
Currently, agroindustrial waste can be used to obtain bioactive compounds. The solid-state fermentation is an alternative for the valorization of these waste and to be able to release bioactive compounds that may be of interest to different industrial sectors. The aim of this [...] Read more.
Currently, agroindustrial waste can be used to obtain bioactive compounds. The solid-state fermentation is an alternative for the valorization of these waste and to be able to release bioactive compounds that may be of interest to different industrial sectors. The aim of this study was to evaluate solid-state fermentation conditions using pineapple peel waste as the substrate with Aspergillus niger spp., to release bioactive compounds using a Plackett–Burman exploratory design. Temperature, humidity, inoculum, NaNO3, MgSO4, KCl, and KH2PO4 conditions in the fermentation process were evaluated. The antioxidant capacity was determined, and the main compounds of the fermentation extracts were identified. The results revealed that the Aspergillus niger HT3 strain reached a hydrolyzable tannin release of 10.00 mg/g, While Aspergillus niger Aa20 reached a condensed tannin release of 82.59 mg/g. The KH2PO4 affects the release of condensed tannins with A. niger Aa20, and MgSO4 affects the release of hydrolyzable tannins with A. niger HT3. In addition, a positive antioxidant activity was demonstrated for the DPPH, ABTS, and FRAP technique. The main compounds in the fermented pineapple peel were 3-feruloylquinic acid, caffeic acid, lariciresinol, and 3-hydroxyphloretin 2′-O-xylosyl-glucoside, among others. The solid-state fermentation process is a biotechnological alternative for the release of bioactive compounds. Full article
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<p>Radial growth for the evaluation of fungal strains with invasive capacity on pineapple peel waste.</p>
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<p>Kinetics of quantification of (<b>A</b>) HT and (<b>B</b>) CT of <span class="html-italic">A. niger</span> Aa20 and <span class="html-italic">A. niger</span> HT3.</p>
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<p>Concentration of polyphenols found in the fermentation process: (<b>A</b>) HT concentrations of <span class="html-italic">A. niger</span> HT3 treatments; and (<b>B</b>) CT concentrations of <span class="html-italic">A. niger</span> Aa20 treatments.</p>
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<p>Pareto chart of the variables that affect the fermentation process: (<b>A</b>) HT for <span class="html-italic">A. niger</span> HT3; and (<b>B</b>) CT for <span class="html-italic">A. niger</span> Aa20.</p>
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<p>Antioxidant activity of pineapple peel waste of fermentation extracts for DPPH.</p>
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<p>Antioxidant activity of pineapple peel waste of fermentation extracts for ABTS.</p>
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<p>Antioxidant activity of pineapple peel waste of fermentation extracts for FRAP.</p>
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16 pages, 2549 KiB  
Article
16S rRNA Analysis of Electrogenic Bacterial Communities from Soil Microbial Fuel Cells
by Ana Rumora, Liliana Hopkins, Kayla Yim, Melissa F. Baykus, Luisa Martinez and Luis Jimenez
Appl. Microbiol. 2024, 4(2), 918-933; https://doi.org/10.3390/applmicrobiol4020062 - 5 Jun 2024
Viewed by 487
Abstract
Electrogenic bacteria present in bioelectrical devices such as soil microbial fuel cells (SMFCs) are powered by the oxidation of organic and inorganic compounds due to microbial activity. Fourteen soils randomly selected from Bergen Community College or areas nearby, located in the state of [...] Read more.
Electrogenic bacteria present in bioelectrical devices such as soil microbial fuel cells (SMFCs) are powered by the oxidation of organic and inorganic compounds due to microbial activity. Fourteen soils randomly selected from Bergen Community College or areas nearby, located in the state of New Jersey, USA, were used to screen for the presence of electrogenic bacteria. SMFCs were incubated at 35–37 °C. Of the 14 samples, 11 generated electricity and enriched electrogenic bacteria. The average optimal electricity production by the top 3 SMFCs was 152 microwatts. The highest electrical production was produced by SMFC-B1C and SMFC-B1B, with 162 and 152 microwatts, respectively. Microbial DNA was extracted from the biofilm grown on the anodes, followed by PCR analysis of the 16S rRNA V3–V4 region. Next-generation sequencing was performed to determine the structure and diversity of the electrogenic microbial community. The top 3 MFCs with the highest electricity production showed a bacterial community predominantly composed of bacteria belonging to the Bacillota and Pseudomonadota phyla with a significant presence of Euryarcheota members of methanogenic archaea. SMFC-B1C showed a more diverse electrogenic community, followed by SMFC-B1B and SMFC-B1. When analyzing the top 10 bacteria in the SMFCs, 67 percent belonged to the class Clostridia, indicating that anaerobic conditions were required to enrich electrogenic bacterial numbers and optimize electrical production. The ongoing optimization of SMFCs will provide better production of electricity and continuous enhancement of microbial activity to sustain longer operational times and higher levels of electrogenesis. The characterization of electrogenic microbial communities will provide valuable information to understand the contribution of different populations to the production of electricity in bioelectrical devices. Full article
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<p>Soil microbial fuel cells.</p>
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<p>Electricity (microwatts) generation over days by SMFCs.</p>
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<p>Alpha diversity of SMFCs. (number of species per sample).</p>
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<p>Relative abundances of bacteria and archaea phyla in SMFCs.</p>
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<p>Relative abundance of archaea in SMFCs.</p>
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<p>Gel electrophoresis analysis of GH48 genes in SMFCs. Lane 1: molecular-weight markers. Lane 2: SFMC-B1. Lane 3: SMFC-B1B. Lane 4: SMFC-B1C.</p>
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24 pages, 634 KiB  
Review
The Industrial Fermentation Process and Clostridium Species Used to Produce Biobutanol
by David T. Jones
Appl. Microbiol. 2024, 4(2), 894-917; https://doi.org/10.3390/applmicrobiol4020061 - 31 May 2024
Viewed by 356
Abstract
The fermentation route for producing biobutanol from renewable plant biomass was used extensively during the last century. The key factors affecting performance in the standard batch industrial fermentation process are highlighted. Four species of Clostridium were utilized for the industrial production of solvents, [...] Read more.
The fermentation route for producing biobutanol from renewable plant biomass was used extensively during the last century. The key factors affecting performance in the standard batch industrial fermentation process are highlighted. Four species of Clostridium were utilized for the industrial production of solvents, and although they share many features in common, they also exhibit significant differences. The salient features of the existing industrial species and strains are reviewed. These include their suitability for the type of process and fermentation substrate used. The strains are also assessed with respect to their potential for future applications. Full article
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<p>Timelines for the periods that the industrial fermentation process was in operation in different countries/regions. The dark blue bars indicate the year that the fermentation process began and terminated. The lighter blue bars indicate that the actual year that the fermentation process either began or was terminated is not known.</p>
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19 pages, 1725 KiB  
Article
Trichoderma: Population Structure and Genetic Diversity of Species with High Potential for Biocontrol and Biofertilizer Applications
by Adnan Ismaiel, Dilip K. Lakshman, Prashant P. Jambhulkar and Daniel P. Roberts
Appl. Microbiol. 2024, 4(2), 875-893; https://doi.org/10.3390/applmicrobiol4020060 - 27 May 2024
Viewed by 443
Abstract
Certain Trichoderma isolates provide biofertilizer, biocontrol, and other plant-beneficial activities while inhabiting the soil or internal plant tissue, and their use in agricultural systems can contribute to sustainable food production. It is thought that colonization of soil or internal plant tissue is fundamental [...] Read more.
Certain Trichoderma isolates provide biofertilizer, biocontrol, and other plant-beneficial activities while inhabiting the soil or internal plant tissue, and their use in agricultural systems can contribute to sustainable food production. It is thought that colonization of soil or internal plant tissue is fundamental for biocontrol and biofertilizer applications. Our collective analyses of prior surveys, where the tef1α sequence was almost exclusively used to identify Trichoderma species, showed that isolates from the Harzianum complex clade, the T. asperellum/T. asperelloides group, T. virens, T. hamatum, and T. atroviride were prevalent in soil and/or as endophytes. Population structure and genetic diversity based on the genetic markers tef1α, rpb2, and ITS were investigated, and new lineages with statistical bootstrap support within T. atroviride, T. asperellum, T. hamatum, and T. virens populations were found. The nearest relatives of some of these species were also revealed. Choosing isolates from among more than 500 known Trichoderma species for use in non-targeted evaluation screens for biocontrol or biofertilizer applications is time-consuming and expensive. Preferentially selecting isolates from T. atroviride, T. asperellum/T. asperelloides, T. hamatum, the T. harzianum complex clade, T. virens, and possibly nearest relatives may speed the identification of candidates for commercialization due to the demonstrated ability of these species to successfully inhabit the soil and internal plant tissue. To our knowledge, this is the first report where dominant soil and endophytic Trichoderma species were identified from past survey data and population structure and genetic diversity analyses conducted. Full article
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<p>Phylogenetic tree revealing the genetic diversity of the <span class="html-italic">T. atroviride</span> population based on the DNA sequences of <span class="html-italic">tef1α</span>, <span class="html-italic">rpb2</span>, and ITS. Sequences are identified by <span class="html-italic">tef1α</span> GenBank accession number followed by the country of isolation. The scale bar indicates the number of nucleotide changes. Numbers on the branches represent bootstrap values greater than 70%. The type species and bootstrap-supported clades are highlighted in colors.</p>
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<p>Phylogenetic tree revealing the diversity of the <span class="html-italic">T. asperellum</span> population based on the DNA sequences of <span class="html-italic">tef1α</span>, <span class="html-italic">rpb2</span>, and ITS. The tree was generated using parsimony in PAUP. The numbers above the branches are bootstrap values obtained with 1000 bootstrap replicates. Sequences are identified by <span class="html-italic">tef1α</span> GenBank accession number followed by the country of isolation; C1 and C2 refer to lineages with bootstrap values above 70%. The scale bar indicates the number of nucleotide changes. The tree is rooted to the type species of <span class="html-italic">T. asperelloides</span>. The type species and bootstrap-supported clades are highlighted in colors.</p>
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<p>Phylogenetic tree revealing the genetic diversity of the <span class="html-italic">T. asperelloides</span> population based on the DNA sequences of <span class="html-italic">tef1α</span>, <span class="html-italic">rpb2</span>, and ITS. The tree was produced using parsimony in PAUP. The numbers above the branches are bootstrap values obtained with 1000 bootstraps. Sequences are identified by GenBank accession numbers followed by the country of isolation; C1 refers to lineages with bootstrap support or geographic significance. The tree was rooted to the <span class="html-italic">T. yunnanense</span> type species from China. The type species and bootstrap-supported clades are highlighted in colors. The scale bar indicates the number of nucleotide changes.</p>
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<p>Phylogenetic tree revealing the genetic diversity of the <span class="html-italic">T. hamatum</span> population based on the DNA sequences of <span class="html-italic">tef1α</span>, <span class="html-italic">rpb2</span>, and ITS. The tree was produced using parsimony in PAUP. The numbers above the branches are bootstrap values obtained with 1000 bootstrap replicates. Tree leaves are marked by GenBank accession number followed by the country of isolation. The tree is rooted to <span class="html-italic">T. pubescens</span> type species. C1–C4 are lineages with bootstrap support of 70% and greater and are highlighted in colors. The scale bar indicates the number of nucleotide changes.</p>
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<p>One of the most parsimonious trees obtained via PAUP based on sequences of <span class="html-italic">tef1α</span>, <span class="html-italic">rpb2</span>, and ITS resolving the relationship of <span class="html-italic">Trichoderma</span> species within the Harzianum complex clade. Tree leaves are labeled with tef1α GenBank accession numbers for <span class="html-italic">Trichoderma</span> species. Numbers above the branches indicate bootstrap support of 70 or greater; <sup>E</sup> at the end of the accession number indicates that the strain was isolated as an endophyte; <sup>T</sup> at the end of the accession number indicates a type species. Clades are marked with vertical lines, and numbers 1–14 represent identified species. The scale bar indicates the number of nucleotide changes. Lineages marked with vertical lines (L1–L5) represent unidentified lineages. The color highlights represent the two main clades. The tree was rooted to <span class="html-italic">T. pleurotum</span> and <span class="html-italic">T. pleuroticola</span>.</p>
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<p>Phylogenetic tree revealing the genetic diversity of the <span class="html-italic">T. virens</span> population based on the DNA sequences of tef1α, rpb2, and ITS. The tree was produced using parsimony in PAUP. The numbers above the branches are values obtained with 1000 bootstrap replicates. Sequences are identified by tef1α GenBank accession numbers followed by the country of origin; C1–C7 refer to lineages with bootstrap support or geographic significance. The type species and bootstrap-supported clades are highlighted in colors. The tree is rooted to the <span class="html-italic">T. crassum</span> type species. The scale bar indicates the number of nucleotide changes.</p>
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<p>One of the most parsimonious trees obtained via PAUP based on DNA sequence of <span class="html-italic">tef1α</span>, <span class="html-italic">rpb2</span>, and ITS showing the nearest relatives to the <span class="html-italic">Trichoderma</span> species <span class="html-italic">T. atroviride</span>, <span class="html-italic">T. asperellum</span>, <span class="html-italic">T. asperelloides</span>, and <span class="html-italic">T. hamatum</span>. Sequences are identified by GenBank accession number for <span class="html-italic">tef1α</span> followed by species names and the country of origin. Clades C1–C4 are marked by vertical lines. Numbers above the branches represent bootstrap support values of 70 and greater from 1000 replicates. <sup>T</sup> at the end of leaf names refers to type species. The tree is rooted to <span class="html-italic">T. evansii</span>. The type species and bootstrap-supported clades are highlighted in colors. The scale bar indicates the number of nucleotide changes.</p>
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19 pages, 3445 KiB  
Article
The Detection of Propionate Utilization by Bacteria Isolated from a Plastic Recycling Site
by Shuyan Wu, Pornchanok Subharat, Faith Palevich, John Mills and Gale Brightwell
Appl. Microbiol. 2024, 4(2), 856-874; https://doi.org/10.3390/applmicrobiol4020059 - 23 May 2024
Viewed by 644
Abstract
(1) The study aims to utilize a reported approach for culturing mesophilic bacteria from a plastic waste environment; (2) The work revived mesophilic microbial population from an aged PET recycling site using a culture-based approach, and determined the purified isolates in genus level [...] Read more.
(1) The study aims to utilize a reported approach for culturing mesophilic bacteria from a plastic waste environment; (2) The work revived mesophilic microbial population from an aged PET recycling site using a culture-based approach, and determined the purified isolates in genus level in 16S identification; (3) A total of 59 bacterial isolates were obtained, in which microbial species, including Pseudomonas spp, Rhodococcus spp, and Burkholderia spp were identified as abundance. It was observed that the surviving microbes favoured sodium propionate as a short-chain carbon source for growth, rather than the intended plastic substrate, PET. The preference of sodium propionate utilization by several bacterial isolates, including 5601W (detected as Rhodococcus spp.), 5601Y, 7801, and 7802 (detected as Burkholderia spp.), was confirmed through growth curve analysis and cell enumeration conducted in a medium where sodium propionate served as the sole carbon source.; (4) The microbial demonstration revealed the metabolic complex of microbial communities in the environment and indicated the challenges associated with bacterial isolation from environments with accumulated plastic waste. Full article
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<p>Flow chart of microbial cultivation conducted in the study.</p>
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<p>Microbial enrichment examples from 1st generation of sample isolation. (<b>a</b>) Sample No. 63; (<b>b</b>) Sample No. 83; (<b>c</b>) Sample No. 68; (<b>d</b>) Sample No. 56.</p>
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<p>Percentage of culturable bacteria identified using 16S PCR amplicons from the sampling survey.</p>
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<p>Bacterial growth over 72 h incubation in the presence of different levels of SP. (<b>a</b>) Growth curve of 5601 mixed isolates (5601W and 5601Y); (<b>b</b>) Growth curve of isolate 7801; (<b>c</b>) Growth curve of isolate 7802; (<b>d</b>) Density of viable cells in cultivation with 0.04% SP at the endpoint of the growth curve. Control, initial viable cell counts at the start of the 72-h incubation test. Sample groups that did not share a letter were significantly different (<span class="html-italic">p</span> &lt; 0.05). Grouping Information Using the Tukey Method and 95% Confidence has been provided in <a href="#app1-applmicrobiol-04-00059" class="html-app">Table S1</a>.</p>
Full article ">Figure 4 Cont.
<p>Bacterial growth over 72 h incubation in the presence of different levels of SP. (<b>a</b>) Growth curve of 5601 mixed isolates (5601W and 5601Y); (<b>b</b>) Growth curve of isolate 7801; (<b>c</b>) Growth curve of isolate 7802; (<b>d</b>) Density of viable cells in cultivation with 0.04% SP at the endpoint of the growth curve. Control, initial viable cell counts at the start of the 72-h incubation test. Sample groups that did not share a letter were significantly different (<span class="html-italic">p</span> &lt; 0.05). Grouping Information Using the Tukey Method and 95% Confidence has been provided in <a href="#app1-applmicrobiol-04-00059" class="html-app">Table S1</a>.</p>
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<p>Growth characteristics of 5601W and 5601Y isolates. (<b>a</b>) Growth curve of 5601W. (<b>b</b>) Growth curve of 5601Y. (<b>c</b>) Cell enumeration at incubation times: D0 (0 h), D1 (24 h), D2 (48 h), and D3 (72 h). Significant differences were detected between no-SP group and SP group at different levels (<span class="html-italic">p</span> &lt; 0.05). Grouping Information Using the Tukey Method and 95% Confidence has been provided in <a href="#app1-applmicrobiol-04-00059" class="html-app">Table S2</a>.</p>
Full article ">Figure 5 Cont.
<p>Growth characteristics of 5601W and 5601Y isolates. (<b>a</b>) Growth curve of 5601W. (<b>b</b>) Growth curve of 5601Y. (<b>c</b>) Cell enumeration at incubation times: D0 (0 h), D1 (24 h), D2 (48 h), and D3 (72 h). Significant differences were detected between no-SP group and SP group at different levels (<span class="html-italic">p</span> &lt; 0.05). Grouping Information Using the Tukey Method and 95% Confidence has been provided in <a href="#app1-applmicrobiol-04-00059" class="html-app">Table S2</a>.</p>
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<p>The growth curves in triplicate tests. (<b>a</b>) growth curve of isolate 5601W; (<b>b</b>) growth curve of isolate 5601Y.</p>
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17 pages, 4080 KiB  
Article
TRI14 Is Critical for Fusarium graminearum Infection and Spread in Wheat
by Guixia Hao, Robert H. Proctor, Daren W. Brown, Nicholas A. Rhoades, Todd A. Naumann, HyeSeon Kim, Santiago Gutiėrrez and Susan P. McCormick
Appl. Microbiol. 2024, 4(2), 839-855; https://doi.org/10.3390/applmicrobiol4020058 - 23 May 2024
Viewed by 838
Abstract
Trichothecenes are sesquiterpenoid toxins produced by diverse ascomycetes, including Fusarium. The trichothecene analog deoxynivalenol (DON) produced by the Fusarium head blight (FHB) pathogen Fusarium graminearum is a virulence factor on wheat and a major food and feed safety concern. In Fusarium, [...] Read more.
Trichothecenes are sesquiterpenoid toxins produced by diverse ascomycetes, including Fusarium. The trichothecene analog deoxynivalenol (DON) produced by the Fusarium head blight (FHB) pathogen Fusarium graminearum is a virulence factor on wheat and a major food and feed safety concern. In Fusarium, the trichothecene biosynthetic gene (TRI) cluster consists of 7–14 genes. Most TRI cluster genes are conserved and their specific roles in trichothecene biosynthesis have been determined. An exception is TRI14, which is not required for DON synthesis in vitro but is required for spread of F. graminearum in wheat heads. In the current study, gene expression analyses revealed that TRI14 was highly induced in infected wheat heads. We demonstrated that TRI14 was not only required for F. graminearum spread but also important for initial infection in wheat. Although a prior study did not detect DON in infected seeds, our analyses showed significantly less DON and fungal biomass in TRI14-mutant (designated ∆tri14)-inoculated heads than wild-type-inoculated heads. Gene expression comparison showed that the level of expression of TRI genes was similar in the wheat tissues infected with ∆tri14 or the wild type, indicating the reduced toxin levels caused by ∆tri14 may be due to less fungal growth. ∆tri14 also caused less lesion and grew less in wheat coleoptiles than the wild type. The growth of ∆tri14 in carboxymethylcellulose medium was more sensitive to hydrogen peroxide than the wild type. The data suggest that TRI14 plays a critical role in F. graminearum growth, and potentially protects the fungus from plant defense compounds. Full article
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Figure 1

Figure 1
<p>(<b>A</b>) Distribution of trichothecene biosynthetic (<span class="html-italic">TRI</span>) genes in representative species of 13 fungal genera. The tree to the left was inferred from six housekeeping genes (<span class="html-italic">DPA1</span>, <span class="html-italic">FAS1</span>, <span class="html-italic">RPB1</span>, <span class="html-italic">RPB2</span>, <span class="html-italic">TEF1</span>, and <span class="html-italic">TUB2</span>). The colored shading indicates the fungal class to which the species belong: blue indicates Dothideomycetes; orange indicates Eurotiomycetes; and green indicates Sordariomycetes. The grid to the right indicates whether an ortholog of the 21 known <span class="html-italic">TRI</span> genes were detected by BLASTn analysis of a genome sequence for each fungal species in the tree. Tri14 is shaded in red. The Greek letter Psi (ψ) indicates the corresponding gene can be nonfunctional. In some previous studies on <span class="html-italic">TRI</span> genes, the genus names <span class="html-italic">Cordyceps</span>, <span class="html-italic">Myrothecium</span>, or <span class="html-italic">Spicellum</span> were used instead of <span class="html-italic">Akanthomyces</span>, <span class="html-italic">Paramyrothecium</span> or <span class="html-italic">Trichothecium</span>, respectively [<a href="#B1-applmicrobiol-04-00058" class="html-bibr">1</a>,<a href="#B6-applmicrobiol-04-00058" class="html-bibr">6</a>,<a href="#B18-applmicrobiol-04-00058" class="html-bibr">18</a>]. (<b>B</b>) Three-dimensional structures of Tri14 proteins predicted by AlphaFold. (<b>a</b>) FgTri14; (<b>b</b>) <span class="html-italic">F. sporotrichioides</span>; (<b>c</b>) <span class="html-italic">Trichoderma arundinaceum</span>.</p>
Full article ">Figure 1 Cont.
<p>(<b>A</b>) Distribution of trichothecene biosynthetic (<span class="html-italic">TRI</span>) genes in representative species of 13 fungal genera. The tree to the left was inferred from six housekeeping genes (<span class="html-italic">DPA1</span>, <span class="html-italic">FAS1</span>, <span class="html-italic">RPB1</span>, <span class="html-italic">RPB2</span>, <span class="html-italic">TEF1</span>, and <span class="html-italic">TUB2</span>). The colored shading indicates the fungal class to which the species belong: blue indicates Dothideomycetes; orange indicates Eurotiomycetes; and green indicates Sordariomycetes. The grid to the right indicates whether an ortholog of the 21 known <span class="html-italic">TRI</span> genes were detected by BLASTn analysis of a genome sequence for each fungal species in the tree. Tri14 is shaded in red. The Greek letter Psi (ψ) indicates the corresponding gene can be nonfunctional. In some previous studies on <span class="html-italic">TRI</span> genes, the genus names <span class="html-italic">Cordyceps</span>, <span class="html-italic">Myrothecium</span>, or <span class="html-italic">Spicellum</span> were used instead of <span class="html-italic">Akanthomyces</span>, <span class="html-italic">Paramyrothecium</span> or <span class="html-italic">Trichothecium</span>, respectively [<a href="#B1-applmicrobiol-04-00058" class="html-bibr">1</a>,<a href="#B6-applmicrobiol-04-00058" class="html-bibr">6</a>,<a href="#B18-applmicrobiol-04-00058" class="html-bibr">18</a>]. (<b>B</b>) Three-dimensional structures of Tri14 proteins predicted by AlphaFold. (<b>a</b>) FgTri14; (<b>b</b>) <span class="html-italic">F. sporotrichioides</span>; (<b>c</b>) <span class="html-italic">Trichoderma arundinaceum</span>.</p>
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<p>Trichothecene produced by <span class="html-italic">TRI14</span> deletion mutants (∆<span class="html-italic">tri14</span>-27 and -50) and wild-type parent strain (GZ3639). Three replicate cultures of each strain were grown for 7 days in liquid agmatine medium. Culture extracts were examined by GC-MS for 15-acetyldeoxynivalenol (15-ADON), and the resulting data were analyzed by one-way ANOVA and Tukey–Kramer HSD tests using JMP (<span class="html-italic">n</span> = 3).</p>
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<p>Induction of <span class="html-italic">TRI14</span> in <span class="html-italic">F. graminearum</span>-inoculated wheat heads. Heads of wheat cultivar Norm were inoculated by immersion in a macroconidial suspension of wild-type <span class="html-italic">F. graminearum</span> (10<sup>5</sup> conidia/mL in 0.02% Tween 20). Heads were collected daily for 7 days post inoculation. Three biological replicates, with two heads per replicate, were collected at each time point for RNA isolation. Gene expression was determined by RT-qPCR. β-tubulin expression served as an internal control to normalize gene expression. Fold changes in gene expression were relative to expression levels determined for a 7-day axenic <span class="html-italic">F. graminearum</span> wild-type strain grown on V8 Juice agar, which was set as one. Three technical replicates were conducted for each sample from three biological replicates at each time points.</p>
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<p>Deletion of <span class="html-italic">TRI14</span> restricts FHB spread and reduces fungal biomass and DON contents in inoculated spikelets. (<b>A</b>) Spikelets of wheat cultivar Norm were point inoculated with conidia suspensions of ∆<span class="html-italic">tri14</span> or the wild-type parent strain GZ3639 (10 µL, 10<sup>5</sup> conidia/mL). Photographs were taken at 21 days post inoculation (dpi). Red arrows mark the inoculated spikelets, which were collected for DON and fungal biomass quantification. (<b>B</b>) The percentage of diseased spikelets at 7, 14, and 21 dpi. (<b>C</b>) Fungal biomass in inoculated wheat spikelets at 21 dpi. Fungal biomass was quantified by qPCR by calculating <span class="html-italic">TRI6</span> Ct value relative to wheat <span class="html-italic">TaGAPDH</span> Ct value. Bars represents percentage of fungal biomass in heads inoculated with ∆<span class="html-italic">tri14</span> relative to those inoculated with GZ3639. (<b>D</b>) DON content in inoculated wheat spikelets at 21 dpi. Asterisk (*) indicates significant difference at the <span class="html-italic">p</span> &lt; 0.05 confidence level. One-way ANOVA and Tukey–Kramer HSD (<span class="html-italic">n</span> = 24 for disease, and <span class="html-italic">n</span> = 8 for biomass and toxin) tests were conducted using JMP.</p>
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<p>Deletion of <span class="html-italic">TRI14</span> reduces fungal biomass and DON in dip-inoculated wheat heads. Dip inoculations were performed by immersing whole heads of wheat cv. Norm in suspensions of ∆<span class="html-italic">tri14</span> or the wild-type parent strain GZ3639 (5 × 10<sup>4</sup> conidia/mL). (<b>A</b>) FHB was scored as the percentage of spikelets with visual symptoms at 5 days post inoculation (dpi). (<b>B</b>) Fungal biomass in inoculated wheat heads at 5 dpi. Fungal biomass was quantified by qPCR by calculating <span class="html-italic">TRI6</span> Ct value relative to wheat <span class="html-italic">TaGAPDH</span> Ct value. Bars represents percentage of fungal biomass in heads inoculated with ∆<span class="html-italic">tri14</span> relative to those inoculated with GZ3639. (<b>C</b>) DON content in inoculated wheat heads at 5 dpi. Asterisk (*) indicates significant difference at the <span class="html-italic">p</span> &lt; 0.05 confidence level. One-way ANOVA and Tukey–Kramer HSD (<span class="html-italic">n</span> = 22 for disease, and <span class="html-italic">n</span> = 7 for biomass and DON) tests were conducted using JMP.</p>
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<p>Comparison of <span class="html-italic">TRI</span> gene expression in wheat heads inoculated with GZ3639 and ∆<span class="html-italic">tri14</span>. (<b>A</b>) <span class="html-italic">TRI14</span>. (<b>B</b>) <span class="html-italic">TRI</span> genes (eight): <span class="html-italic">TRI5</span>, <span class="html-italic">TRI6</span>, <span class="html-italic">TRI12</span>, <span class="html-italic">TRI3</span>, <span class="html-italic">TRI4</span>, <span class="html-italic">TRI8</span>, <span class="html-italic">TRI10</span> and <span class="html-italic">TRI11</span>. Heads of wheat cultivar Norm were inoculated by immersing the entire head in a macroconidia suspension of GZ3639 or ∆<span class="html-italic">tri14</span> (10<sup>5</sup> conidia/mL in 0.02% Tween 20). Three biological replicates, each replicate with three heads, were collected 3 days post inoculation (dpi) and used for RNA isolation. Gene expression was determined by RT-qPCR. Fungal β-tubulin was used as an internal control for transcript normalization. Relative gene expression was calculated using the 2<sup>−ΔΔCt</sup> method by setting the expression in inoculated heads as base (<b>A</b>) and the expression level in GZ3639 inoculated as base (<b>B</b>). Three technical replicates were conducted for each biological replicates. Asterisk (*) indicates significant difference at the <span class="html-italic">p</span> &lt; 0.05 confidence level. One-way ANOVA and Tukey–Kramer HSD tests (<span class="html-italic">n</span> = 3) were conducted using JMP.</p>
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<p><span class="html-italic">TRI14</span> deletion mutant reduces lesion and fungal biomass in infected wheat coleoptiles. (<b>A</b>) Lesions on coleoptiles at 7 dpi infected by wild type (GZ3639) and ∆<span class="html-italic">tri14</span>. Red parentheses indicate lesion lengths on individual coleoptiles. <b>(B</b>) Average lesion length on coleoptiles caused by the wild-type and ∆<span class="html-italic">tri14</span> strains. (<b>C</b>) Fungal biomass in coleoptiles inoculated with the ∆<span class="html-italic">tri14</span> strain and wild-type strains. Bars represents percentage of fungal biomass in heads inoculated with ∆<span class="html-italic">tri14</span> relative to those inoculated with GZ3639. Histograms in (<b>B</b>,<b>C</b>) indicate mean values from 20 coleoptiles. Error bars indicate standard error. Asterisks (*) denote significant difference at the confidence level (<span class="html-italic">p</span> &lt; 0.05). One-way ANOVA and Tukey–Kramer HSD (<span class="html-italic">n</span> = 20) tests were conducted in JMP.</p>
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<p>H<sub>2</sub>O<sub>2</sub> affects growth of ∆<span class="html-italic">tri14</span> mutant. (<b>A</b>) Growth comparison of wild type and ∆<span class="html-italic">tri14</span> on PDA plates containing 25 mM H<sub>2</sub>O<sub>2</sub> at five days post inoculation. (<b>B</b>) H<sub>2</sub>O<sub>2</sub> similarly inhibited growth of wild type and ∆<span class="html-italic">tri14</span>. Values are averages of four biological replicates. (<b>C</b>) Comparison of growth of wild type and ∆<span class="html-italic">tri14</span> in CMC medium containing 2 mM H<sub>2</sub>O<sub>2</sub>. (<b>D</b>) Comparison of conidiation of wild type and ∆<span class="html-italic">tri14</span> in CMC medium containing 2 mM H<sub>2</sub>O<sub>2</sub> after 72 h incubation. Values are averages of 12 biological replicates. One-way ANOVA and Tukey–Kramer HSD tests of means were conducted in JMP. Different letters indicate significant difference with <span class="html-italic">p</span> &lt; 0.05 confidence.</p>
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15 pages, 1563 KiB  
Review
Reassessing Gout Management through the Lens of Gut Microbiota
by Jean Demarquoy and Oumaima Dehmej
Appl. Microbiol. 2024, 4(2), 824-838; https://doi.org/10.3390/applmicrobiol4020057 - 22 May 2024
Viewed by 640
Abstract
Gout, recognized as the most common form of inflammatory arthritis, arises from the accumulation of uric acid crystals, leading to intense pain, particularly in the big toe. This condition has traditionally been associated with the overproduction or reduced clearance of uric acid. Recent [...] Read more.
Gout, recognized as the most common form of inflammatory arthritis, arises from the accumulation of uric acid crystals, leading to intense pain, particularly in the big toe. This condition has traditionally been associated with the overproduction or reduced clearance of uric acid. Recent studies, however, have underscored the significant role of the gut microbiota in uric acid metabolism, impacting both its production and elimination. This emerging understanding suggests that maintaining gut health could offer innovative approaches to treating gout, complementing traditional dietary and pharmacological interventions. It highlights the potential of probiotics or microbiome-based therapies, indicating a future where treatments are tailored to an individual’s microbiome. This offers a fresh perspective on gout management and underscores the broader influence of the microbiota on health and disease. Full article
(This article belongs to the Special Issue Microbiome in Ecosystem 3.0)
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<p>Schematic representation of the origin of uric acid and its association with gout: Uric acid originates from dietary sources and hepatic biosynthesis. It is eliminated from the body through renal excretion and the gastrointestinal tract. Excessive levels of uric acid can lead to the development of gout. Drawing created with the assistance of Macrovector Image and brgfx on Freepik.</p>
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<p>Metabolic pathways for uric acid: Uric acid can be transformed into allantoin by uricase, an enzyme that is not expressed by human cells but by many bacteria of the gut microbiota. Drawing created with the assistance of Macrovector Image and brgfx on Freepik.</p>
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<p>PRISMA flow [<a href="#B22-applmicrobiol-04-00057" class="html-bibr">22</a>].</p>
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13 pages, 1475 KiB  
Article
Synergistic Effect of Postbiotic Yeast ABB C22® on Gut Inflammation, Barrier Function, and Protection from Rotavirus Infection in In Vitro Models
by Lydia Carrera Marcolin, Jordi Cuñé Castellana, Laia Martí Melero, Carlos de Lecea and Maria Tintoré Gazulla
Appl. Microbiol. 2024, 4(2), 811-823; https://doi.org/10.3390/applmicrobiol4020056 - 16 May 2024
Viewed by 681
Abstract
Diarrhoea is a serious cause of mortality worldwide that can lead to dehydration, gut barrier function impairment, nutrient malabsorption, and alterations of the gut microbiota (dysbiosis). The current solutions for its management, such as oral rehydration salts (ORS), inhibitors of gut motility, antibiotics, [...] Read more.
Diarrhoea is a serious cause of mortality worldwide that can lead to dehydration, gut barrier function impairment, nutrient malabsorption, and alterations of the gut microbiota (dysbiosis). The current solutions for its management, such as oral rehydration salts (ORS), inhibitors of gut motility, antibiotics, and living probiotics, only partially counteract the mechanisms of the disease and do not provide a full coverage of the problem. The potential risks of the use of living probiotic strains, particularly in immunocompromised patients, can be eliminated with the use of tyndallized (heat-killed) postbiotic bacteria and yeast. ABB C22® is a postbiotic combination of three tyndallized yeasts, namely Saccharomyces boulardii, Saccharomyces cerevisiae, and Kluyveromyces marxianus. To assess the action of the postbiotic combination on diarrhoea, immune and gut epithelial cell signalling assays, the gut barrier formation assay, and the rotavirus gene expression assay were performed. ABB C22® showed a strong anti-inflammatory effect, an induction of the build-up of the gut epithelium, and a degree of protection against rotavirus infection. These experimental studies support the use of the postbiotic ABB C22® as a solution for the management of diarrhoea and gastrointestinal conditions, alone or in combination with existing but incomplete treatments. Full article
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<p>In vitro modulation of TNF-α and IL-10 levels and TNF-α/IL-10 ratio in human THP-1 cell line (macrophages). (<b>A</b>) TNF-α levels in the absence of pro-inflammatory stimulus. (<b>B</b>) TNF-α levels in the presence of a pro-inflammatory stimulus (LPS challenge) simulating an infection process. (<b>C</b>) IL-10 levels in the absence of pro-inflammatory stimulus. (<b>D</b>) IL-10 levels in the presence of a pro-inflammatory stimulus (LPS challenge) simulating an infection process. (<b>E</b>) TNF-α/IL-10 ratio in the absence of pro-inflammatory stimulus. (<b>F</b>) TNF-α/IL-10 ratio in the presence of a pro-inflammatory stimulus (LPS challenge) simulating an infection process. All results are expressed as the standardization against the effect of the negative control.</p>
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<p>Production of pro-inflammatory cytokines by Caco-2 cells after incubation with ABB C22<sup>®</sup> and three yeasts. *, ** and *** represent statistical significance with <span class="html-italic">p</span>-value &lt; 0.05, 0.01, and 0.001, respectively, for between-group comparisons (one-way analysis of variance, ANOVA, and Dunnett’s post hoc test). (<b>A</b>) IP-10 cytokine production in the absence of pro-inflammatory stimulus. (<b>B</b>) IP-10 cytokine production in the presence of a pro-inflammatory stimulus (TNF-α/IFN-γ) simulating an inflamed gut epithelium. (<b>C</b>) IL-8 cytokine production in the absence of pro-inflammatory stimulus. (<b>D</b>) IL-8 cytokine production in the presence of a pro-inflammatory stimulus (TNF-α/IFN-γ) simulating an inflamed gut epithelium. (<b>E</b>) MCP-1 cytokine production in the absence of pro-inflammatory stimulus. (<b>F</b>) MCP-1 cytokine production in the presence of a pro-inflammatory stimulus (TNF-α/IFN-γ) simulating an inflamed gut epithelium. The results of each cytokine are expressed as the standardization against the effect of the negative control.</p>
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<p>Bars and slopes of trendlines for TEER increases associated with incubation of Caco-2 monolayer cells with a negative control, ABB C22<sup>®</sup>, and a commercial control of live <span class="html-italic">S. boulardii</span> CNCM I-745<sup>®</sup>. The comparison of ∆TEER values (Y axis) over the course of 22 days (X axis) indicates a higher spontaneous build-up of the epithelium monolayer for the ABB C22<sup>®</sup> condition versus the controls.</p>
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<p>Bar diagram showing relative NSP3 and VP7 gene expression in RNA extracts from MA104 cells subjected to a 24 h pre-treatment with the selected combinations of yeast strains and to infection with rotavirus for 72 h. *, ** and **** represent statistical significance with <span class="html-italic">p</span>-value &lt; 0.05, 0.01, and 0.0001, respectively.</p>
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17 pages, 2567 KiB  
Review
Genetic Engineering of Filamentous Fungi: Prospects for Obtaining Fourth-Generation Biological Products
by Lorena Resende Oliveira, Ariany Rosa Gonçalves, Eliane Dias Quintela, Leandro Colognese, Marcio Vinicius de C. Barros Cortes and Marta Cristina Corsi de Filippi
Appl. Microbiol. 2024, 4(2), 794-810; https://doi.org/10.3390/applmicrobiol4020055 - 13 May 2024
Viewed by 805
Abstract
Filamentous fungi exhibit unparalleled potential as cell factories for protein production, owing to their adeptness in protein secretion and remarkable proficiency in post-translational modifications. This review delineates the role of filamentous fungi in bio-input technology across different generations and explores their capacity to [...] Read more.
Filamentous fungi exhibit unparalleled potential as cell factories for protein production, owing to their adeptness in protein secretion and remarkable proficiency in post-translational modifications. This review delineates the role of filamentous fungi in bio-input technology across different generations and explores their capacity to generate secondary metabolites. Our investigation highlights filamentous fungi as frontrunners in the production of bioactive compounds, emphasizing the imperative nature of elucidating their metabolic repertoire. Furthermore, we delve into common strategies for genetic transformation in filamentous fungi, elucidating the underlying principles, advantages, and drawbacks of each technique. Taking a forward-looking approach, we explore the prospects of genome engineering, particularly the CRISPR-Cas9 technique, as a means to propel protein secretion in filamentous fungi. Detailed examination of the protein secretion pathways in these fungi provides insights into their industrial applications. Notably, extensive research within the scientific community has focused on Aspergillus and Trichoderma species for the industrial production of proteins and enzymes. This review also presents practical examples of genetic engineering strategies aimed at augmenting enzyme secretion in filamentous fungi for various industrial applications. These findings underscore the potential of filamentous fungi as versatile platforms for protein production and highlight avenues for future research and technological advancement in this field. Full article
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<p>The different generations of bio-input technology.</p>
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<p>Active ingredients registered in Brazil based on Filamentous Fungi for pest and disease control [<a href="#B9-applmicrobiol-04-00055" class="html-bibr">9</a>].</p>
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<p>Estimate of bioactive metabolites got from microorganisms, adapted from [<a href="#B35-applmicrobiol-04-00055" class="html-bibr">35</a>].</p>
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<p>Diagram of the primary and secondary metabolism of fungi showing when the production of secondary metabolites occurs, adapted from [<a href="#B38-applmicrobiol-04-00055" class="html-bibr">38</a>]. The solid blue line represents the growth curve of a hypothetical microorganism. The dashed brown line represents the nutrient concentration. And the dashed purple line represents the concentration of secondary metabolites, which occurs during the stationary growth phase of the microorganism.</p>
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<p>Basic steps in gene editing using CRISPR/Cas9. [credit: Esmée Dragt (creator) and Louis Ngai (BioRender.com (2020). Retrieved from <a href="https://app.biorender.com/biorender-templates/figures/all/t-5f873df466346900a43c6db1-crisprcas9-gene-editing" target="_blank">https://app.biorender.com/biorender-templates/figures/all/t-5f873df466346900a43c6db1-crisprcas9-gene-editing</a>, accessed on 16 January 2024)].</p>
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<p>Protein secretion pathways in filamentous fungi. The secretion pathways of filamentous fungi exemplify the following modes: (1) classical secretion through the ER, (2) septal secretion, (3) Golgi-independent secretion, (4) multivesicular body (MVB) secretion, and (5) autophagic secretion, adapted from [<a href="#B84-applmicrobiol-04-00055" class="html-bibr">84</a>]. The black balls represent proteins secreted by the classical secretion pathway through the ER; The orange balls represent the proteins secreted by the septal secretion; The green ones represent the proteins secreted by the Golgi-independent secretion; The red ones represent the proteins secreted by multivesicular body (MVB) secretion and the blue ones represent the proteins secreted by autophagic secretion.</p>
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12 pages, 4928 KiB  
Article
Genomic and Functional Characterization of CTX-M-15-Producing Klebsiella pneumoniae ST307 Isolated from Imported Leopard Tortoises in Germany
by Tammy J. Schmidt, Sophie Aurich, Franziska Unger, Tobias Eisenberg and Christa Ewers
Appl. Microbiol. 2024, 4(2), 782-793; https://doi.org/10.3390/applmicrobiol4020054 - 11 May 2024
Viewed by 651
Abstract
The Klebsiella pneumoniae ST307 clone, identified in the mid-1990s, has emerged as a global antimicrobial-resistant (AMR) high-risk clone, significantly contributing to the global health challenge also posed by other AMR K. pneumoniae lineages. The acquisition of a blaCTX-M-15-carrying plasmid has facilitated [...] Read more.
The Klebsiella pneumoniae ST307 clone, identified in the mid-1990s, has emerged as a global antimicrobial-resistant (AMR) high-risk clone, significantly contributing to the global health challenge also posed by other AMR K. pneumoniae lineages. The acquisition of a blaCTX-M-15-carrying plasmid has facilitated its widespread dissemination. At Europe’s major transport hub for the movement of live animals, Frankfurt Airport, a shipment of 20 live leopard tortoises was sampled during German border control in 2014. Phylogenetic analysis (MLST) identified a K. pneumoniae ST307 strain, prompting further investigation. Our analysis revealed the presence of a ~193 kb plasmid carrying a broad range of AMR genes, including blaCTX-M-15, blaTEM-1B, blaOXA-1, aac(3)-IIa, aac(6′)-Ib-cr, aph(3″)-Ib, aph(6)-Id, and qnrB1. Additionally, mutations in the quinolone resistance-determining region in gyrA (S83I) and parC (S80I) were detected. Phenotypic testing demonstrated resistance of the isolate to the most common antimicrobials used in both human and veterinary medicine; exceptions included carbapenems and newer β-lactamase inhibitor combinations. Because the role of imported exotic animals in the dissemination of AMR genes is largely deficient, the present study fills yet missing mosaic pieces in the complete picture of extended-spectrum β-lactamase (ESBL)-producing Enterobacterales. Full article
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<p>Circular visualization of <span class="html-italic">K. pneumoniae</span> plasmids as compared to pIHIT34097 using BRIG [<a href="#B43-applmicrobiol-04-00054" class="html-bibr">43</a>]. Details of the origin and genes harbored by the plasmids are presented in <a href="#app1-applmicrobiol-04-00054" class="html-app">Supplementary Table S1</a>.</p>
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<p>Minimum spanning tree (MST) based on allelic distances of 70 <span class="html-italic">K. pneumoniae</span> genomes (60 × human, 8 × environment, 2 × tortoise) determined by cgMLST analysis. The nodes are colored according to the geographical origin of the strains. The size of the nodes is proportional to the number of isolates. Numbers on branches indicate allele differences between core genomes. The nodes representing IHIT34097 and BL714, both isolated from tortoises, are marked with a dotted margin. Strains are assigned to MST clusters 1 to 4 with a threshold of 15 allele differences. Details of the origin and genes harbored by the strains are presented in <a href="#app1-applmicrobiol-04-00054" class="html-app">Supplementary Table S1</a>.</p>
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<p>Results of phenotypic virulence-associated assays. (<b>a</b>) Survival in 50% human serum after 0 and 4 h of incubation compared to serum-resistant strain PBIO1289 and serum-sensitive strain W3110 revealed a serum-resistant phenotype of IHIT34097. The serum-sensitive strain W3110 mixed with heat-inactivated serum was added to validate the bactericidal effect of the serum. Results are given as a log<sub>2</sub> fold change in CFU/mL. IHIT34097 showed a significantly greater increase in growth after 4 h of incubation compared to the positive control PBIO1289 (Fisher exact * <span class="html-italic">p</span> &lt; 0.00001; the result is significant at <span class="html-italic">p</span> &lt; 0.05). (<b>b</b>) Qualitative siderophore production of IHIT34097 revealed a small halo of 9.5 mm and therefore positive siderophore production <span class="html-italic">(entABCEF</span>, <span class="html-italic">fepABCDG</span>, <span class="html-italic">fes</span>, <span class="html-italic">ybdA</span>, and <span class="html-italic">iutA</span>). For better comparability, <span class="html-italic">iucABCD</span> positive strain IHIT50398 is also shown, indicating an increased siderophore production as defined by halo comparison (16.5 mm halo, 8.5 mm colony).</p>
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11 pages, 1309 KiB  
Article
Genes of Salmonella enterica Serovar Enteritidis Involved in Biofilm Formation
by Seulgi Lee and Jinru Chen
Appl. Microbiol. 2024, 4(2), 771-781; https://doi.org/10.3390/applmicrobiol4020053 - 10 May 2024
Viewed by 800
Abstract
Although biofilms contribute to bacterial tolerance to desiccation and survival in low-moisture foods, the molecular mechanisms underlying biofilm formation have not been fully understood. This study created a mutant library from Salmonella Enteritidis using mini-Tn10 transposon mutagenesis. The biofilm-forming potential of acquired [...] Read more.
Although biofilms contribute to bacterial tolerance to desiccation and survival in low-moisture foods, the molecular mechanisms underlying biofilm formation have not been fully understood. This study created a mutant library from Salmonella Enteritidis using mini-Tn10 transposon mutagenesis. The biofilm-forming potential of acquired mutants was assessed before the genomic DNA of the mutants that formed significantly (p ≤ 0.05) less biofilm mass than their wildtype parent strain was extracted for deep DNA sequencing. The gene of each mutant interrupted by mini-Tn10 insertion was identified by aligning obtained sequencing data with the reference Genbank sequences using a BLAST search. Sixty-four mutant colonies were selected, and five mutants that formed the least amount of biofilm mass compared to the wildtype parent strain were selected for sequencing analysis. The results of the BLAST search revealed that the gene interrupted by mini-Tn10 in each mutant is responsible for the biosynthesis of aldehyde dehydrogenase (EutE), cysteine desulfurase (SufS or SufE), a transporter protein, porin OmpL, and a ribbon–helix–helix protein from the CopG family, respectively. Knock-off mutant construction is a possible approach to verify the potential of the identified genes to serve as targets of antimicrobial intervention to control Salmonella colonization on low-moisture foods and in their production environment. Full article
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<p>Cultures of a selected <span class="html-italic">Salmonella</span> mutant on tryptic soy agar supplemented with 100 μg/mL ampicillin (<b>left</b>) and XLT-4 agar (<b>middle</b>), as well as the cultures of the <span class="html-italic">E. coli</span> donor BW20767 [pink] and the <span class="html-italic">Salmonella</span> mutant [colorless] (<b>right</b>) on MacConkey agar.</p>
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<p>Biofilm mass developed by wildtype and mutant <span class="html-italic">S. enteritidis</span>. The data represent the A<sub>550</sub> values of the solutions of crystal violet extracted from biofilm mass. The error bars represent the standard deviations of the means. Means followed by different letters are significantly different (<span class="html-italic">p</span> ≤ 0.05). SE-PC: positive control from the wildtype parent strain.</p>
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<p>Mini-Tn<span class="html-italic">10</span> insertion locations in the SE-L3, SE-L19, SE-L29, SE-S15, and SE-S26 mutants on a circular chromosome map of <span class="html-italic">S. enteritidis</span> (accession no. CP050716.1).</p>
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18 pages, 2216 KiB  
Article
Antimicrobial Activity of Fungal Endophytes Associated with Peperomia argyreia (Piperaceae)
by Melisa Isabel Barolo, María Victoria Castelli and Silvia Noelí López
Appl. Microbiol. 2024, 4(2), 753-770; https://doi.org/10.3390/applmicrobiol4020052 - 5 May 2024
Viewed by 790
Abstract
The endophytic fungal biodiversity of unique plants like Peperomia argyreia (Miq.) É. Morren (Piperaceae) has antimicrobial properties and can be employed for infection treatment. Fungal isolates were obtained from appropriately treated plant tissues cultured in solid media, characterized by morphology, and identified by [...] Read more.
The endophytic fungal biodiversity of unique plants like Peperomia argyreia (Miq.) É. Morren (Piperaceae) has antimicrobial properties and can be employed for infection treatment. Fungal isolates were obtained from appropriately treated plant tissues cultured in solid media, characterized by morphology, and identified by molecular biology using ITS and NL primers. The antimicrobial properties of fungal extracts were analyzed by combining microdilution and bioautographic assays complemented with metabolic profiling by automated thin-layer chromatography and 1H NMR techniques. Thirty-one filamentous fungi were isolated and characterized by ITS and/or D1/D2 region amplification of rDNA, identified as Thermothielavioides, Trichoderma, Cyphellophora, Cladosporium, Arcopilus, Plectosphaerella; Chaetomium, Sporothrix, Alboefibula, and Penicillium. Thermothielavioides spp. inhibited Staphylococcus aureus ATCC 25923; moreover, Penicillium westlingii P4 showed inhibitory activity on Ascochyta rabiei AR2. The bioactivity-guided fractionation of the EtOAc extract (MIC = 62.5 μg/mL) of P. westlingii P4 allowed the purification of citrinin as the main inhibitory compound (MIC = 62.5 μg/mL). Peperomia argyreia harbors a rich and diverse endophytic community able to produce bioactive molecules. Citrinin, with a minor influence of volatile compounds biosynthesized by P. westlingii P4, was responsible for the inhibition of A. rabiei AR2. Full article
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<p>Distribution of the genera of the fungal endophytes isolated from <span class="html-italic">Peperomia argyreia</span> (Piperaceae).</p>
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<p>Similarity matrix of MALDI spectra from the fungal endophytes isolated from <span class="html-italic">P. argyreia</span>. To the left of each isolate code is the identification obtained by the molecular biology tool. Similarity scale (white to black 0–100%): white 0–18%; light gray 18–32%; gray 32–50%; dark gray 50–66%; blue 66–83%; black 83–100%.</p>
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<p>(<b>A</b>) <sup>1</sup>H NMR (300 MHz, CDCl3) spectra of selected extracts of the endophytic fungi P4, P1, P5, P20, P31, P13, P22, and P30 isolated from <span class="html-italic">P. argyreia</span>. (<b>B</b>) PCA of the <sup>1</sup>H NMR spectra of the extracts of the 31 endophytic fungi isolated from <span class="html-italic">P. argyreia</span>.</p>
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<p>(<b>a</b>) Combined antagonistic effects amongst <span class="html-italic">P. westlingii</span> and <span class="html-italic">A. rabiei</span> after 21 d in PDA in the dark. (<b>b</b>) Control plate of <span class="html-italic">A. rabiei</span> after 21 d in PDA in the dark. (<b>c</b>) UV 254 nm TLC profile comparing EtOAc extracts of P4 colony, a piece of agar between P4 and <span class="html-italic">A. rabiei</span> (*), and a section of the PDA medium away from the interactions (**). (<b>d</b>) UV-Vis densitometric spectrum taken from the chromatographic band corresponding to citrinin (red blot). (<b>e</b>) Plate (<b>c</b>) sprayed with H<sub>2</sub>SO<sub>4</sub> plus heating observed at 254 nm. Mobile phase: EtOAc:MeOH:H2O (7.7:1.3:1), extracts: 25 μg/band of 4 mm. Photographs were taken on a TLC Visualizer 2 Camag. Densitometric analysis was performed in a TLC Scanner 4 Camag. (<b>e</b>) a piece of agar between P4 and <span class="html-italic">A. rabiei</span> (*); a section of the PDA medium away from the interactions (**).</p>
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<p>Comparison of the development of <span class="html-italic">A. rabiei</span> in PDA (control) versus in PDA plus 125 μg/mL of citrinin at 7, 14, and 21 d of development at 24 ° C, in the dark. MGI% = Mycelial growth index.</p>
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8 pages, 608 KiB  
Article
A Sublethal Concentration of Chlorine Induces Antibiotic Resistance in Salmonella via Production of Reactive Oxygen Species
by Mohammed Aljuwayd, Israa Abdullah Malli, Steven C. Ricke and Young Min Kwon
Appl. Microbiol. 2024, 4(2), 745-752; https://doi.org/10.3390/applmicrobiol4020051 - 30 Apr 2024
Viewed by 594
Abstract
Studies have shown that the production of reactive oxygen species (ROS) is triggered by bactericidal antibiotics, which contributes significantly to the killing of bacterial cells and increasing mutations in surviving cells. In this study, we hypothesized that exposure of Salmonella to sublethal concentrations [...] Read more.
Studies have shown that the production of reactive oxygen species (ROS) is triggered by bactericidal antibiotics, which contributes significantly to the killing of bacterial cells and increasing mutations in surviving cells. In this study, we hypothesized that exposure of Salmonella to sublethal concentrations of hypochlorite (NaOCl), a commonly used sanitizer in household and food industries increases mutation rates, leading to the development of antibiotic resistance. We found that a sublethal concentration (20 ppm) of NaOCl increased the mutation rates of S. typhimurium 14028s significantly (p < 0.05), which was prevented by the ROS scavenger thiourea, supporting that the increased mutation was due to NaOCl-triggered ROS production. We further found that the exposure of S. typhimurium 14028s to the same sublethal concentration of NaOCl increases resistance to kanamycin among the 3 antibiotics evaluated. The results of this study suggest that when NaOCl applied as a sanitizer fails to kill Salmonella due to diluted local concentrations or presence of organic materials, it can cause an adverse outcome of developing antibiotic resistance of the pathogen. Full article
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<p>The mutation rates of <span class="html-italic">S. typhimurium</span> 14028s after exposure to a sublethal concentration of NaOCl. <span class="html-italic">S. typhimurium</span> 14028s was exposed to NaOCl (20 ppm) or NaOCl (20 ppm) plus thiourea (150 mM) before determination of the mutation rate using rifampicin. The same procedure was repeated with no exposure (no treatment; negative control) or exposure to H<sub>2</sub>O<sub>2</sub> (1 mM; positive control). Different letters denote statistical differences (<span class="html-italic">p</span> &lt; 0.0006).</p>
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<p>Development of antibiotic resistance after exposure to a sublethal concentration of NaOCl. <span class="html-italic">S. typhimurium</span> 14028s was exposed to NaOCl (20 ppm) or none (negative control) before determination of the resistance to different antibiotics (Amp, Cm or Km) as the % of the surviving cells.</p>
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14 pages, 3566 KiB  
Article
Effects of Vacuum Pasteurization on the Nutritional, Sensory and Microbiological Properties of Orange (Citrus × sinensis) and Carrot (Daucus carota L.) Nectar
by Llerena-Silva Wilma, José Burgos, Jacqueline Ortiz, Iván Samaniego, Jhunior Marcia, Molina José, Christian Vallejo, Ignacio Angós, Ajitesh Yaday and Ricardo Santos Alemán
Appl. Microbiol. 2024, 4(2), 731-744; https://doi.org/10.3390/applmicrobiol4020050 - 28 Apr 2024
Viewed by 846
Abstract
This study involved the evaluation of the effect of vacuum pasteurization on physicochemical characteristics (pH, total soluble solids, titratable acidity, chroma, tone, IO, vitamin C, 5-hydroxymethylfurfural), microbiological properties (Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, total coliforms, total mesophilic aerobes, [...] Read more.
This study involved the evaluation of the effect of vacuum pasteurization on physicochemical characteristics (pH, total soluble solids, titratable acidity, chroma, tone, IO, vitamin C, 5-hydroxymethylfurfural), microbiological properties (Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, total coliforms, total mesophilic aerobes, molds and yeasts) and sensory characteristics of orange and carrot nectar. The thermal treatments were designed based on the thermal lethality of two heat-resistant microorganisms typical of the product (Neosartorya fischeri and Zygosaccaromyces bailii). The evaluation was carried out on raw nectar and pasteurized nectar. The shelf life was estimated to be 30 days (6 °C). The most favorable results were obtained by applying a heat treatment at 88 °C for 32.68 min, managing to retain 85.87% of vitamin C and a microbiological stability of 12 days (6 ± 0.6 °C) with regard to total mesophilic aerobes. Likewise, the tasters established that this treatment resulted in the best flavor, texture and acceptability characteristics. Full article
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<p>Flow diagram of the vacuum pasteurization process for orange and carrot nectar.</p>
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<p>Color changes in orange and carrot nectar using 6 heat treatments. Raw nectar (<b><span style="color:#0070C0">o</span></b>), pasteurized nectar (<b><span style="color:#538135">o</span></b>).</p>
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<p>Degradation of vitamin C in orange and carrot nectar using 6 thermal treatments: T1: 92 °C/3.3 min; T2: 90 °C/10.3min; T3: 88 °C/32.7min; T4: 70 °C/2.3min; T5: 65 °C/11.4min; T6: 60 °C/56.6 min. Raw nectar (■), pasteurized (<span style="color:#7F7F7F">■</span>) and stored at 6 °C for 30 days (<span style="color:#AEAAAA">■</span>). A, B, C: Significant differences (<span class="html-italic">p</span> &lt; 0.05) between thermal treatments (T1, T2, T3, T4, T5, T6). a, b, c: Significant differences (<span class="html-italic">p</span> &lt; 0.05) between orange and carrot nectar raw and pasteurized nectar.</p>
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<p>Evolution of the content of total mesophilic aerobic bacteria (<b>□</b>), yeasts (◊) and molds (○) in orange and carrot nectars treated by vacuum cooking. T1: 92 °C/3.3 min (<b>A</b>); T2: 90 °C/10.3 min (<b>B</b>); T3: 88 °C/32.7 min (<b>C</b>); T4: 70 °C/2.3 min (<b>D</b>); T5: 65 °C/11.4 min (<b>E</b>); T6: 60 °C/56.6 min (<b>F</b>). NEN standard limit &lt; 10 CFU·mL<sup>−1</sup> for total mesophilic aerobic microorganisms and &lt;10 PUF·mL<sup>−1</sup> for molds in pasteurized products: juices, pulps, concentrates, nectars, fruit and vegetable drinks.</p>
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<p>Effectiveness of the pasteurization process on the content of index microorganisms (<b>A</b>–<b>C</b>) and pathogenic microorganisms (<b>D</b>–<b>F</b>) of 6 treatments of orange and carrot nectar, treated by vacuum cooking. Evolution of the content of total mesophilic aerobic microorganisms (<b>A</b>), molds (<b>B</b>), yeasts (<b>C</b>), Enterobacteriaceae (<b>D</b>), <span class="html-italic">Escherichia coli</span> (<b>E</b>) and <span class="html-italic">Staphylococcus aureus</span> (<b>F</b>). T1: 92 °C/3.3 min, T2: 90 °C/10.3 min, T3: 88 °C/32.7 min, T4: 70 °C/2.3 min, T5: 65 °C/11.4 min, T6: 60 °C/56.6 min. INEN standard limit &lt; 10 CFU·mL<sup>−1</sup> for index microorganisms in pasteurized products and &lt; 3 CFU·mL<sup>−1</sup> for pathogenic microorganisms.</p>
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<p>Effectiveness of the pasteurization process on the content of index microorganisms (<b>A</b>–<b>C</b>) and pathogenic microorganisms (<b>D</b>–<b>F</b>) of 6 treatments of orange and carrot nectar, treated by vacuum cooking. Evolution of the content of total mesophilic aerobic microorganisms (<b>A</b>), molds (<b>B</b>), yeasts (<b>C</b>), Enterobacteriaceae (<b>D</b>), <span class="html-italic">Escherichia coli</span> (<b>E</b>) and <span class="html-italic">Staphylococcus aureus</span> (<b>F</b>). T1: 92 °C/3.3 min, T2: 90 °C/10.3 min, T3: 88 °C/32.7 min, T4: 70 °C/2.3 min, T5: 65 °C/11.4 min, T6: 60 °C/56.6 min. INEN standard limit &lt; 10 CFU·mL<sup>−1</sup> for index microorganisms in pasteurized products and &lt; 3 CFU·mL<sup>−1</sup> for pathogenic microorganisms.</p>
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<p>Descriptive parameters of sensory evaluation of orange and carrot nectars, treated by vacuum cooking. T1: 92 °C/3.3 min; T2: 90 °C/10.3 min; T3: 88 °C/32.7 min; T4: 70 °C/2.3 min; T5: 65 °C/11.4 min; T6: 60 °C/56.6 min.</p>
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<p>Hedonic parameters for sensory evaluation of orange and carrot nectars, treated by vacuum cooking. T1: 92 °C/3.3 min; T2: 90 °C/10.3 min; T3: 88 °C/32.7 min; T4: 70 °C/2.3 min; T5: 65 °C/11.4 min; T6: 60 °C/56.6 min, control. a, b, c: Significant differences (<span class="html-italic">p</span> &lt; 0.05) between thermal treatments (T1, T2, T3, T4. T5, T6).</p>
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11 pages, 609 KiB  
Article
The Dose Response Effects of Partially Hydrolyzed Guar Gum on Gut Microbiome of Healthy Adults
by Megan Edelman, Qi Wang, Rylee Ahnen and Joanne Slavin
Appl. Microbiol. 2024, 4(2), 720-730; https://doi.org/10.3390/applmicrobiol4020049 - 27 Apr 2024
Viewed by 1481
Abstract
Partially hydrolyzed guar gum (PHGG) is a water-soluble, prebiotic fiber that is used in foods and supplements. The effects of PHGG and its role in gut health are still being studied. The purpose of this study was to evaluate changes in the gut [...] Read more.
Partially hydrolyzed guar gum (PHGG) is a water-soluble, prebiotic fiber that is used in foods and supplements. The effects of PHGG and its role in gut health are still being studied. The purpose of this study was to evaluate changes in the gut microbiome composition of healthy individuals in response to low-dose PHGG supplementation compared with a low fiber diet. A randomized, double-blind, placebo-controlled crossover study was performed on 33 healthy subjects (17 males, 16 females). Each subject completed three 14-day treatment periods with a 2-week washout between each period. Treatments included supplementation with 3 g PHGG, 6 g PHGG, or a placebo. During all periods, the participants followed a low fiber diet (≤14 g/day). Stools were collected on days 0 and 14 of each period. Gut microbiome profiling was performed using 16S rRNA sequencing. Stools were assessed by investigators with the Bristol Stool Form Scale as a secondary outcome. Saliva cortisol was also measured as a secondary outcome. Supplementation of 3 g and 6 g PHGG significantly increased Verrucomicrobia on day 14 when compared to the placebo (p = 0.0066 and p = 0.0068, respectively). On the genus level, Akkermansia was significantly increased on day 14 with both the 3 g and 6 g PHGG doses (p = 0.0081 and p = 0.0083). Faecalibacterium was significantly decreased on day 14 with 3 g PHGG (p = 0.0054). Supplementing with low doses of PHGG has the potential to cause shifts in the gut microbiome composition. By increasing beneficial microbes, PHGG can improve the microbiome composition of healthy individuals and may play a role in the treatment of inflammatory gastrointestinal diseases. Full article
(This article belongs to the Special Issue Human Microbiota Influence on Human Health Status 2.0)
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<p>Timeline of the PHGG treatment delivery and washout periods.</p>
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16 pages, 2403 KiB  
Article
Impact of Carao (Cassia grandis) on Lactobacillus plantarum Immunomodulatory and Probiotic Capacity
by Jhunior Marcia, Hector Manuel Zumbado, Manuel Álvarez Gil, Daniel Martín-Vertedor, Ismael Montero-Fernández, Ajitesh Yadav and Ricardo S. Aleman
Appl. Microbiol. 2024, 4(2), 704-719; https://doi.org/10.3390/applmicrobiol4020048 - 22 Apr 2024
Viewed by 963
Abstract
Lactobacillus plantarum has beneficial effects on the reduction of symptoms of poor lactose digestion and hypercholesterolemia, removal of the duration and severity of diarrheal processes, improvement of the intestinal permeability barrier, prevention of some types of cancer by adsorption or inactivation of genotoxic [...] Read more.
Lactobacillus plantarum has beneficial effects on the reduction of symptoms of poor lactose digestion and hypercholesterolemia, removal of the duration and severity of diarrheal processes, improvement of the intestinal permeability barrier, prevention of some types of cancer by adsorption or inactivation of genotoxic agents, increased resistance to intestinal and extraintestinal infections, attenuation of inflammatory bowel disease, and prevention of allergies (especially food). On the other hand, carao (Cassia grandis) has shown remarkable nutritious content with influential dietary applications. As a result, this investigation aimed to explore the effect of Cassia grandis pulp on viability of Lactobacillus plantarum under gastrointestinal conditions, immunomodulatory capacity, and probiotic potential. Adding carao to the medium under different experimental conditions, including rich and minimal culture media and a gastrointestinal digestion process of skimmed milk, did not substantially affect Lactobacillus plantarum’s growth but prolonged its viability. The administration of Lactobacillus plantarum with carao in mice did not induce a proinflammatory response at a systemic level. Still, it did cause an increase in the production of immunoregulatory cytokines. Also, the viability of TSB broth was improved by adding carao. Carao improved the growth of acid tolerance, bile tolerance, growth in TSB broth, and NaCl resistance. According to the results, carao may enhance the characteristics of L. plantarum when enriching fermented dairy products. Full article
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<p>Bile tolerance (0.3% oxgalt) of <span class="html-italic">L. plantarum</span> in MRS broth as influenced by carao concentration over 8 h. Ca = carao concentration at 1%, 2%, and 5%. * Treatments were not stadistical different.</p>
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<p>Acid tolerance (pH 2) of <span class="html-italic">L. plantarum</span> in MRS broth as influenced by ingredients over 30 min. Error bars represent standard deviation. C = control, Ca = carao con-centration at 1%, 2%, and 5%. * Treatments were not stadistical different.</p>
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<p>Resistance to NaCl of <span class="html-italic">L. plantarum</span>. * Average of three replicates. Ca = carao con-centration at 1%, 2%, and 5%.</p>
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<p>The growth of <span class="html-italic">L. plantarum</span> in TSB (<b>A</b>) and LPSM (<b>B</b>).</p>
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<p>Survival of <span class="html-italic">L. plantarum</span> in a gastrointestinal digestion simulation test in the absence and presence of carao. No statistical difference was found between control samples and carao samples.</p>
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<p>Levels of TNF-a in the cecal contents of uninfected mice (white bars) and mice infected with <span class="html-italic">Y. enterocolitica</span> (black bars). L.P. = <span class="html-italic">Lactobacillus plantarum;</span> C. = Carao (<span class="html-italic">Cassia grandis</span>).</p>
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<p>Levels of IL-10 in the cecal contents of uninfected mice (white bars) and mice infected with <span class="html-italic">Y. enterocolitica</span> (black bars). L.P. = <span class="html-italic">Lactobacillus plantarum</span>; C. = Carao (<span class="html-italic">Cassia grandis</span>).</p>
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<p>Levels of IgA in the cecal contents of uninfected mice (white bars) and mice infected with <span class="html-italic">Y. enterocolitica</span> (black bars). L.P. = <span class="html-italic">Lactobacillus plantarum;</span> C. = Carao (<span class="html-italic">Cassia grandis</span>).</p>
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<p>Levels of TNF-a in the plasma contents of uninfected mice (white bars) and mice infected with <span class="html-italic">Y. enterocolitica</span> (black bars). L.P. = <span class="html-italic">Lactobacillus plantarum;</span> C. = Carao (<span class="html-italic">Cassia grandis</span>). No statistical difference was found between control samples and carao samples.</p>
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<p>Levels of IL-10 in the plasma contents of uninfected mice (white bars) and mice infected with <span class="html-italic">Y. enterocolitica</span> (black bars). L.P. = <span class="html-italic">Lactobacillus plantarum</span>; C. = Carao (<span class="html-italic">Cassia grandis</span>). No statistical difference was found between control samples and carao samples among infected mice.</p>
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<p>Levels of INF-y in the plasma contents of uninfected mice (white bars) and mice infected with <span class="html-italic">Y. enterocolitica</span> (black bars). L.P. = <span class="html-italic">Lactobacillus plantarum;</span> C. = Carao (<span class="html-italic">Cassia grandis</span>).</p>
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22 pages, 4109 KiB  
Article
Diversity of Microbial Communities in Trade Wastes—Implications for Treatments and Operations
by Jake A. K. Elliott, Christian Krohn and Andrew S. Ball
Appl. Microbiol. 2024, 4(2), 682-703; https://doi.org/10.3390/applmicrobiol4020047 - 19 Apr 2024
Viewed by 1112
Abstract
Industrial wastewaters display a complex and diverse range of physicochemical properties that are measured, studied, and treated by businesses and water service providers. Less frequently measured are the microbial communities in these wastes, despite possible implications for health, equipment maintenance, and the environment. [...] Read more.
Industrial wastewaters display a complex and diverse range of physicochemical properties that are measured, studied, and treated by businesses and water service providers. Less frequently measured are the microbial communities in these wastes, despite possible implications for health, equipment maintenance, and the environment. This study aimed to assess the microbial communities of eighteen raw and discharge-ready wastewaters across eleven industrial sites to compare the microbial compositions of these wastewaters across different industry sectors, on-site treatment levels, and other wastewater components. The potential for variance in the biomethane yield, depending on microbial communities, was also measured. Using targeted sequencing, a unique taxonomy was identified, including genera linked to animals (Acetitomaculum, Lactobacillus, NK4A214, Prevotella, and Shuttleworthia), cooling water (Bosea, Legionella, Methyloversatilis, and Reyranella), and extreme conditions (Alkalibacillus, Geobacillus, Halorubrum, and Pyrobaculum). However, the compositions of the microbial communities were not found to be directly correlated to industry sector or on-site treatment levels, nor were they found to have a direct effect on the biomethane potential. However, the presence of certain individual taxa is linked to the methane yield and treatment status and may be explained in the context of physicochemical properties while serving as potential markers for identifying, improving, or developing on-site processes. Full article
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<p>Diversity measurements of microbial communities sequenced from wastewater samples. Colour of box-plot denotes whether sample was measured before or after on-site treatment; colour and shape of dots depict level of methane yield in BMP tests.</p>
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<p>PCA of microbial communities in wastewater samples. Circles represent untreated streams, squares represent wastewater ready for discharge to sewers (treated), and colours denote sites. 5C represents the source-separated waste from Site 5. The letter at each point denotes a high, medium, or low (H, M, or L, respectively) gas yield in BMP tests. Groups shown by ellipses; 12.6% and 11.5% of the variance between samples are mapped by the x- and y-axes, respectively.</p>
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<p>Genera with statistically significant (<span class="html-italic">p</span> &lt; 0.05) differences in relative abundance in untreated samples relative to treated samples. Samples limited to sites with both treated and untreated samples available. Y-axis shows log-fold change in relative abundance in untreated samples vs. treated samples. Positive values, in brown, denote genera more abundant in untreated samples; negative values, in blue, denote genera more abundant in treated samples; <span class="html-italic">n</span> = 12.</p>
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<p>Genera with statistically significant (<span class="html-italic">p</span> &lt; 0.05) differences in relative abundance. Y-axis shows log-fold change in relative abundance in high-yielding samples relative to low-yielding samples. Positive values, in green, denote genera more abundant in untreated samples; negative values, in red, denote genera more abundant in low-yielding samples; <span class="html-italic">n</span> = 16.</p>
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<p>Abundance plot at phylum level, showing sites, treatment status, and level of gas yield from BMP tests. Proteobacteria were the most highly abundant across the samples. Phylum abundance had no significant difference between treatment levels.</p>
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<p>Canonical correspondence analysis (CCA) plots of abundances (Bray–Curtis dissimilarities) of all the samples, showing the 10 most common phyla (<b>a</b>) and the influence of the measured chemical data on their abundance (<b>b</b>). Plot b axes are at a smaller scale for clarity. CCA1 represents 31.3% of the inertia; CCA2 represents 19.9%.</p>
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<p>Abundance plots at genus level, showing sites, treatment status, and level of gas yield from BMP tests. Plot is separated into groups (<b>a</b>–<b>d</b>) as identified in PCA (<a href="#applmicrobiol-04-00047-f002" class="html-fig">Figure 2</a>). Genera are ordered by the highest relative abundance in the group.</p>
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17 pages, 2631 KiB  
Article
Bioprospection of Bacterial Strains from Chromite Process Industry Residues from Mexico for Potential Remediation
by Paola Abigail Martínez-Aldape, Mario Enrique Sandoval-Vergara, Reyna Edith Padilla-Hernández, César Augusto Caretta, Julio César Valerdi-Negreros, Pablo Casanova, Magna Maria Monteiro, Claire Gassie, Marisol Goñi-Urriza, Elcia Margareth Souza Brito and Remy Guyoneaud
Appl. Microbiol. 2024, 4(2), 665-681; https://doi.org/10.3390/applmicrobiol4020046 - 18 Apr 2024
Viewed by 896
Abstract
Industrial residues with high concentrations of hexavalent chromium [Cr(VI)], characterized by an alkaline pH (between 9 and 13) and high salinity (around 100 psu), were used as a source for extremophilic chromium-resistant and -reducing microorganisms. An investigation of biodiversity through MiSeq showed the [...] Read more.
Industrial residues with high concentrations of hexavalent chromium [Cr(VI)], characterized by an alkaline pH (between 9 and 13) and high salinity (around 100 psu), were used as a source for extremophilic chromium-resistant and -reducing microorganisms. An investigation of biodiversity through MiSeq showed the presence of 20 bacterial classes, with Bacilli (47%), Negativicutes (15%), Bacteriodia (8%), Gammaproteobacteria (7%) and Clostridia (5%) being the most abundant. The bioprospection allowed the cultivation of 87 heterotrophic bacterial colonies and 17 bacterial isolates at the end of the isolation, and screening procedures were obtained. The isolates were related to Cellulosimicrobium aquatile, C. funkei, Acinetobacter radioresistens, Staphylococcus equorum, S. epidermis, Brachybacterium paraconglometratum, Glutamicibacter creatinolyticus, Pseudomonas songnenensis, Microbacterium algeriense and Pantoea eucalypti, most of them being resistant to Cr(VI). Resistances of up to 400 mg.L1 of chromate were obtained for four related strains (QReMLB55A, QRePRA55, QReMLB33A and QReMLB44C). The C. aquatile strain QReMLB55A and the P. songnenensis strain QReMLB33A were exposed to K2Cr2O7 (200 mg.L1) under optimal conditions, diminishing 94% and 24% of the Cr(VI) in 6 days, respectively. These strains exhibited a high potential for chromium remediation biotechnologies. Full article
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<p>Sampling site. The panel on the top indicates the location of the site (red star) in the state of Guanajuato, between the cities of Leon and San Francesco del Rincon. The middle panel illustrates details of sample collection: photos A and B show the solid residues, and photos C and D show details of the lixiviate samplings. The bottom panel represents the strategies used: diversity analysis through MiSeq (using V4–V5 region); culture and isolation using LB, R2A and NB media; and the assessment of the reduction of and resistance to Cr(VI).</p>
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<p>Major bacterial phyla and classes of the community structure obtained by MiSeq sequencing (this work, samples collected in 2014) as compared to the cloning approach (in 2008, from Brito et al., 2013 [<a href="#B12-applmicrobiol-04-00046" class="html-bibr">12</a>]).</p>
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<p>Maximum-likelihood tree based on the alignment of 720 pb of 16S rRNA gene sequences showing the phylogenetic positions of isolated strains. The strains are indicated in parentheses with the name of the respective species. Bootstrap values (1000 resamplings) are indicated at the nodes.</p>
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<p>Chromium resistance of the 17 isolated bacterial strains at different Cr(VI) concentrations.</p>
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<p>Reduction kinetics of Cr(VI) by the selected isolated bacterial strains, QReMLB55A and QReMLB33A (in LB medium, inoculated with <math display="inline"><semantics> <mrow> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mn>8</mn> </mrow> </msup> <msup> <mrow> <mi mathvariant="normal">c</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">l</mi> <mi mathvariant="normal">l</mi> <mi mathvariant="normal">s</mi> <mo>.</mo> <mi mathvariant="normal">m</mi> <mi mathvariant="normal">L</mi> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>, incubated at 33 °C, with optimal pH and salinity). Error bars come from standard deviation of triplicates.</p>
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15 pages, 1066 KiB  
Article
Molecular Characterization of the Gorgonzola Cheese Mycobiota and Selection of a Putative Probiotic Saccharomyces cerevisiae var. boulardii for Evaluation as a Veterinary Feed Additive
by Samuele Voyron, Francesca Bietto, Mauro Fontana, Elisa Martello, Natascia Bruni and Enrica Pessione
Appl. Microbiol. 2024, 4(2), 650-664; https://doi.org/10.3390/applmicrobiol4020045 - 3 Apr 2024
Viewed by 806
Abstract
Gorgonzola is an Italian “erborinato” blue cheese from cow’s milk, bearing blue-green “parsley-like” spots due to the spread of Penicillium roqueforti mycelium. Due to its pH, water activity, and high nutrient content, as well as the environmental conditions required for its maturation, Gorgonzola [...] Read more.
Gorgonzola is an Italian “erborinato” blue cheese from cow’s milk, bearing blue-green “parsley-like” spots due to the spread of Penicillium roqueforti mycelium. Due to its pH, water activity, and high nutrient content, as well as the environmental conditions required for its maturation, Gorgonzola constitutes an optimal ecological niche supporting the growth of both yeasts and filamentous fungi. Therefore, exploring the abundant mycobiota present in this peculiar habitat is of great interest regarding the search for new probiotic strains. The present investigation aimed to characterize the Gorgonzola mycobiota using both phenotypic (macroscopic and microscopic morphological analyses) and genotypic (DNA barcoding) analyses to find possible putative probiotic strains to be used in veterinary medicine in feed supplements. Among the different isolated filamentous fungi (Mucor and Penicillium) and yeasts (Yarrowia, Debaryomyces, Saccharomyces, and Sporobolomyces), we selected a strain of Saccharomyces cerevisiae var. boulardii. We tested its adaptation to thermal stress and its stability in feed matrices. The overall results highlight that the selected strain is stable for three months and can be considered as a possible candidate for use as a probiotic in veterinary feed supplements. Full article
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<p>Yeast and filamentous fungi isolated from Gorgonzola cheese (Biraghi S.p.a.) and grown in CYGE or Sabouraud agar. Total of 126 fungal strains belonging to phylum of Ascomycota (8 genera, 13 species), <span class="html-italic">Basidiomycota</span> (1 genus, 1 species), and <span class="html-italic">Mucoromycota</span> (1 genus, 4 species) were isolated.</p>
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<p>Survival rate of <span class="html-italic">S. cereviasae var. boulardii</span> in feed mixture during three months of monitoring measured as viable cell count on OGYE agar. Data are results of five different samples and are expressed as CFU/g. Statistical differences to Week 0 are depicted as a different letter. Viability of putative probiotic significantly declines over time but remains above probiotic efficacy threshold of 10<sup>8</sup> CFU/g.</p>
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15 pages, 2891 KiB  
Article
Longitudinal Sequencing and Variant Detection of SARS-CoV-2 across Southern California Wastewater
by Jason A. Rothman, Andrew Saghir, Amity G. Zimmer-Faust, Kylie Langlois, Kayla Raygoza, Joshua A. Steele, John F. Griffith and Katrine L. Whiteson
Appl. Microbiol. 2024, 4(2), 635-649; https://doi.org/10.3390/applmicrobiol4020044 - 29 Mar 2024
Viewed by 756
Abstract
Wastewater-based epidemiology (WBE) is useful for detecting pathogen prevalence and may serve to effectively monitor diseases across broad scales. WBE has been used throughout the COVID-19 pandemic to track disease burden through quantifying SARS-CoV-2 RNA present in wastewater. Aside from case load estimation, [...] Read more.
Wastewater-based epidemiology (WBE) is useful for detecting pathogen prevalence and may serve to effectively monitor diseases across broad scales. WBE has been used throughout the COVID-19 pandemic to track disease burden through quantifying SARS-CoV-2 RNA present in wastewater. Aside from case load estimation, WBE is being used to assay viral genomic diversity and emerging potential SARS-CoV-2 variants. Here, we present a study in which we sequenced RNA extracted from sewage influent obtained from eight wastewater treatment plants representing 16 million people in Southern California from April 2020 to August 2021. We sequenced SARS-CoV-2 with two methods: Illumina Respiratory Virus-Enriched metatranscriptomic sequencing (N = 269), and QIAseq SARS-CoV-2-tiled amplicon sequencing (N = 95). We classified SARS-CoV-2 reads into lineages and sublineages that approximated named variants and identified single nucleotide variants (SNVs), of which many are putatively novel SNVs and SNVs of unknown potential function and prevalence. Through our retrospective study, we also show that several SARS-CoV-2 sublineages were detected in wastewater before clinical detection, which may assist in the prediction of future variants of concern. Lastly, we show that sublineage diversity was similar across Southern California and that diversity changed over time, indicating that WBE is effective across megaregions. As the COVID-19 pandemic moves to new phases, and SARS-CoV-2 variants emerge, monitoring wastewater is important to understand local- and population-level dynamics of the virus. These results will aid in our ability to monitor the evolutionary potential of SARS-CoV-2 and help understand circulating SNVs to further combat COVID-19. Full article
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<p>Stacked bar plots showing the relative abundances of RNA reads mapping to (<b>A</b>) the top 10 most proportionally abundant viruses plus all others in respiratory virus-enriched libraries and (<b>B</b>) SARS-CoV-2 plus other viruses in tiled-amplicon libraries. Plots are faceted by WTP and labeled with sampling date.</p>
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<p>The relative proportional abundance of the ten most-abundant SARS-CoV-2 lineages plus others in (<b>A</b>) respiratory virus-enriched libraries, and (<b>B</b>) tiled-amplicon libraries faceted by WTP and labeled with sampling date. Note that one sample date from the North City Water Reclamation Plant is not shown.</p>
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<p>SARS-CoV-2 sublineages at greater than 0.2% relative abundance (for plot visibility) first detected in wastewater samples in (<b>A</b>) respiratory virus-enriched libraries (IRV) and (<b>B</b>) tiled-amplicon libraries by date; (<b>C</b>) denotes the total number of SARS-CoV-2 sublineages first detected by our wastewater sequencing or clinical samples by IRV or tiled-amplicon libraries, respectively, without the relative abundance cutoff.</p>
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<p>Non-metric multidimensional scaling (NMDS) ordinations of the Bray–Curtis dissimilarities of SARS-CoV-2 sublineages faceted by water treatment plant for (<b>A</b>) respiratory virus-enriched (IRV) and (<b>B</b>) tiled-amplicon libraries. SARS-CoV-2 sublineages did not significantly differ between WTPs (PERMANOVA [IRV: <span class="html-italic">p</span> = 0.07, R<sup>2</sup> = 0.01], [tiled-amplicon: <span class="html-italic">p</span> = 0.58, R<sup>2</sup> = 0.01]) but differed by calendar month (PERMANOVA [IRV: <span class="html-italic">p</span> &lt; 0.001, R<sup>2</sup> = 0.15], [tiled-amplicon: <span class="html-italic">p</span> &lt; 0.001, R<sup>2</sup> = 0.21]). Color and plot labels denote sampling month, and only WTPs with yearlong data are included.</p>
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<p>(<b>A</b>) Number of single nucleotide variants (SNVs) detected at each sample date and (<b>B</b>) nucleotide position across the SARS-CoV-2 genome for all samples colored by library preparation method (IRV signifies Illumina Respiratory Virus enrichment panel); (<b>C</b>,<b>D</b>) indicate the frequency of SNVs detected at each position of the SARS-CoV-2 genome across all respiratory virus-enriched and tiled-amplicon libraries, respectively.</p>
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15 pages, 3262 KiB  
Article
Porphyromonas gingivalis Strain W83 Infection Induces Liver Injury in Experimental Alcohol-Associated Liver Disease (ALD) in Mice
by Yun Zhou, Craig McClain and Wenke Feng
Appl. Microbiol. 2024, 4(2), 620-634; https://doi.org/10.3390/applmicrobiol4020043 - 27 Mar 2024
Viewed by 862
Abstract
The liver plays a vital role in the defense against infections. Porphyromonas gingivalis (P. gingivalis), a dominant etiologic oral bacterium implicated in periodontal disease (PD), has been associated with various systemic diseases. This study aimed to investigate the influence of P. [...] Read more.
The liver plays a vital role in the defense against infections. Porphyromonas gingivalis (P. gingivalis), a dominant etiologic oral bacterium implicated in periodontal disease (PD), has been associated with various systemic diseases. This study aimed to investigate the influence of P. gingivalis on alcohol-associated liver diseases (ALD). Mice were fed a Lieber–DeCarli liquid diet containing 5% ethanol for 10 days after an initial adaptation period on a diet with lower ethanol content for 7 days. Two days before tissue sample collection, the mice were administered P. gingivalis strain W83 (Pg) through intraperitoneal injection (IP). Pair-fed mice with Pg infection (PF+Pg) exhibited an activated immune response to combat infections. However, alcohol-fed mice with Pg infection (AF+Pg) showed liver injury with noticeable abscess lesions and elevated serum alanine aminotransferase (ALT) levels. Additionally, these mice displayed liver infiltration of inflammatory monocytes and significant downregulation of proinflammatory cytokine gene expression levels; and AF+Pg mice also demonstrated increased intrahepatic neutrophil infiltration, as confirmed by chloroacetate esterase (CAE) staining, along with elevated gene expression levels of neutrophil cytosol factor 1 (Ncf1), neutrophilic inflammation driver lipocalin 2 (Lcn2), and complement component C5a receptor 1 (C5ar1), which are associated with neutrophilic inflammation. Interestingly, compared to PF+Pg mice, the livers of AF+Pg mice exhibited downregulation of gene expression levels of NADPH oxidase 2 (Cybb), the leukocyte adhesion molecule Cd18, and the Toll-like receptor adaptor Myd88. Consequently, impaired clearance of P. gingivalis and other bacteria in the liver, increased susceptibility to infections, and inflammation-associated hepatic necrotic cell death were observed in AF+Pg mice, which is likely to have facilitated immune cell infiltration and contributed to liver injury. Furthermore, in addition to the Srebf1/Fasn pathway induced by alcohol feeding, Pg infection also activated carbohydrate response element-binding protein (ChREBP) in AF+Pg mice. In summary, this study demonstrates that P. gingivalis infection, acting as a “second hit”, induces dysfunction of immune response and impairs the clearance of bacteria and infections in alcohol-sensitized livers. This process drives the development of liver injury. Full article
(This article belongs to the Special Issue Human Microbiota Influence on Human Health Status 2.0)
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<p><span class="html-italic">Pg</span> infection of alcohol-fed mice induced liver injury. (<b>A</b>) Experimental diagram. Mice fed with the Lieber–DeCarli liquid diet with/without ethanol (EtOH) for total of 18 days; mice infected with <span class="html-italic">Pg</span> on day 16 (shown by arrow) and sacrificed on day 18. (<b>B</b>) Representative images of livers. (<b>C</b>–<b>E</b>) mice weight loss, liver weights and liver/body weight ratios. (<b>F</b>) Mice spleen weights. (<b>G</b>) Serum ALT values. (<b>H</b>) Serum AST values. Data are expressed as mean ± SEM (<span class="html-italic">n</span> = 6–7). One-way ANOVA with Tukey’s post-hoc test (marked as *) or Two-tailed unpaired t test (marked as #) (* or # <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p><span class="html-italic">Pg</span> infection of alcohol-fed mice induced liver infiltration of inflammatory monocytes/macrophages and repressed inflammatory cytokine expression in mice livers. (<b>A</b>–<b>H</b>) Relative gene mRNA expression levels in the livers. (<b>I</b>) Representative liver F4/80 macrophage staining; white scale bar is 100 μm. Data are expressed as mean ± SEM (<span class="html-italic">n</span> = 6–7). Groups differ significantly (* or # <span class="html-italic">p</span> &lt; 0.05; ** or ## <span class="html-italic">p</span> &lt; 0.01; *** or ### <span class="html-italic">p</span> &lt; 0.001).</p>
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<p><span class="html-italic">Pg</span> infection of alcohol-fed mice induced neutrophil infiltration to liver and defective clearance of <span class="html-italic">Pg</span> and infections in mice livers. (<b>A</b>–<b>F</b>) Relative liver gene mRNA expression levels. (<b>G</b>,<b>H</b>) Relative liver <span class="html-italic">Pg</span> and universal 16S rRNA levels. (<b>I</b>) Immuno-blot analysis of Lcn2 in the livers. (<b>J</b>) Serum Lcn2 protein levels. (<b>K</b>) Representative liver CAE staining; pictures were taken under 20× magnification power, black scale bar is 100 μm. Data are expressed as mean ± SEM (<span class="html-italic">n</span> = 6–7). Groups differ significantly (* or # <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** or ### <span class="html-italic">p</span> &lt; 0.001).</p>
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<p><span class="html-italic">Pg</span> infection of alcohol-fed mice induced inflammasome activation and cell death in mice livers. (<b>A</b>–<b>E</b>) Relative liver gene mRNA expression levels. (<b>F</b>) Representative liver H and E staining showing necrotic cell death with increased eosinophilia staining in AF+<span class="html-italic">Pg</span> mice (circle line); pictures were taken under 10× magnification power, black scale bar is 100 μm. (<b>G</b>) Representative liver TUNEL staining showing TUNEL-positive apoptosis (arrowheads) and TUNEL-positive pyroptotic cells at a lower staining intensity (arrows); pictures were taken under 40 × magnification power, black scale bar is 50 μm. Data are expressed as mean ± SEM (<span class="html-italic">n</span> = 6–7). Groups differ significantly (* or # <span class="html-italic">p</span> &lt; 0.05, ** or ## <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001).</p>
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<p><span class="html-italic">Pg</span> infection of alcohol-fed mice induced lipogenesis-related gene expression in mice livers. (<b>A</b>–<b>C</b>) Relative liver gene mRNA expression levels. Data are expressed as mean ± SEM (<span class="html-italic">n</span> = 6–7). Groups differ significantly (* <span class="html-italic">p</span> &lt; 0.05, * <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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13 pages, 291 KiB  
Article
In Silico Prophage Analysis of Halobacterium salinarum ATCC 33170
by Danielle L. Peters, Bassel Akache, Wangxue Chen and Michael J. McCluskie
Appl. Microbiol. 2024, 4(2), 607-619; https://doi.org/10.3390/applmicrobiol4020042 - 26 Mar 2024
Viewed by 613
Abstract
The extremophile Halobacterium salinarum is an aerobic archaeon that has adapted to thrive in high-salt environments such as salted fish, hypersaline lakes, and salterns. Halophiles have garnered significant interest due to their unique interactions with bacteriophages known as haloarchaeophages. Studies have identified and [...] Read more.
The extremophile Halobacterium salinarum is an aerobic archaeon that has adapted to thrive in high-salt environments such as salted fish, hypersaline lakes, and salterns. Halophiles have garnered significant interest due to their unique interactions with bacteriophages known as haloarchaeophages. Studies have identified and characterized prophages in halophilic archaea, such as Haloferax volcanii, Haloquadratum walsbyi, and Haloarcula marismortui. Still, an investigation has yet to be conducted into the presence of prophage elements on Halobacterium salinarum ATCC 33170. This is of particular interest to us as we are using this strain as a source of archaeol, as one of the components of our sulfated lactosyl archaeol (SLA) archaeosome adjuvant. Genomic contigs of strain 33170 were bioinformatically assessed for prophage-like features using BLAST, PHASTER, InterProScan, and PHYRE2. A 7 kb region encoding six genes was identified as an incomplete prophage, and the proteins were further analyzed, revealing high homology to proteins encoded by bacteria, archaea, and an IS200 transposon. Restricting the BLASTp database to viruses resulted in hits to both myo- and siphoviral proteins, which would be unusual for an intact prophage. Additionally, no known phage structural proteins were identified in the search, suggesting a low chance that H. salinarum ATCC 33170 harbors a latent prophage. Full article
13 pages, 619 KiB  
Review
The Influence of Technological Shifts in the Food Chain on the Emergence of Foodborne Pathogens: An Overview
by Saja Hamaideh, Amin N. Olaimat, Murad A. Al-Holy, Ahmad Ababneh, Hafiz Muhammad Shahbaz, Mahmoud Abughoush, Anas Al-Nabulsi, Tareq Osaili, Mutamed Ayyash and Richard A. Holley
Appl. Microbiol. 2024, 4(2), 594-606; https://doi.org/10.3390/applmicrobiol4020041 - 25 Mar 2024
Viewed by 1113
Abstract
The transformation of the food chain due to technological advances has had significant implications in regard to food safety. A noteworthy trend in this evolution relates to the emergence of new or previously unseen pathogens within products, thereby altering the landscape of foodborne [...] Read more.
The transformation of the food chain due to technological advances has had significant implications in regard to food safety. A noteworthy trend in this evolution relates to the emergence of new or previously unseen pathogens within products, thereby altering the landscape of foodborne illness epidemiology. The escalating frequency of these events underscores the need for a comprehensive re-evaluation of preventive strategies. The occurrence of novel species of bacteria, viruses, parasites, and unusual biotoxins from unexpected sources has challenged the previous limits that had been set to prevent foodborne illness outbreaks. The repercussions, ranging from detrimental effects on public health to economic burden, are influenced by a myriad of factors affecting the evolution of foodborne pathogens and emerging ailments. Among these factors are shifts in population demographics and behaviors, especially dietary patterns, as well as climate extremes, advances in more precise pathogen detection, microbial adaptation, evolving agricultural practices, and transformative changes within the food industry. This review critically examines the impact of technological metamorphosis along the food chain, encompassing production, processing, handling, packaging, storage, transportation, and industry demographics on the dynamics influencing the emergence of foodborne pathogens. Additionally, potential solutions to mitigate and manage this escalating issue are proposed. Full article
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<p>Factors contributing to the emergence of foodborne pathogens.</p>
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12 pages, 1208 KiB  
Article
Breaking the Mold: Towards Rapid and Cost-Effective Microbial Contamination Detection in Paints and Cosmetics Using ATP-Bioluminescence
by Mira Mutschlechner, Daniela Chisté and Harald Schöbel
Appl. Microbiol. 2024, 4(2), 582-593; https://doi.org/10.3390/applmicrobiol4020040 - 22 Mar 2024
Viewed by 824
Abstract
Traditional culture-based methods, though a “gold standard” for bacterial detection in various industrial sectors, do often not fulfill today’s high requirements regarding rapidity, on-site applicability, and cost-efficiency both during operation and evaluation. Here, the feasibility of using an adenosine triphosphate (ATP)-based assay for [...] Read more.
Traditional culture-based methods, though a “gold standard” for bacterial detection in various industrial sectors, do often not fulfill today’s high requirements regarding rapidity, on-site applicability, and cost-efficiency both during operation and evaluation. Here, the feasibility of using an adenosine triphosphate (ATP)-based assay for determining microbial contaminations in paints and cosmetics was investigated and compared with standard plate count techniques and dipslides. Therefore, we initially determined the level of sensitivity and assessed the accuracy and concordance among the different methods via spiking tests using a mix of frequently abundant bacterial species to simulate microbial contamination. Bioluminescence intensity was linearly proportional to log colony counts over five orders of magnitude (R2 = 0.99), indicating a high level of sensitivity. Overall, the accuracy varied depending on the test specimen, most probably due to matrix-related quenching effects. Although the degree of conformity was consistently higher at target concentrations ≥ 105 CFU·mL−1, microbial contaminations were detectable down to 103 CFU·mL−1, thus meeting the high requirements of various industries. ATP-based results tended to be within an order of magnitude lower than the reference. However, bearing that in mind, the developed assay serves as a rapid, real-time alternative for routine quality control and hygiene monitoring. Full article
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<p>A brief overview of the experimental setup. Different bacterial species were spread on agar plates and a single colony was used to prepare overnight cultures (1). The suspension was then adjusted to defined concentrations (2) and used to generate standard curves (3a). ATP standard curves were generated using pure ATP (3b). For the spiking experiments, the bacterial suspension was used to inoculate the complex matrix samples (4). The cell viability was determined via standard aerobic plate counts (5a), ATP assays (5b) and dipslides (5c). Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>, accessed on 23 February 2024.</p>
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<p>ATP dose-response curve using signal-to-noise ratios (S/N) from RLU and ATP concentrations (nM) (both log-transformed).</p>
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<p>Standard curves for individual bacteria and the mixed bacterial culture. Data represent log-transformed mean values.</p>
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<p>Spiking experiments using wood stain (<b>A</b>), wall paint (<b>B</b>), oil in water (<b>C</b>), and water in oil emulsion (<b>D</b>) as test matrices. Different initial target concentrations were evaluated using ATP assays, plate count techniques, and dipslides. Results represent means (±SD), <span class="html-italic">n</span> = 3.</p>
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19 pages, 2624 KiB  
Article
Green Macroalgae Hydrolysate for Biofuel Production: Potential of Ulva rigida
by Walaa Sayed, Audrey Cabrol, Alaa Salma, Abdeltif Amrane, Maud Benoit, Ronan Pierre and Hayet Djelal
Appl. Microbiol. 2024, 4(2), 563-581; https://doi.org/10.3390/applmicrobiol4020039 - 22 Mar 2024
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Abstract
In this study, the green macroalgae Ulva rigida, which contains 34.9% carbohydrates, underwent treatment with commercial hydrolytic enzymes. This treatment yielded a hydrolysate that contained 23 ± 0.6 g·L−1 of glucose, which was subsequently fermented with Saccharomyces cerevisiae. The fermentation process [...] Read more.
In this study, the green macroalgae Ulva rigida, which contains 34.9% carbohydrates, underwent treatment with commercial hydrolytic enzymes. This treatment yielded a hydrolysate that contained 23 ± 0.6 g·L−1 of glucose, which was subsequently fermented with Saccharomyces cerevisiae. The fermentation process resulted in an ethanol concentration of 9.55 ± 0.20 g·L−1. The optimal conditions for ethanol production by S. cerevisiae were identified as follows: non-sterilized conditions, an absence of enrichment, and using an inoculum size of 118 mg·L−1. Under these conditions, the fermentation of the green macroalgal hydrolysate achieved a remarkable conversion efficiency of 80.78%. The ethanol o/t ratio, namely the ratios of the experimental to theoretical ethanol produced, for Scheffersomyces stipitis, Candida guilliermondii, Kluyveromyces marxianus, and S. cerevisiae after 48 h of fermentation were 52.25, 63.20, 70.49, and 82.87%, respectively. Furthermore, S. cerevisiae exhibited the best outcomes in terms of ethanol production (9.35 g·L−1) and conversion efficiency (80.78%) after 24 h (optimal time) of fermentation. Full article
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Figure 1
<p>Glucose consumption, ethanol, acetic acid, and glycerol production during 48 h of fermentation of algal hydrolysate by <span class="html-italic">S. cerevisiae</span>.</p>
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<p>Glycerol, acetic acid, and ethanol yields (g·g<sup>−1</sup>), after 48 h of fermentation by <span class="html-italic">S. cerevisiae</span> in the algal hydrolysate (<span class="html-fig-inline" id="applmicrobiol-04-00039-i001"><img alt="Applmicrobiol 04 00039 i001" src="/applmicrobiol/applmicrobiol-04-00039/article_deploy/html/images/applmicrobiol-04-00039-i001.png"/></span> ) and the synthetic medium (<span class="html-fig-inline" id="applmicrobiol-04-00039-i002"><img alt="Applmicrobiol 04 00039 i002" src="/applmicrobiol/applmicrobiol-04-00039/article_deploy/html/images/applmicrobiol-04-00039-i002.png"/></span>).</p>
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<p>Growth rate (<b>a</b>), glucose consumption (<b>b</b>), and ethanol production (<b>c</b>) for <span class="html-italic">S. cerevisiae</span> with the non-sterilized and the sterilized algal hydrolysate.</p>
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<p>Glucose consumption (<b>a</b>), ethanol production (<b>b</b>), and cell density (<b>c</b>) for <span class="html-italic">P. stipitis</span>, <span class="html-italic">C. guilliermondii</span>, <span class="html-italic">K</span>. <span class="html-italic">marxianus,</span> and <span class="html-italic">S. cerevisiae</span> during fermentation of algal hydrolysate without sterilization or enrichment and for an inoculum size of 1% (<span class="html-italic">v</span>/<span class="html-italic">v</span>).</p>
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<p>Glycerol, acetic acid, and ethanol yields obtained with the various yeasts at 48 h of fermentation.</p>
Full article ">Figure A1
<p>Simplified design for the protocol used to produce ethanol.</p>
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