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Microorganisms, Volume 8, Issue 10 (October 2020) – 174 articles

Cover Story (view full-size image): Bacteria packaging is a phenomenon observed when undigested bacteria are evacuated in a protozoan’s fecal pellets. The packaged bacteria may be surrounded by a membrane layer that can protect them from physical stress and biocides. Here, we show that the ciliates Tetrahymena pyriformis and T. thermophila can package various species of non-pathogenic bacteria with different characteristics, as previous research in the field has focused almost exclusively on human pathogens. Each of the bacterial strains studied produces a specific pellet morphology, illustrating the complex relationship between bacteria and protozoa. Based on these results, bacteria packaging may be a more widespread phenomenon than previously considered. View this paper
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13 pages, 4041 KiB  
Article
A Peptide Found in Human Serum, Derived from the C-Terminus of Albumin, Shows Antifungal Activity In Vitro and In Vivo
by Tecla Ciociola, Pier Paolo Zanello, Tiziana D’Adda, Serena Galati, Stefania Conti, Walter Magliani and Laura Giovati
Microorganisms 2020, 8(10), 1627; https://doi.org/10.3390/microorganisms8101627 - 21 Oct 2020
Cited by 8 | Viewed by 2443
Abstract
The growing problem of antimicrobial resistance highlights the need for alternative strategies to combat infections. From this perspective, there is a considerable interest in natural molecules obtained from different sources, which are shown to be active against microorganisms, either alone or in association [...] Read more.
The growing problem of antimicrobial resistance highlights the need for alternative strategies to combat infections. From this perspective, there is a considerable interest in natural molecules obtained from different sources, which are shown to be active against microorganisms, either alone or in association with conventional drugs. In this paper, peptides with the same sequence of fragments, found in human serum, derived from physiological proteins, were evaluated for their antifungal activity. A 13-residue peptide, representing the 597–609 fragment within the albumin C-terminus, was proved to exert a fungicidal activity in vitro against pathogenic yeasts and a therapeutic effect in vivo in the experimental model of candidal infection in Galleria mellonella. Studies by confocal microscopy and transmission and scanning electron microscopy demonstrated that the peptide penetrates and accumulates in Candida albicans cells, causing gross morphological alterations in cellular structure. These findings add albumin to the group of proteins, which already includes hemoglobin and antibodies, that could give rise to cryptic antimicrobial fragments, and could suggest their role in anti-infective homeostasis. The study of bioactive fragments from serum proteins could open interesting perspectives for the development of new antimicrobial molecules derived by natural sources. Full article
(This article belongs to the Special Issue Natural Antimicrobial Compounds)
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<p>Time kinetics of K13L killing of <span class="html-italic">C. albicans</span> SC5314 cells. The activity is expressed as percentage killing, calculated as: 100-(average number of colony forming units (CFUs) in the peptide-treated group/average number of CFUs in the control group) × 100. Each experiment was performed in triplicate.</p>
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<p>Far-UV circular dichroism (CD) spectra of K13L (100 μM) in aqueous solution (black line) or K13L (50 μM) in 100 mM sodium dodecyl sulfate (SDS) (red line) 5 days after preparation of the starting aqueous solution (1.58 mM).</p>
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<p>In vivo toxicity of K13L. ●, saline-injected larvae; <tt>▼</tt>, K13L-injected larvae. No significant difference in survival was found by the Mantel–Cox log-rank test.</p>
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<p>In vivo therapeutic activity of K13L. ●, <span class="html-italic">C. albicans</span>-infected, saline-injected larvae; <tt>▼</tt>, <span class="html-italic">C. albicans</span>-infected, K13L-treated larvae. ** significant difference in survival in comparison to the infected, saline-treated group (<span class="html-italic">p</span> = 0.0098), as assessed by the Mantel–Cox log-rank test.</p>
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<p>Transmission electron microscopy of <span class="html-italic">Candida albicans</span> cells treated with peptide K13L. Cells were incubated without (panels <b>A</b> and <b>B</b>) or with (panels <b>C</b> and <b>D</b>) K13L. Microbodies were seen in still intact treated cells. Bar: 1000 nm (panels <b>A</b> and <b>C</b>), 500 nm (panels <b>B</b> and <b>D</b>).</p>
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<p>Scanning electron microscopy of <span class="html-italic">Candida albicans</span> cells untreated (control, panels <b>A</b> and <b>B</b>) or treated with peptide K13L (panels <b>C</b> and <b>D</b>). Gross alterations in cell morphology were observed after treatment with the peptide (panel <b>C</b> and panel <b>D</b>, arrows). Bar: 1 μm.</p>
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<p>Confocal microscopy images of <span class="html-italic">Candida albicans</span> cells treated with fluorescein isothiocyanate (FITC)-labeled K13L for 5 min (panel <b>A</b>), 75 min (panel <b>B</b>), 285 min (panel <b>C</b>), and 315 min, 30 min after addition of propidium iodide (PI) (panel <b>D</b>, FITC, panel <b>E</b>, PI, panel <b>F</b>, merge). Some non-viable yeast cells are already present in the inoculum (panel <b>A</b>, arrows); over time, intracellular localization of FITC-labeled K13L is observed (some cells indicated by arrowheads, panels <b>B</b> and <b>C</b>). Peptide internalization led to cell death, as demonstrated by the merge of green (FITC) and red (PI) signals in panel <b>F</b>).</p>
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25 pages, 3328 KiB  
Review
Retrospective Analysis on Antimicrobial Resistance Trends and Prevalence of β-lactamases in Escherichia coli and ESKAPE Pathogens Isolated from Arabian Patients during 2000–2020
by Mahfouz Nasser, Snehal Palwe, Ram Naresh Bhargava, Marc G. J. Feuilloley and Arun S. Kharat
Microorganisms 2020, 8(10), 1626; https://doi.org/10.3390/microorganisms8101626 - 21 Oct 2020
Cited by 22 | Viewed by 5696
Abstract
The production of diverse and extended spectrum β-lactamases among Escherichia coli and ESKAPE pathogens is a growing threat to clinicians and public health. We aim to provide a comprehensive analysis of evolving trends of antimicrobial resistance and β-lactamases among E. coli and ESKAPE [...] Read more.
The production of diverse and extended spectrum β-lactamases among Escherichia coli and ESKAPE pathogens is a growing threat to clinicians and public health. We aim to provide a comprehensive analysis of evolving trends of antimicrobial resistance and β-lactamases among E. coli and ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acine to bacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) in the Arabian region. A systematic review was conducted in Medline PubMed on papers published between January 2000 and February 2020 on countries in the Arab region showing different antibiotic resistance among E. coli and ESKAPE pathogens. A total of n = 119,144 clinical isolates were evaluated for antimicrobial resistance in 19 Arab countries. Among these clinical isolates, 74,039 belonged to E. coli and ESKAPE pathogen. Distribution of antibiotic resistance among E. coli and ESKAPE pathogens indicated that E. coli (n = 32,038) was the predominant pathogen followed by K. pneumoniae (n = 17,128), P. aeruginosa (n = 11,074), methicillin-resistant S. aureus (MRSA, n = 4370), A. baumannii (n = 3485) and Enterobacter spp. (n = 1574). There were no reports demonstrating Enterococcus faecium producing β-lactamase. Analyses revealed 19 out of 22 countries reported occurrence of ESBL (Extended-Spectrum β-Lactamase) producing E. coli and ESKAPE pathogens. The present study showed significantly increased resistance rates to various antimicrobial agents over the last 20 years; for instance, cephalosporin resistance increased from 37 to 89.5%, fluoroquinolones from 46.8 to 70.3%, aminoglycosides from 40.2 to 64.4%, mono-bactams from 30.6 to 73.6% and carbapenems from 30.5 to 64.4%. An average of 36.9% of the total isolates were reported to have ESBL phenotype during 2000 to 2020. Molecular analyses showed that among ESBLs and Class A and Class D β-lactamases, blaCTX-M and blaOXA have higher prevalence rates of 57% and 52.7%, respectively. Among Class B β-lactamases, few incidences of blaVIM 27.7% and blaNDM 26.3% were encountered in the Arab region. Conclusion: This review highlights a significant increase in resistance to various classes of antibiotics, including cephalosporins, β-lactam and β-lactamase inhibitor combinations, carbapenems, aminoglycosides and quinolones among E. coli and ESKAPE pathogens in the Arab region. Full article
(This article belongs to the Section Antimicrobial Agents and Resistance)
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<p>PRISMA flow diagram for study inclusion. PRISMA = preferred reporting items for systematic reviews and meta-analysis.</p>
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<p>Percentage of distribution of <span class="html-italic">E. coli</span> and ESKAPE pathogens in the Arab region during 2000–2020.</p>
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<p>Antibiotic resistance among <span class="html-italic">E. coli</span> and ESKAPE pathogens in the Arab region (mean percentage) during 2000–2020.</p>
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<p>Geography distribution of ESBL among <span class="html-italic">E. coli</span> and ESKAPE pathogens in the Arab region (mean percentage) during 2000–2020.</p>
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<p>Comparing ESBL producing <span class="html-italic">E. coli</span> and ESKAPE Pathogens during 2000–2020.</p>
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<p>Distribution of β-lactamase genes among <span class="html-italic">E. coli</span> and ESKAPE pathogens in the Arab region.</p>
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<p>Comparing β-lactamase genes among <span class="html-italic">E. coli</span> and ESKAPE pathogens in the Arab region during 2000–2020.</p>
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12 pages, 969 KiB  
Review
A Review of Potential Impacts of Climate Change on Coffee Cultivation and Mycotoxigenic Fungi
by Mira Adhikari, Elizabeth L. Isaac, R. Russell M. Paterson and Mark A. Maslin
Microorganisms 2020, 8(10), 1625; https://doi.org/10.3390/microorganisms8101625 - 21 Oct 2020
Cited by 39 | Viewed by 7385
Abstract
Coffee is one of the most traded commodities in the world. It plays a significant role in the global economy, employing over 125 million people. However, it is possible that this vital crop is threatened by changing climate conditions and fungal infections. This [...] Read more.
Coffee is one of the most traded commodities in the world. It plays a significant role in the global economy, employing over 125 million people. However, it is possible that this vital crop is threatened by changing climate conditions and fungal infections. This paper reviews how suitable areas for coffee cultivation and the toxigenic fungi species of Aspergillus, Penicillium, and Fusarium will be affected due to climate change. By combining climate models with species distribution models, a number of studies have investigated the future distribution of coffee cultivation. Studies predict that suitable coffee cultivation area could drop by ~50% under representation concentration pathway (RCP) 6.0 by 2050 for both Arabica and Robusta. These findings agree with other studies which also see an altitudinal migration of suitable cultivation areas to cooler regions, but limited scope for latitudinal migration owing to coffee’s inability to tolerate seasonal temperature changes. Increased temperatures will see an overall increase in mycotoxin production such as aflatoxins, particularly in mycotoxigenic fungi (e.g., Aspergillus flavus) more suited to higher temperatures. Arabica and Robusta’s limited ability to relocate means both species will be grown in less suitable climates, increasing plant stress and making coffee more susceptible to fungal infection and mycotoxins. Information regarding climate change parameters with respect to mycotoxin concentrations in real coffee samples is provided and how the changed climate affects mycotoxins in non-coffee systems is discussed. In a few areas where relocating farms is possible, mycotoxin contamination may decrease due to the “parasites lost” phenomenon. More research is needed to include the effect of mycotoxins on coffee under various climate change scenarios, as currently there is a significant knowledge gap, and only generalisations can be made. Future modelling of coffee cultivation, which includes the influence of atmospheric carbon dioxide fertilisation and forest management, is also required; however, all indications show that climate change will have an extremely negative effect on future coffee production worldwide in terms of both a loss of suitable cultivation areas and an increase in mycotoxin contamination. Full article
(This article belongs to the Special Issue Coffee, Fungi, Mycotoxins, and Climate Change)
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<p>Present-day and future suitability maps for Arabica and Robusta. A value of 1 indicates a high probability (certainty) of species presence in the region, while a value of 0 indicates a very low probability of species presence on the basis of bioclimate conditions. Future scenarios presented are those of the Intergovernmental Panel on Climate Change (IPCC) (2013) RCP 2.6 and 8.5 for 2070. Source: Adhikari et al. [<a href="#B41-microorganisms-08-01625" class="html-bibr">41</a>].</p>
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16 pages, 3877 KiB  
Article
Non-Invasive Luciferase Imaging of Type I Interferon Induction in a Transgenic Mouse Model of Biomaterial Associated Bacterial Infections: Microbial Specificity and Inter-Bacterial Species Interactions
by Muhammad Imran Rahim, Andreas Winkel, Stefan Lienenklaus, Nico S. Stumpp, Szymon P. Szafrański, Nadine Kommerein, Elmar Willbold, Janin Reifenrath, Peter P. Mueller, Michael Eisenburger and Meike Stiesch
Microorganisms 2020, 8(10), 1624; https://doi.org/10.3390/microorganisms8101624 - 21 Oct 2020
Cited by 2 | Viewed by 2730
Abstract
The performance of biomaterials is often compromised by bacterial infections and subsequent inflammation. So far, the conventional analysis of inflammatory processes in vivo involves time-consuming histology and biochemical assays. The present study employed a mouse model where interferon beta (IFN-β) is monitored as [...] Read more.
The performance of biomaterials is often compromised by bacterial infections and subsequent inflammation. So far, the conventional analysis of inflammatory processes in vivo involves time-consuming histology and biochemical assays. The present study employed a mouse model where interferon beta (IFN-β) is monitored as a marker for non-invasive rapid detection of inflammation in implant-related infections. The mouse model comprises subcutaneous implantation of morphologically modified titanium, followed by experimental infections with four taxonomically diverse oral bacteria: Streptococcus oralis, Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis and Treponema denticola (as mono culture or selected mixed-culture). IFN-β expression increased upon infections depending on the type of pathogen and was prolonged by the presence of the implant. IFN-β expression kinetics reduced with two mixed species infections when compared with the single species. Histological and confocal microscopy confirmed pathogen-specific infiltration of inflammatory cells at the implant-tissue interface. This was observed mainly in the vicinity of infected implants and was, in contrast to interferon expression, higher in infections with dual species. In summary, this non-invasive mouse model can be used to quantify longitudinally host inflammation in real time and suggests that the polymicrobial character of infection, highly relevant to clinical situations, has complex effects on host immunity. Full article
(This article belongs to the Special Issue Biofilm Implant Related Infections)
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<p>Details of cylindrical titanium implants. Holes were drilled in titanium cylinders (<b>A</b>,<b>B</b>). Cylindrical implant contains 24 holes, in the periphery each 0.5 mm in diameter, 1 hole at the bottom 0.8 mm and an opening at the top 3.3 mm (<b>C</b>,<b>D</b>).</p>
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<p>Interferon beta (IFN-β) induction during biomaterial-associated bacterial infections. (<b>A</b>) Black circles in each mouse show areas containing sterile implants or implants infected with <span class="html-italic">S. oralis</span> (<span class="html-italic">So</span>), <span class="html-italic">A. actinomycetemcomitans</span> (<span class="html-italic">Aa</span>), <span class="html-italic">P. gingivalis</span> (<span class="html-italic">Pg</span>) or <span class="html-italic">T. denticola</span> (<span class="html-italic">Td</span>) at day 0. Dashed black circles on day 0 show the regions for infected sham operated tissues. IFN luciferase luminescence intensity around implants (+) and sham-operated tissues (−) is indicated by bioluminescent patches (d2–d21). The illustration shows images from a typical single experiment selected from a group of three animals. In vivo measured bioluminescent signals from the sites of implantations were quantified and are shown here as radiance at the indicated time points (<b>B</b>–<b>F</b>). (<b>B</b>–<b>E</b>), illustrate IFN-β kinetics in response to <span class="html-italic">S. oralis</span> (yellow), <span class="html-italic">A. actinomycetemcomitans</span> (green), <span class="html-italic">P. gingivalis</span> (red), and <span class="html-italic">T. denticola</span> (dark red) infections of subcutaneous implants (circles with border), sham-operated tissues (circles without borders) and from sterile implants (white circles), respectively. (<b>F</b>) IFN-β luciferase activity from sterile implants and implants infected with different pathogens. Three animals, each carrying three implants were used in each group yielding <span class="html-italic">n</span> = 9 biological observations. Error bars indicate mean ± s.e.m. Significance values have been adjusted by the Bonferroni correction for multiple tests. Symbols ***, *, and # indicate <span class="html-italic">p</span> &lt; 0.001, <span class="html-italic">p</span> &lt; 0.05, and significant <span class="html-italic">p</span> values prior to Bonferroni correction, respectively. Black symbols represent significant <span class="html-italic">p</span> values between sterile and infected implants. Colored symbols indicate significant <span class="html-italic">p</span> values for each of the infected implants (<span class="html-italic">S. oralis</span> (yellow), <span class="html-italic">A. actinomycetemcomitans</span> (green), <span class="html-italic">P. gingivalis</span> (red) or <span class="html-italic">T. denticola</span> (dark red)) with sterile implant, respectively (<b>F</b>).</p>
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<p>IFN-β induction upon dual species infections. (<b>A</b>) IFN-β luminescence measured at the indicated time points in days from sterile implants, infected implants (+), infected surgical pouches without implants (−). Bioluminescent images from a typical single experiment. Implantation sites were marked as region of interest and bioluminescent signals were quantified as radiance at the indicated time points (<b>B</b>,<b>C</b>). (<b>B</b>) IFN-β kinetics upon <span class="html-italic">A. actinomycetemcomitans-T. denticola</span> (AaTd) dual species infections of implants (blue squares with borders), tissues (blue squares). (<b>C</b>) IFN-β kinetics upon <span class="html-italic">S. oralis-P. gingivalis</span> (SoPg) dual species infections of implants (purple squares with borders), tissues (purple squares). (<b>D</b>) Comparison of Aa and Td implant infections as single species with AaTd dual species implant infections. (<b>E</b>) Comparison of So and Pg implant infections as single species with SoPg dual species infections. Three animals, each carrying three implants were used in each group yielding n = 9 biological observations. Error bars indicate mean ± s.e.m. Significance values have been adjusted by the Bonferroni correction for multiple tests. Symbols ***, *, and # indicate <span class="html-italic">p</span> &lt; 0.001, <span class="html-italic">p</span> &lt; 0.05, and significant <span class="html-italic">p</span> value prior to Bonferroni correction, respectively. Black symbols represent <span class="html-italic">p</span> values between sterile and infected implants (<b>B</b>,<b>C</b>). Colored symbols indicate <span class="html-italic">p</span> values between implants infected with single species to dual species infected implants (<b>D</b>,<b>E</b>).</p>
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<p>Histological evaluation around sterile and infected implants as well as in areas of infections without implants on day 21. Few immune cells are present at the sterile implant (Ti) tissue interface (<b>A</b>). Large numbers of inflammatory cells (blue nuclei) were present at tissues-implant (Ti) interfaces infected with <span class="html-italic">S. oralis</span> (<b>B</b>), <span class="html-italic">A. actinomycetemcomitans</span> (<b>C</b>), <span class="html-italic">P. gingivalis</span> (<b>D</b>) or <span class="html-italic">T. denticola</span> (<b>H</b>). Tissue infections without implants showed no signs of inflammation (<b>E</b>,<b>F</b>,<b>G</b>,<b>K</b>). Tissue-implant interfaces infected with dual species <span class="html-italic">S. oralis-P. gingivalis</span> (<b>I</b>) and <span class="html-italic">A. actinomycetemcomitans-T.denticola</span> (<b>J</b>) showed huge recruitment of inflammatory cells (blue nuclei). Dual species infected tissues without implants did not exhibit high recruitment of inflammatory cells (<b>L</b>,<b>M</b>). Abbreviations: Ti, site of implantation; AdTi, adipose tissue; skmu, skeletal muscles in the tissue, Ep, epidermis, De, dermis. The dashed border line indicate tissue-implant interface. The scale bar represents 100 micrometers in each case.</p>
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<p>Bacterial infections promote accumulation of inflammatory cells in the implant-tissue interfaces. Confocal microscopic images of sterile titanium implants 21 days after implantation (<b>A</b>), <span class="html-italic">S. oralis</span> infected titanium implant surfaces (<b>B</b>), <span class="html-italic">A. actinomycetemcomitans</span> infected titanium implant surfaces (<b>C</b>), <span class="html-italic">A. actinomycetemcomitans</span> biofilms in the infected peri-implant tissues (<b>D</b>, white arrow), <span class="html-italic">P. gingivalis</span> infected titanium implant surfaces (<b>E</b>), <span class="html-italic">T. denticola</span> infected implant surfaces (<b>F</b>), fine fibrillary material interposed between the implant surface and the connective tissue (<b>G</b>, white arrows). <span class="html-italic">S. oralis-P. gingivalis</span> infected implants (<b>H</b>,<b>I</b>), <span class="html-italic">A. actinomycetemcomitans-T. denticola</span> infected implant surfaces (<b>J</b>). Thick layer of connective tissue (<b>K</b>, white arrow).</p>
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16 pages, 528 KiB  
Article
Effect of a Debaryomyces hansenii and Lactobacillus buchneri Starter Culture on Aspergillus westerdijkiae Ochratoxin A Production and Growth during the Manufacture of Short Seasoned Dry-Cured Ham
by Lucilla Iacumin, Martina Arnoldi and Giuseppe Comi
Microorganisms 2020, 8(10), 1623; https://doi.org/10.3390/microorganisms8101623 - 21 Oct 2020
Cited by 23 | Viewed by 3113
Abstract
Recently, specific dry-cured hams have started to be produced in San Daniele and Parma areas. The ingredients are similar to protected denomination of origin (PDO) produced in San Daniele or Parma areas, and include pork leg, coming from pigs bred in the Italian [...] Read more.
Recently, specific dry-cured hams have started to be produced in San Daniele and Parma areas. The ingredients are similar to protected denomination of origin (PDO) produced in San Daniele or Parma areas, and include pork leg, coming from pigs bred in the Italian peninsula, salt and spices. However, these specific new products cannot be marked as a PDO, either San Daniele or Parma dry cured ham, because they are seasoned for 6 months, and the mark PDO is given only to products seasoned over 13 months. Consequently, these products are called short-seasoned dry-cured ham (SSDCH) and are not branded PDO. During their seasoning period, particularly from the first drying until the end of the seasoning period, many molds, including Eurotium spp. and Penicillium spp., can grow on the surface and work together with other molds and tissue enzymes to produce a unique aroma. Both of these strains typically predominate over other molds. However, molds producing ochratoxins, such as Aspergillus ochraceus and Penicillium nordicum, can simultaneously grow and produce ochratoxin A (OTA). Consequently, these dry-cured hams may represent a potential health risk for consumers. Recently, Aspergillus westerdijkiae has been isolated from SSDCHs, which could represent a potential problem for consumers. Therefore, the aim of this study was to inhibit A. westerdijkiae using Debaryomyces hansenii or Lactobacillus buchneri or a mix of both microorganisms. Six D. hansenii and six L. buchneri strains were tested in vitro for their ability to inhibit A. westerdijkiae. The strains D. hansenii (DIAL)1 and L. buchneri (Lb)4 demonstrated the highest inhibitory activity and were selected for in situ tests. The strains were inoculated or co-inoculated on fresh pork legs for SSDCH production with OTA-producing A. westerdijkiae prior to the first drying and seasoning. At the end of seasoning (six months), OTA was not detected in the SSDCH treated with both microorganisms and their combination. Because both strains did not adversely affect the SSDCH odor or flavor, the combination of these strains are proposed for use as starters to inhibit OTA-producing A. westerdijkiae. Full article
(This article belongs to the Special Issue Food Spoilage Microorganisms: Ecology and Control)
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<p>Short-seasoned dry-cured ham (SSDCH) (<b>a</b>) without; (<b>b</b>) with <span class="html-italic">A. westerdijkiae.</span></p>
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16 pages, 285 KiB  
Review
Control of Francisella tularensis Virulence at Gene Level: Network of Transcription Factors
by Petra Spidlova, Pavla Stojkova, Anders Sjöstedt and Jiri Stulik
Microorganisms 2020, 8(10), 1622; https://doi.org/10.3390/microorganisms8101622 - 21 Oct 2020
Cited by 14 | Viewed by 3727
Abstract
Regulation of gene transcription is the initial step in the complex process that controls gene expression within bacteria. Transcriptional control involves the joint effort of RNA polymerases and numerous other regulatory factors. Whether global or local, positive or negative, regulators play an essential [...] Read more.
Regulation of gene transcription is the initial step in the complex process that controls gene expression within bacteria. Transcriptional control involves the joint effort of RNA polymerases and numerous other regulatory factors. Whether global or local, positive or negative, regulators play an essential role in the bacterial cell. For instance, some regulators specifically modify the transcription of virulence genes, thereby being indispensable to pathogenic bacteria. Here, we provide a comprehensive overview of important transcription factors and DNA-binding proteins described for the virulent bacterium Francisella tularensis, the causative agent of tularemia. This is an unexplored research area, and the poorly described networks of transcription factors merit additional experimental studies to help elucidate the molecular mechanisms of pathogenesis in this bacterium, and how they contribute to disease. Full article
(This article belongs to the Special Issue Tularemia: Pathogenesis, Diagnostic, Prevention, and Treatment)
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33 pages, 6855 KiB  
Article
Deciphering the Infectious Process of Colletotrichum lupini in Lupin through Transcriptomic and Proteomic Analysis
by Guillaume Dubrulle, Adeline Picot, Stéphanie Madec, Erwan Corre, Audrey Pawtowski, Riccardo Baroncelli, Michel Zivy, Thierry Balliau, Gaétan Le Floch and Flora Pensec
Microorganisms 2020, 8(10), 1621; https://doi.org/10.3390/microorganisms8101621 - 21 Oct 2020
Cited by 19 | Viewed by 4413
Abstract
The fungal phytopathogen Colletotrichum lupini is responsible for lupin anthracnose, resulting in significant yield losses worldwide. The molecular mechanisms underlying this infectious process are yet to be elucidated. This study proposes to evaluate C. lupini gene expression and protein synthesis during lupin infection, [...] Read more.
The fungal phytopathogen Colletotrichum lupini is responsible for lupin anthracnose, resulting in significant yield losses worldwide. The molecular mechanisms underlying this infectious process are yet to be elucidated. This study proposes to evaluate C. lupini gene expression and protein synthesis during lupin infection, using, respectively, an RNAseq-based transcriptomic approach and a mass spectrometry-based proteomic approach. Patterns of differentially-expressed genes in planta were evaluated from 24 to 84 hours post-inoculation, and compared to in vitro cultures. A total of 897 differentially-expressed genes were identified from C. lupini during interaction with white lupin, of which 520 genes were predicted to have a putative function, including carbohydrate active enzyme, effector, protease or transporter-encoding genes, commonly described as pathogenicity factors for other Colletotrichum species during plant infection, and 377 hypothetical proteins. Simultaneously, a total of 304 proteins produced during the interaction were identified and quantified by mass spectrometry. Taken together, the results highlight that the dynamics of symptoms, gene expression and protein synthesis shared similarities to those of hemibiotrophic pathogens. In addition, a few genes with unknown or poorly-described functions were found to be specifically associated with the early or late stages of infection, suggesting that they may be of importance for pathogenicity. This study, conducted for the first time on a species belonging to the Colletotrichum acutatum species complex, presents an opportunity to deepen functional analyses of the genes involved in the pathogenicity of Colletotrichum spp. during the onset of plant infection. Full article
(This article belongs to the Section Plant Microbe Interactions)
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Graphical abstract
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<p>Overview of the phenotypic and molecular <span class="html-italic">C. lupini</span> infectious process. (<b>A</b>) Lupin inoculated with water (top) and with RB221 (bottom) at 84 hpi. (<b>B</b>) Germinated conidia (Cn) of the strain RB221 on lupin epidermis with appressorium (Ap) at 12 hpi (top) and formation of a primary hyphae (Ph) and a thinner secondary hyphae (Sh) at 48 hpi (bottom). Fungal structures were colored by lactophenol cotton blue and the length of the scale bar is 10 µm. (<b>C</b>) Evolution of the size of necrosis caused by <span class="html-italic">C. lupini</span> on lupin hypocotyl for 84 hpi. (<b>D</b>) Heatmap of 897 <span class="html-italic">C. lupini</span> DEGs compared to liquid culture (LC) (LFC &lt; −1 and &gt; 1, FDR &lt; 0.05), grouped by putative functional class. Pathogenicity-related genes included stress response genes, Nudix, NEP and other functions described as associated with pathogenicity. Colored bars indicated gene expression by Z-score calculated from normalized reads of DEGs, and ranging from −2 (downregulated gene, blue) to 2 (upregulated gene, red). The green or black rectangles at the right of each gene represent genes respectively predicted as encoding secreted proteins or small secreted proteins.</p>
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<p>Venn diagram showing overlap of the 593 upregulated genes (<b>A</b>), 304 downregulated genes (<b>B</b>) and 304 QPs (<b>C</b>) across infection stages, together with the overlap of genes and proteins based on results from both transcriptomic and proteomic analysis during infectious process (<b>D</b>).</p>
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<p>Significantly-enriched GO terms obtained from the GO enrichment analysis of all DEGs. The three main GO categories represent biological processes (orange), molecular functions (green), and cellular components (yellow). For each GO term, the percentage of up- and down-regulated genes compared to the number of genes in the genome associated with the same GO term is represented. Significant GO terms associated with DEGs were ordered by increasing FDR value.</p>
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<p>Overview of <span class="html-italic">C. lupini</span> expression and synthesis of candidate effectors. Venn diagram showing the overlap between candidate effector-encoding genes upregulated compared to liquid cultures in the RNAseq study and the candidate effector proteins revealed by this study (<b>A</b>). Heatmap of the five quantified proteins associated with candidate effectors function, regarding their abundance and the corresponding transcript expression profile. Hatching areas indicate that data are not available (<b>B</b>). Colored bars indicated gene expression by Z-score calculated from normalized reads, and ranging from −2 (downregulated gene, blue) to 2 (upregulated gene, red), or protein abundance by Z-score calculated from protein log10 abundance, and ranging from −2 (lowest abundance, blue) to 2 (highest abundance, red).</p>
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<p>Overview of <span class="html-italic">C. lupini</span> expression and synthesis of candidate CAZymes. Venn diagram showing the overlap between CAZyme-encoding genes upregulated from RNAseq analysis and the candidate CAZymes proteins revealed by proteomic analysis (<b>A</b>). Heatmap of the 14 quantified proteins associated with CAZyme function, regarding their abundance and the corresponding transcript expression profile. Hatching areas indicate that data are not available (<b>B</b>). Colored bars indicated gene expression by Z-score calculated from normalized reads, and ranging from −2 (downregulated gene, blue) to 2 (upregulated gene, red), or protein abundance by Z-score calculated from protein log10 abundance, and ranging from −2 (lowest abundance, blue) to 2 (highest abundance, red).</p>
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<p>Overview of <span class="html-italic">C. lupini</span> expression and synthesis of candidate peptidases. Boxplot showing the mean abundance of the candidate peptidase from four biological repetitions and quantified by mass spectrometry (<b>A</b>). Venn diagram showing the overlap between peptidase-encoding genes upregulated in the RNAseq analysis and the peptidase proteins revealed by proteomic analysis (<b>B</b>). Heatmap of the 13 candidate peptidases regarding their abundance and their corresponding transcript expression profile. Hatching areas indicate that data are not available (<b>C</b>). Colored bars indicated gene expression by Z-score calculated from normalized reads, and ranging from −2 (downregulated gene, blue) to 2 (upregulated gene, red), or protein abundance by Z-score calculated from protein log10 abundance, and ranging from −2 (lowest abundance, blue) to 2 (highest abundance, red). Asterisks between histograms indicate significant changes over time.</p>
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<p>Overview of <span class="html-italic">C. lupini</span> expression and synthesis of transmembrane transporters. Venn diagram showing the overlap between DEGs and QPs associated with transmembrane transporter functions (<b>A</b>). Heatmap of the 7 candidate transmembrane transporters regarding their protein abundance and the corresponding transcript expression profile. Hatching areas indicate that data are not available (<b>B</b>). Colored bars indicated gene expression by Z-score calculated from normalized reads, and ranging from −2 (downregulated gene, blue) to 2 (upregulated gene, red), or protein abundance by Z-score calculated from protein log10 abundance, and ranging from −2 (lowest abundance, blue) to 2 (highest abundance, red).</p>
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<p>Overview of <span class="html-italic">C. lupini</span> expression and synthesis of genes and proteins associated with secondary metabolism and transcription factors. Boxplots showing the mean abundance of proteins associated with secondary metabolism from four biological repetitions and quantified by mass spectrometry. (<b>A</b>). Heatmap of the two proteins associated with secondary metabolism regarding their abundance and the corresponding transcript expression profile. Hatching areas indicate that data are not available (<b>B</b>). Boxplots showing the mean abundance of the transcription factor from four biological repetitions quantified by mass spectrometry. (<b>C</b>). Colored bars indicated gene expression by Z-score calculated from normalized reads, and ranging from −2 (downregulated gene, blue) to 2 (upregulated gene, red), or protein abundance by Z-score calculated from protein log10 abundance, and ranging from −2 (lowest abundance, blue) to 2 (highest abundance, red). Asterisks between histograms indicate significant changes over time.</p>
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<p>Abundance of representative pathogenesis-related proteins from <span class="html-italic">C. lupini</span> (Nudix, NEP, stress responses (SR) and other pathogenicity proteins (P)) across the infection kinetics. Boxplots show the mean abundance of pathogenesis-related proteins from four biological repetitions quantified by mass spectrometry. Asterisks between histograms indicate significant changes over time (<b>A</b>). Alignment of the protein sequences of the six NEPs differentially expressed in <span class="html-italic">C. lupini</span> during infection. The conserved amino acid residues were represented in green on the identity bar. Residues different from the conserved NEP pattern were identified in red. Asterisks indicate residues characterized as crucial for NEP activity (a), amino acid residues by alanine replacements resulting in abolished (b) or reduced (c) activity [<a href="#B14-microorganisms-08-01621" class="html-bibr">14</a>,<a href="#B73-microorganisms-08-01621" class="html-bibr">73</a>] (<b>B</b>).</p>
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23 pages, 333 KiB  
Review
Rhinovirus Infection in Children with Acute Bronchiolitis and Its Impact on Recurrent Wheezing and Asthma Development
by Carlotta Biagi, Alessandro Rocca, Giulia Poletti, Marianna Fabi and Marcello Lanari
Microorganisms 2020, 8(10), 1620; https://doi.org/10.3390/microorganisms8101620 - 21 Oct 2020
Cited by 21 | Viewed by 3847
Abstract
Acute bronchiolitis represents the leading cause of hospitalization in infants. Together with a respiratory syncytial virus, rhinovirus (RV) is one of the most common pathogens associated with bronchiolitis, and its genetic diversity (>150 types) makes the recurrence of RV infections each year quite [...] Read more.
Acute bronchiolitis represents the leading cause of hospitalization in infants. Together with a respiratory syncytial virus, rhinovirus (RV) is one of the most common pathogens associated with bronchiolitis, and its genetic diversity (>150 types) makes the recurrence of RV infections each year quite typical. The frequency of RV infection and co-infection with other viruses and its impact on the clinical course of bronchiolitis have been studied by several authors with controversial results. Some studies demonstrate that multiple virus infections result in more severe clinical presentation and a higher risk of complications, whereas other studies suggest no influence on clinical course. Moreover, RV bronchiolitis has been reported to potentially contribute to the development of long-term sequelae, such as recurrent wheezing and asthma, in the pediatric population. In the present review, we summarize the most recent findings of the role of RV infection in children with acute bronchiolitis, its impact on subsequent asthma development, and the implication in clinical practice. Full article
(This article belongs to the Special Issue Epidemiology of Enterovirus Disease)
19 pages, 2727 KiB  
Article
Salt Marsh Elevation Drives Root Microbial Composition of the Native Invasive Grass Elytrigia atherica
by Edisa García Hernández, Elena Baraza, Christian Smit, Matty P. Berg and Joana Falcão Salles
Microorganisms 2020, 8(10), 1619; https://doi.org/10.3390/microorganisms8101619 - 21 Oct 2020
Cited by 9 | Viewed by 3398
Abstract
Elytrigia atherica is a native invasive plant species whose expansion on salt marshes is attributed to genotypic and phenotypic adaptations to non-ideal environmental conditions, forming two ecotypes. It is unknown how E. atherica–microbiome interactions are contributing to its adaptation. Here we investigated [...] Read more.
Elytrigia atherica is a native invasive plant species whose expansion on salt marshes is attributed to genotypic and phenotypic adaptations to non-ideal environmental conditions, forming two ecotypes. It is unknown how E. atherica–microbiome interactions are contributing to its adaptation. Here we investigated the effect of sea-water flooding frequency and associated soil (a)biotic conditions on plant traits and root-associated microbial community composition and potential functions of two E. atherica ecotypes. We observed higher endomycorrhizal colonization in high-elevation ecotypes (HE, low inundation frequency), whereas low-elevation ecotypes (LE, high inundation frequency) had higher specific leaf area. Similarly, rhizosphere and endosphere bacterial communities grouped according to ecotypes. Soil ammonium content and elevation explained rhizosphere bacterial composition. Around 60% the endosphere amplicon sequence variants (ASVs) were also found in soil and around 30% of the ASVs were ecotype-specific. The endosphere of HE-ecotype harbored more unique sequences than the LE-ecotype, the latter being abundant in halophylic bacterial species. The composition of the endosphere may explain salinity and drought tolerance in relation to the local environmental needs of each ecotype. Overall, these results suggest that E. atherica is flexible in its association with soil bacteria and ecotype-specific dissimilar, which may enhance its competitive strength in salt marshes. Full article
(This article belongs to the Special Issue Role of Microorganisms in the Evolution of Animals and Plants)
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Figure 1

Figure 1
<p>Principal coordinate analysis based on weighted Unifrac distances of the bacterial community inhabiting the endosphere (spheres), rhizosphere (squares) and bulk soil (triangles) (<b>a</b>). Types of communities were split in two plots to observe the effect of elevation differences on rhizosphere and soil (<b>b</b>) and on endosphere samples (<b>c</b>). Percentage of community variance explained by each axis is indicated in parentheses and PERMANOVA pseudo-F and <span class="html-italic">p</span>-values for elevation and compartment effect are reported in the text. Symbol color indicate sites, symbols in red shades are found at high elevation and blue shade at low elevation.</p>
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<p>Partial distance-based redundancy analysis (db-RDA) for the bacterial communities associated with <span class="html-italic">E. atherica</span> traits and environmental variables based on the Bray–Curtis dissimilarity. SLA, specific leaf area; Biomass, aboveground biomass; MC, Mycorrhizal colonization. C:N ratio, soil total carbon to total nitrogen ratio. FF, Flooding frequency. Percentage of variance explained by each axis is indicated in parentheses. Symbol color indicate sites, symbols in red shades are found at high elevation and blue shade at low elevation.</p>
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<p>Relative ASV composition in <span class="html-italic">Elytrigia atherica</span> endosphere, rhizosphere and soil from each site at high salt marsh elevation (sites H1–H3) and low elevation (L1–L3). (<b>a</b>) Bar plot showing the phyla with at least 0.5% abundance, “Other” indicate the group of taxa with less than 0.5% abundance. (<b>b</b>) Phyla associated with either high or low elevation in each type of sample. Box plot shows root-mean-squared error resulted of the forward selection method. The apparent discrimination accuracy of these balances is 1.</p>
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<p>Heat-maps based on pair-wise SIMPER analysis showing the scaled abundances of the first 30 amplicon sequence variants (ASVs) that are primarily responsible for differences in bacterial community composition between high and low elevation in three types of communities: Soil (<b>A</b>), Rhizosphere (<b>B</b>) and endosphere (<b>C</b>). Sites label is located at the top of each column (H = high elevation; L = low elevation). The colors of the taxa names indicate the Phylum to which they belong.</p>
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<p>Differences in endosphere bacterial composition in each <span class="html-italic">E. atherica</span> ecotype. Venn diagram showing the proportion of the endosphere ASVs shared with rhizosphere and soil and exclusively found in inner root in HE ecotype (panel <b>a</b>) and LE ecotype (panel <b>b</b>). Venn diagram showing the proportion of shared endosphere ASVs among elevations (panel <b>c</b>). Mean relative abundance of the core bacterial genera at each elevation (panel <b>d</b>).</p>
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<p>Potential function differences among elevations in each type of community. (<b>a</b>) Relative abundance of different functions based on the FAPROTAX database in the three types of communities. Elevation effect was tested with aligned rank transform for non-parametric factorial and significant differences are indicated with asterisks. Triangle symbols indicate potential functions that were increased in sites with a tendency to be higher in high or low elevation sites. (<b>b</b>) Potential soil denitrification activity. Different letters indicate significant difference among elevations (t-Welch test <span class="html-italic">p</span> &lt; 0.05).</p>
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22 pages, 4534 KiB  
Article
Use of Exopolysaccharide-Synthesizing Lactic Acid Bacteria and Fat Replacers for Manufacturing Reduced-Fat Burrata Cheese: Microbiological Aspects and Sensory Evaluation
by Giuseppe Costantino, Maria Calasso, Fabio Minervini and Maria De Angelis
Microorganisms 2020, 8(10), 1618; https://doi.org/10.3390/microorganisms8101618 - 21 Oct 2020
Cited by 10 | Viewed by 3551
Abstract
This study aimed to set-up a biotechnological protocol for manufacturing a reduced-fat Burrata cheese using semi-skimmed milk and reduced-fat cream, in different combinations with exopolysaccharides-synthesizing bacterial starters (Streptococcus thermophilus, E1, or Lactococcus lactis subsp. lactis and Lc. lactis subsp. cremoris [...] Read more.
This study aimed to set-up a biotechnological protocol for manufacturing a reduced-fat Burrata cheese using semi-skimmed milk and reduced-fat cream, in different combinations with exopolysaccharides-synthesizing bacterial starters (Streptococcus thermophilus, E1, or Lactococcus lactis subsp. lactis and Lc. lactis subsp. cremoris, E2) and carrageenan or xanthan. Eight variants of reduced-fat cheese (fat concentration 34–51% lower than traditional full-fat Burrata cheese, used as the control) were obtained using: (i) semi-skimmed milk and reduced-fat cream alone (RC) or in combination with (ii) xanthan (RCX), (iii) carrageenan (RCC), (iv) starter E1 (RCE1), (v) starter E2 (RCE2), (vi) both starters (RCE1-2), (vii) E1 and xanthan (RCXE1), or E1 and carrageenan (RCCE1). Post-acidification occurred for the RCC, RCX, and RCE2 Burrata cheeses, due to the higher number of mesophilic cocci found in these cheeses after 16 days of storage. Overall, mesophilic and thermophilic cocci, although showing cheese variant-depending dynamics, were dominant microbial groups, flanked by Pseudomonas sp. during storage. Lactobacilli, increasing during storage, represented another dominant microbial group. The panel test gave highest scores to RCE1-2 and RCXE1 cheeses, even after 16 days of storage. The 16S-targeted metagenomic analysis revealed that a core microbiota (S. thermophilus, Streptococcus lutetiensis, Lc. lactis, Lactococcus sp., Leuconostoc lactis, Lactobacillus delbrueckii, and Pseudomonas sp.), characterized the Burrata cheeses. A consumer test, based on 105 people, showed that more than 50% of consumers did not distinguish the traditional full-fat from the RCXE1 reduced-fat Burrata cheese. Full article
(This article belongs to the Special Issue Microbial Populations of Fermented Foods)
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Figure 1

Figure 1
<p>Values of pH (<b>A</b>) and total titratable acidity (TTA) (<b>B</b>), determined after 1 (T1), 8 (T8), and 16 (T16) days of storage at 4 °C, in the Burrata cheeses made from whole milk and cream (Control); semi-skimmed milk and reduced-fat cream (RC); semi-skimmed milk and reduced-fat cream diluted with xanthan (RCX) or carrageenan (RCC); semi-skimmed milk added with exopolysaccharide producing starter E1 and reduced-fat cream (RCE1); semi-skimmed milk and reduced-fat cream added with exopolysaccharide producing starter E2 (RCE2); semi-skimmed milk and reduced-fat cream both added with E1 and E2 (RCE1-2); semi-skimmed milk added with E1 and reduced-fat cream diluted with xanthan (RCXE1) or carrageenan (RCCE1). Within the same thesis, bars labelled with the same letter represent not significantly (<span class="html-italic">p</span> &gt; 0.05) different values.</p>
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<p>Concentration of proteins in the pH 4.6-insoluble (<b>A</b>) and pH 4.6-soluble nitrogen fraction (<b>B</b>), determined after 1 (T1) and 16 (T16) days of storage at 4 °C, in the Burrata cheeses made from whole milk and cream (Control); semi-skimmed milk and reduced-fat cream (RC); semi-skimmed milk and reduced-fat cream diluted with xanthan (RCX) or carrageenan (RCC); semi-skimmed milk added with exopolysaccharide producing starter E1 and reduced-fat cream (RCE1); semi-skimmed milk and reduced-fat cream added with exopolysaccharide producing starter E2 (RCE2); semi-skimmed milk and reduced-fat cream both added with E1 and E2 (RCE1-2); semi-skimmed milk added with E1 and reduced-fat cream diluted with xanthan (RCXE1) or carrageenan (RCCE1). Within the same thesis, bars labelled with the same letter represent not significantly (<span class="html-italic">p</span> &gt; 0.05) different values.</p>
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<p>Cell densities of microbial groups, determined after 1 (T1), 8 (T8), and 16 (T16) days of storage at 4 °C, in the Burrata cheeses made from whole milk and cream (Control); semi-skimmed milk and reduced-fat cream (RC); semi-skimmed milk and reduced-fat cream diluted with xanthan (RCX) or carrageenan (RCC); semi-skimmed milk added with exopolysaccharide producing starter E1 and reduced-fat cream (RCE1); semi-skimmed milk and reduced-fat cream added with exopolysaccharide producing starter E2 (RCE2); semi-skimmed milk and reduced-fat cream both added with E1 and E2 (RCE1-2); semi-skimmed milk added with E1 and reduced-fat cream diluted with xanthan (RCXE1) or carrageenan (RCCE1). Within the same panel (showing a given microbial group), bars labelled with one or more common letters represent not significantly (<span class="html-italic">p</span> &gt; 0.05) different values.</p>
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<p>Cell densities of microbial groups, determined after 1 (T1), 8 (T8), and 16 (T16) days of storage at 4 °C, in the Burrata cheeses made from whole milk and cream (Control); semi-skimmed milk and reduced-fat cream (RC); semi-skimmed milk and reduced-fat cream diluted with xanthan (RCX) or carrageenan (RCC); semi-skimmed milk added with exopolysaccharide producing starter E1 and reduced-fat cream (RCE1); semi-skimmed milk and reduced-fat cream added with exopolysaccharide producing starter E2 (RCE2); semi-skimmed milk and reduced-fat cream both added with E1 and E2 (RCE1-2); semi-skimmed milk added with E1 and reduced-fat cream diluted with xanthan (RCXE1) or carrageenan (RCCE1). Within the same panel (showing a given microbial group), bars labelled with one or more common letters represent not significantly (<span class="html-italic">p</span> &gt; 0.05) different values.</p>
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<p>Average values of overall acceptability evaluated through panel test, carried out after 1 (T1), 8 (T8), and 16 (T16) days of storage at 4 °C on the Burrata cheeses made from whole milk and cream (Control); semi-skimmed milk and reduced-fat cream (RC); semi-skimmed milk and reduced-fat cream diluted with xanthan (RCX) or carrageenan (RCC); semi-skimmed milk added with exopolysaccharide producing starter E1 and reduced-fat cream (RCE1); semi-skimmed milk and reduced-fat cream added with exopolysaccharide producing starter E2 (RCE2); semi-skimmed milk and reduced-fat cream both added with E1 and E2 (RCE1-2); semi-skimmed milk added with E1 and reduced-fat cream diluted with xanthan (RCXE1) or carrageenan (RCCE1).Within the same time of analysis, bars labelled with the same letter represent not significantly (<span class="html-italic">p</span> &gt; 0.05) different values.</p>
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<p>Scores and loading plots of the first and second principal components after Principal Component Analysis (PCA) based on the sensory attributes evaluated through panel test. (<b>A</b>) PCA carried out after 1 day; (<b>B</b>) PCA carried out after 8 days; (<b>C</b>) PCA carried out after 16 days of storage at 4 °C of the Burrata cheeses made from whole milk and cream (Control); semi-skimmed milk and reduced-fat cream (RC); semi-skimmed milk and reduced-fat cream diluted with xanthan (RCX) or carrageenan (RCC); semi-skimmed milk added with exopolysaccharide producing starter E1 and reduced-fat cream (RCE1); semi-skimmed milk and reduced-fat cream added with exopolysaccharide producing starter E2 (RCE2); semi-skimmed milk and reduced-fat cream both added with E1 and E2 (RCE1-2); semi-skimmed milk added with E1 and reduced-fat cream diluted with xanthan (RCXE1) or carrageenan (RCCE1).</p>
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<p>Relative abundance (%) of the main bacterial Operational Taxonomic Units (OTUs) assigned at the highest possible taxonomic level found after 1 (T1) and 16 (T16) days of storage at 4 °C, in the Burrata cheeses made from: whole milk and cream (Control); semi-skimmed milk and reduced-fat cream (RC); semi-skimmed milk and reduced-fat cream both added with E1 and E2 (RCE1-2); semi-skimmed milk added with E1 and reduced-fat cream diluted with xanthan (RCXE1). “Others” represent OTUs found at relative abundance less than 0.05%.</p>
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<p>Scores (<b>A</b>) and loading (<b>B</b>) plots of first and second principal components after Principal Component Analysis based on microbiological (cell densities, OTU relative abundance) and biochemical (pH, TTA, concentrations of proteins in pH 4.6-soluble and -insoluble fraction, concentration of peptides in pH 4.6-soluble fraction) characteristics determined after 1 (T1) and 16 (T16) days of storage at 4 °C on the Burrata cheeses made from: whole milk and cream (Control); semi-skimmed milk and reduced-fat cream (RC); semi-skimmed milk and reduced-fat cream both added with E1 and E2 (RCE1-2); semi-skimmed milk added with E1, and reduced-fat cream diluted with xanthan (RCXE1). Total titratable acidity, TTA; total mesophilic microorganisms, Total_meso; mesophilic lactobacilli, M_lb; thermophilic lactobacilli, T_lb; mesophilic cocci, M_cocci; thermophilic cocci, T_cocci; enterococci, Ent; presumptive <span class="html-italic">Pseudomonas</span> sp., Pse; staphylococci, Staphy; coliforms, Colifo; proteins in insoluble fraction, Inso-P; proteins in soluble fraction, Sol-P; <span class="html-italic">Chryseobacterium</span> sp., C_sp; <span class="html-italic">Flavobacterium</span> sp., F_sp; <span class="html-italic">Anoxybacillus</span> sp., A_sp; <span class="html-italic">Brochothrix</span> sp., Br_sp; <span class="html-italic">Kurthia gibsonii</span>, K_gib; <span class="html-italic">Macrococcus caseolyticus</span>, M_caseo; <span class="html-italic">Carnobacterium</span> sp., Ca_sp; <span class="html-italic">Lactobacillus delbrueckii</span>, L_delbr; <span class="html-italic">Leuconostoc lactis</span>, Le_lactis; <span class="html-italic">Leuconostoc mesenteroides</span>, Le_mese; <span class="html-italic">Lactococcus lactis</span>, Lc_lactis; <span class="html-italic">Lactococcus</span> sp., Lc_sp; <span class="html-italic">Streptococcus lutetiensis</span>, S_lutetie; <span class="html-italic">Streptococcus macedonicus</span>, S_macedo; <span class="html-italic">Streptococcus parauberis</span>, S_parab; <span class="html-italic">Streptococcus thermophilus</span>, (S_thermo); <span class="html-italic">Streptococcus</span> sp. (S_sp); <span class="html-italic">Janthinobacterium</span> sp., J_sp; <span class="html-italic">Aeromonas</span> sp., Aero_sp; <span class="html-italic">Psychromonas arctica</span>, Psy_arctica; <span class="html-italic">Shewanella baltica</span>, She_baltica; <span class="html-italic">Buttiauxella agrestis</span>, B_agre; <span class="html-italic">Enterobacter</span> sp., E_sp; <span class="html-italic">Escherichia coli</span>, E_coli; <span class="html-italic">Acinetobacter</span> sp., A_sp; <span class="html-italic">Moraxella osloensis</span>, M_osloensis; <span class="html-italic">Pseudomonas</span> sp., P_sp.</p>
Full article ">Figure 7 Cont.
<p>Scores (<b>A</b>) and loading (<b>B</b>) plots of first and second principal components after Principal Component Analysis based on microbiological (cell densities, OTU relative abundance) and biochemical (pH, TTA, concentrations of proteins in pH 4.6-soluble and -insoluble fraction, concentration of peptides in pH 4.6-soluble fraction) characteristics determined after 1 (T1) and 16 (T16) days of storage at 4 °C on the Burrata cheeses made from: whole milk and cream (Control); semi-skimmed milk and reduced-fat cream (RC); semi-skimmed milk and reduced-fat cream both added with E1 and E2 (RCE1-2); semi-skimmed milk added with E1, and reduced-fat cream diluted with xanthan (RCXE1). Total titratable acidity, TTA; total mesophilic microorganisms, Total_meso; mesophilic lactobacilli, M_lb; thermophilic lactobacilli, T_lb; mesophilic cocci, M_cocci; thermophilic cocci, T_cocci; enterococci, Ent; presumptive <span class="html-italic">Pseudomonas</span> sp., Pse; staphylococci, Staphy; coliforms, Colifo; proteins in insoluble fraction, Inso-P; proteins in soluble fraction, Sol-P; <span class="html-italic">Chryseobacterium</span> sp., C_sp; <span class="html-italic">Flavobacterium</span> sp., F_sp; <span class="html-italic">Anoxybacillus</span> sp., A_sp; <span class="html-italic">Brochothrix</span> sp., Br_sp; <span class="html-italic">Kurthia gibsonii</span>, K_gib; <span class="html-italic">Macrococcus caseolyticus</span>, M_caseo; <span class="html-italic">Carnobacterium</span> sp., Ca_sp; <span class="html-italic">Lactobacillus delbrueckii</span>, L_delbr; <span class="html-italic">Leuconostoc lactis</span>, Le_lactis; <span class="html-italic">Leuconostoc mesenteroides</span>, Le_mese; <span class="html-italic">Lactococcus lactis</span>, Lc_lactis; <span class="html-italic">Lactococcus</span> sp., Lc_sp; <span class="html-italic">Streptococcus lutetiensis</span>, S_lutetie; <span class="html-italic">Streptococcus macedonicus</span>, S_macedo; <span class="html-italic">Streptococcus parauberis</span>, S_parab; <span class="html-italic">Streptococcus thermophilus</span>, (S_thermo); <span class="html-italic">Streptococcus</span> sp. (S_sp); <span class="html-italic">Janthinobacterium</span> sp., J_sp; <span class="html-italic">Aeromonas</span> sp., Aero_sp; <span class="html-italic">Psychromonas arctica</span>, Psy_arctica; <span class="html-italic">Shewanella baltica</span>, She_baltica; <span class="html-italic">Buttiauxella agrestis</span>, B_agre; <span class="html-italic">Enterobacter</span> sp., E_sp; <span class="html-italic">Escherichia coli</span>, E_coli; <span class="html-italic">Acinetobacter</span> sp., A_sp; <span class="html-italic">Moraxella osloensis</span>, M_osloensis; <span class="html-italic">Pseudomonas</span> sp., P_sp.</p>
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<p>Percentages of consumers expressing compared judgment about appearance (<b>A</b>), texture (<b>B</b>), and odor (<b>C</b>) between the traditional full-fat Burrata cheese (Control) and the reduced-fat Burrata cheese produced from semi-skimmed milk added with E1 and reduced-fat cream diluted with xanthan (RCXE1). Compared judgment was expressed using one of the following phrases: (i) preference for Control; (ii) preference for RCXE1; (iii) no difference between the two cheeses (indifferent).</p>
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19 pages, 2571 KiB  
Article
Screening Fungal Endophytes Derived from Under-Explored Egyptian Marine Habitats for Antimicrobial and Antioxidant Properties in Factionalised Textiles
by Ahmed A. Hamed, Sylvia Soldatou, M. Mallique Qader, Subha Arjunan, Kevin Jace Miranda, Federica Casolari, Coralie Pavesi, Oluwatofunmilay A. Diyaolu, Bathini Thissera, Manal Eshelli, Lassaad Belbahri, Lenka Luptakova, Nabil A. Ibrahim, Mohamed S. Abdel-Aziz, Basma M. Eid, Mosad A. Ghareeb, Mostafa E. Rateb and Rainer Ebel
Microorganisms 2020, 8(10), 1617; https://doi.org/10.3390/microorganisms8101617 - 21 Oct 2020
Cited by 45 | Viewed by 5700
Abstract
Marine endophytic fungi from under-explored locations are a promising source for the discovery of new bioactivities. Different endophytic fungi were isolated from plants and marine organisms collected from Wadi El-Natrun saline lakes and the Red Sea near Hurghada, Egypt. The isolated strains were [...] Read more.
Marine endophytic fungi from under-explored locations are a promising source for the discovery of new bioactivities. Different endophytic fungi were isolated from plants and marine organisms collected from Wadi El-Natrun saline lakes and the Red Sea near Hurghada, Egypt. The isolated strains were grown on three different media, and their ethyl acetate crude extracts were evaluated for their antimicrobial activity against a panel of pathogenic bacteria and fungi as well as their antioxidant properties. Results showed that most of the 32 fungal isolates initially obtained possessed antimicrobial and antioxidant activities. The most potent antimicrobial extracts were applied to three different cellulose containing fabrics to add new multifunctional properties such as ultraviolet protection and antimicrobial functionality. For textile safety, the toxicity profile of the selected fungal extract was evaluated on human fibroblasts. The 21 strains displaying bioactivity were identified on molecular basis and selected for chemical screening and dereplication, which was carried out by analysis of the MS/MS data using the Global Natural Products Social Molecular Networking (GNPS) platform. The obtained molecular network revealed molecular families of compounds commonly produced by fungal strains, and in combination with manual dereplication, further previously reported metabolites were identified as well as potentially new derivatives. Full article
(This article belongs to the Special Issue Microbial Secondary Metabolites and Biotechnology)
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<p>Total antioxidant capacity (TAC) of selected fungal extracts. Results are presented as means ± SD, <span class="html-italic">n</span> = 3) and are expressed as mg ascorbic acid equivalent (AAE)/g extract.</p>
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<p>(<b>A</b>) Molecular network of the organic extracts of 21 biologically active Egyptian fungal strains. Nodes are colour-coded based on fungal strain ID, as shown in <a href="#microorganisms-08-01617-t001" class="html-table">Table 1</a>. The reverse triangle-shaped nodes represent previously reported metabolites identified by Global Natural Products Social Molecular Networking (GNPS)’ libraries. Molecular families are shown in circles. (<b>B</b>) Distribution of unique nodes for each fungal strain observed in the molecular network.</p>
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<p>Selected GNPS clusters representing molecular families: (<b>A</b>) emericellamide cluster, (<b>B</b>) butyrolactone cluster, (<b>C</b>) asteltoxin cluster, (<b>D</b>) epicoccolide cluster, and (<b>E</b>) pseurotin cluster. Nodes depicted by inverted triangular shapes represent hits in the GNPS compound library. Candidate molecular formulae for potential new derivatives highlighted in green.</p>
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3 pages, 184 KiB  
Correction
Correction: Krauss, J., et al. Epichloë Endophyte Infection Rates and Alkaloid Content in Commercially Available Grass Seed Mixtures in Europe. Microorganisms 2020, 8, 498
by Jochen Krauss, Veronika Vikuk, Carolyn A. Young, Markus Krischke, Martin J. Mueller and Katja Baerenfaller
Microorganisms 2020, 8(10), 1616; https://doi.org/10.3390/microorganisms8101616 - 21 Oct 2020
Cited by 1 | Viewed by 2328
Abstract
The authors wish to make the following correction to this paper [...] Full article
(This article belongs to the Special Issue Fungal Endophytes and Their Interactions with Plants)
20 pages, 1803 KiB  
Review
Human mecC-Carrying MRSA: Clinical Implications and Risk Factors
by Carmen Lozano, Rosa Fernández-Fernández, Laura Ruiz-Ripa, Paula Gómez, Myriam Zarazaga and Carmen Torres
Microorganisms 2020, 8(10), 1615; https://doi.org/10.3390/microorganisms8101615 - 20 Oct 2020
Cited by 42 | Viewed by 7079
Abstract
A new methicillin resistance gene, named mecC, was first described in 2011 in both humans and animals. Since then, this gene has been detected in different production and free-living animals and as an agent causing infections in some humans. The possible impact [...] Read more.
A new methicillin resistance gene, named mecC, was first described in 2011 in both humans and animals. Since then, this gene has been detected in different production and free-living animals and as an agent causing infections in some humans. The possible impact that these isolates can have in clinical settings remains unknown. The current available information about mecC-carrying methicillin resistant S. aureus (MRSA) isolates obtained from human samples was analyzed in order to establish its possible clinical implications as well as to determine the infection types associated with this resistance mechanism, the characteristics of these mecC-carrying isolates, their possible relation with animals and the presence of other risk factors. Until now, most human mecC-MRSA infections have been reported in Europe and mecC-MRSA isolates have been identified belonging to a small number of clonal complexes. Although the prevalence of mecC-MRSA human infections is very low and isolates usually contain few resistance (except for beta-lactams) and virulence genes, first isolates harboring important virulence genes or that are resistant to non-beta lactams have already been described. Moreover, severe and even fatal human infection cases have been detected. mecC-carrying MRSA should be taken into consideration in hospital, veterinary and food safety laboratories and in prevention strategies in order to avoid possible emerging health problems. Full article
(This article belongs to the Special Issue Staphylococcal Infections (Host and Pathogenic Factors))
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<p>Clonal complexes (CCs) detected in <span class="html-italic">mecC</span>-MRSA human isolates.</p>
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<p><span class="html-italic">spa</span> types detected in <span class="html-italic">mecC</span>-MRSA isolates of humans. Colors indicate the clonal complexes associated with each <span class="html-italic">spa</span> type: green CC49, red CC130, blue CC425, purple CC599, orange CC1943, black CC2361. The number of isolates of each <span class="html-italic">spa</span> type is indicated in parentheses (to calculate the number of isolates in human case reports, only one isolate from each <span class="html-italic">spa</span> type and each patient was considered)</p>
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19 pages, 6081 KiB  
Article
Metagenomic Insight into Environmentally Challenged Methane-Fed Microbial Communities
by Yue Zheng, Huan Wang, Zheng Yu, Fauzi Haroon, Maria E. Hernández and Ludmila Chistoserdova
Microorganisms 2020, 8(10), 1614; https://doi.org/10.3390/microorganisms8101614 - 20 Oct 2020
Cited by 12 | Viewed by 3487
Abstract
In this study, we aimed to investigate, through high-resolution metagenomics and metatranscriptomics, the composition and the trajectories of microbial communities originating from a natural sample, fed exclusively with methane, over 14 weeks of laboratory incubation. This study builds on our prior data, suggesting [...] Read more.
In this study, we aimed to investigate, through high-resolution metagenomics and metatranscriptomics, the composition and the trajectories of microbial communities originating from a natural sample, fed exclusively with methane, over 14 weeks of laboratory incubation. This study builds on our prior data, suggesting that multiple functional guilds feed on methane, likely through guild-to-guild carbon transfer, and potentially through intraguild and intraspecies interactions. We observed that, under two simulated dioxygen partial pressures—low versus high—community trajectories were different, with considerable variability among the replicates. In all microcosms, four major functional guilds were prominently present, representing Methylococcaceae (the true methanotrophs), Methylophilaceae (the nonmethanotrophic methylotrophs), Burkholderiales, and Bacteroidetes. Additional functional guilds were detected in multiple samples, such as members of Opitutae, as well as the predatory species, suggesting additional complexity for methane-oxidizing communities. Metatranscriptomic analysis suggested simultaneous expression of the two alternative types of methanol dehydrogenases in both Methylococcaceae and Methylophilaceae, while high expression of the oxidative/nitrosative stress response genes suggested competition for dioxygen among the community members. The transcriptomic analysis further suggested that Burkholderiales likely feed on acetate that is produced by Methylococcaceae under hypoxic conditions, while Bacteroidetes likely feed on biopolymers produced by both Methylococcaceae and Methylophilaceae. Full article
(This article belongs to the Special Issue Biology, Diversity, and Ecology of Methanotrophic Bacteria)
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<p>Schematic of the microcosm incubation design. Bottom panel: Four replicate cultures were established at two O<sub>2</sub> tensions, low (LO) and high (HO). Top panel: After 3 initial weeks, weekly transfers were carried out along with DNA/RNA sampling from week 4 through week 14. At week 10, the conditions were switched from LO to HO and from HO to LO, respectively, to mimic environmental perturbance.</p>
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<p>Community dynamics in microcosms transitioning from ‘low’ to ‘high’ (<b>a</b>) and from ‘high’ to ‘low’ (<b>b</b>) oxygen conditions, at the family/order level (left) and at the genus level (right). The switch between the conditions at week 10 is marked by an arrow. R1–R4, replicates.</p>
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<p>A heatmap depicting the similarity among the select Burkholderiales metaganome assembled genomes (MAGs) and the single-species genomes. The upper right half of the matrix depicts the average nucleotide identity (ANI) between pairs of genomes and the bottom left half depicts alignment coverage between pairs of genomes.</p>
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<p>A heatmap depicting the similarity among the select Bacteroidetes MAGs and the single-species genomes. The upper right half of the matrix depicts the average nucleotide identity (ANI) between pairs of genomes and the bottom left half depicts alignment coverage between pairs of genomes.</p>
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<p>A heatmap depicting expression of <span class="html-italic">xoxF</span> and <span class="html-italic">mxaF</span> (log2 of transcripts per million, TPM), normalized by total TPM of the respective family (<span class="html-italic">Methylococcaceae/Methylophilaceae</span>). Note that reads matching the multiple <span class="html-italic">xoxF</span> genes in the <span class="html-italic">Methylophilaceae</span> were summed. The HO8, R1 data were omitted due to poor quality.</p>
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<p>A schematic of carbon transfer among the core functional guilds involved in methane consumption. <span class="html-italic">Methylococcaceae</span> excrete methanol (M) and acetate (A)/other organics that are consumed, respectively, by <span class="html-italic">Methylophilaceae</span> and certain Burkholderiales. <span class="html-italic">Methylococcaceae, Methylophilaceae</span>, and potentially Burkholderiales excrete polymeric substances (P) that are consumed by Bacteroidetes.</p>
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13 pages, 2816 KiB  
Article
Mardivirus Infection and Persistence in Feathers of a Chicken Model Harboring a Local Autoimmune Response
by Gisela F. Erf, Gilles Le Pape, Sylvie Rémy and Caroline Denesvre
Microorganisms 2020, 8(10), 1613; https://doi.org/10.3390/microorganisms8101613 - 20 Oct 2020
Cited by 1 | Viewed by 2561
Abstract
Herpesvirus of turkey (HVT) is commonly used as a vaccine to protect chickens against Marek’s disease. Following vaccination, HVT infects feathers where it can be detected in all chicken lines examined. Unlike the parental Brown line (BL), Smyth line (SL) chickens develop vitiligo, [...] Read more.
Herpesvirus of turkey (HVT) is commonly used as a vaccine to protect chickens against Marek’s disease. Following vaccination, HVT infects feathers where it can be detected in all chicken lines examined. Unlike the parental Brown line (BL), Smyth line (SL) chickens develop vitiligo, due to autoimmune destruction of melanocytes in feathers. Previous reports showed a strong inflammatory response in Smyth chickens’ feathers at vitiligo onset, that subsided once melanocytes were destroyed, and depigmentation was complete. Here, we questioned whether the local autoimmune response in the Smyth model influences HVT infection and persistence in feathers. For this, one-day-old SL and BL chickens were vaccinated with Newcastle disease (rHVT-ND). Vitiligo was scored and HVT loads in pigmented and non-pigmented growing feathers were quantified regularly over 20 weeks. Chickens of both lines showed moderate HVT loads in feathers. At the onset of active vitiligo, the HVT load was significantly higher in SL compared to BL feathers. However, no difference in HVT loads was noticed between pigmented and non-pigmented feathers from SL chickens. Therefore, surprisingly, the inflammatory response in feathers of SL chickens did not inhibit HVT infection and persistence, but on the contrary, temporarily promoted HVT infection in feathers. Full article
(This article belongs to the Special Issue Marek’s Disease Virus)
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<p>Herpes virus of turkey–Newcastle disease (HVT-ND) vaccination and vitiligo development in Smyth line chickens. All data are shown in Tukey boxes with medians as horizontal bars and interquartile ranges as vertical bars with notches. The black individual dots represent outliers. (<b>A</b>) Vitiligo score in Brown line (BL) and Smyth line (SL) chickens over time. A score of 1 corresponds to “no vitiligo” and a score of 5 to “complete vitiligo”. The percentage of birds having developed vitiligo is indicated above the graphs for each time. One hundred percent of SL chickens (<span class="html-italic">n</span> = 11) had developed severe vitiligo at week 20, as did one of the BL chickens (<span class="html-italic">n</span> = 9). (<b>B</b>) HVT-ND uptake. NDV antibody titers in plasma were measured at week 11 by ELISA. All birds had elevated titers, mostly above 10,000, indicating good vaccine uptake and antibody response. ns, non-significant.</p>
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<p>Influence of the chicken line (BL vs. SL) on HVT load in feathers independent of pigmentation. Data are shown in gray for BL and in red for SL. Feathers of all types were considered herein (pigmented or not) and abbreviated feathers (<b>A</b>,<b>B</b>). The HVT load unit is HVT genome copy number per million cells. (<b>A</b>) HVT load across time. Data are shown in Tukey boxes with the log medians visible as thick horizontal bars (2.629 for BL, 2.889 for SL). The HVT loads were moderate in both lines. (<b>B</b>) Dynamic of HVT load over time. Each dot corresponds to the median load (log) at a time point. The difference in HVT load was significant at week 8 (adjusted <span class="html-italic">p</span>-value &lt; 0.001, ***; Wilcoxon test with a Holm correction for multiple comparison). ns, non-significant. (<b>C</b>) HVT load per line over time. Data are shown in Tukey boxes as above. ns, non-significant.</p>
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<p>Dynamic of HVT load per subject over time. The HVT load unit is HVT genome copy number per million cells. Each dot corresponds to the HVT load at a time point. (<b>A</b>) BL chickens. (<b>B</b>) SL chickens. The birds exhibited two major profiles: (<b>i</b>) chickens positive at all time points, like B04 or S06; (<b>ii</b>) birds showing one or more null-HVT loads, notably after week 2, like B07 and S09. In this figure, BL and SL are abbreviated as B and S, respectively.</p>
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<p>Comparison between HVT load in pigmented and non-pigmented feathers in vitiliginous SL chickens from week 8 to 20. Pigmented feathers (Feath_A in brown); non-pigmented feathers (Feath_B in white). The HVT load unit is HVT genome copy number per million cells. (<b>A</b>) HVT loads across time. Data are shown in Tukey boxes with the log medians visible as thick horizontal bars (3.037 for Feath_A, 2.951 for Feath_B). The two boxplots highly overlap indicating no or very low differences in HVT loads between pigmented and non-pigmented feathers in SL. (<b>B</b>) HVT loads at individual times. Data are shown in Tukey boxes as above. No significant differences in HVT loads were observed between pigmented (Feath_A) and not pigmented feathers (Feath_B) (all adjusted <span class="html-italic">p</span>-value &gt; 0.9; exact Wilcoxon test with a Holm correction for multiple comparisons).</p>
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<p>HVT loads in the spleen at 15.5 months of age in SL and BL chickens. Seven birds of each line were analyzed. The HVT load unit is HVT genome copy number per million cells. Data are shown in Tukey boxes with the medians visible as thick horizontal bars (212 for BL, 507 for SL). The difference in HVT load in the spleen was not significant between the two lines (exact <span class="html-italic">p</span>-value = 0.7995; permutation test for two independent groups). ns, non-significant.</p>
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18 pages, 383 KiB  
Article
Clustering on Human Microbiome Sequencing Data: A Distance-Based Unsupervised Learning Model
by Dongyang Yang and Wei Xu
Microorganisms 2020, 8(10), 1612; https://doi.org/10.3390/microorganisms8101612 - 20 Oct 2020
Cited by 9 | Viewed by 4528
Abstract
Modeling and analyzing human microbiome allows the assessment of the microbial community and its impacts on human health. Microbiome composition can be quantified using 16S rRNA technology into sequencing data, which are usually skewed and heavy-tailed with excess zeros. Clustering methods are useful [...] Read more.
Modeling and analyzing human microbiome allows the assessment of the microbial community and its impacts on human health. Microbiome composition can be quantified using 16S rRNA technology into sequencing data, which are usually skewed and heavy-tailed with excess zeros. Clustering methods are useful in personalized medicine by identifying subgroups for patients stratification. However, there is currently a lack of standardized clustering method for the complex microbiome sequencing data. We propose a clustering algorithm with a specific beta diversity measure that can address the presence-absence bias encountered for sparse count data and effectively measure the sample distances for sample stratification. Our distance measure used for clustering is derived from a parametric based mixture model producing sample-specific distributions conditional on the observed operational taxonomic unit (OTU) counts and estimated mixture weights. The method can provide accurate estimates of the true zero proportions and thus construct a precise beta diversity measure. Extensive simulation studies have been conducted and suggest that the proposed method achieves substantial clustering improvement compared with some widely used distance measures when a large proportion of zeros is presented. The proposed algorithm was implemented to a human gut microbiome study on Parkinson’s diseases to identify distinct microbiome states with biological interpretations. Full article
(This article belongs to the Special Issue New Methods in Microbial Research)
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<p>A flowchart to illustrate PAM algorithm for two clusters.</p>
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<p>Accuracy boxplots for simulated data. Two-subclass and three-subclass scenarios are considered. Three different cases of proportion of zeros (ZP) are evaluated - high ZP, medium ZP, and low ZP, are presented in left, middle, and right, respectively. For each box of the boxplots, the center line represents the median, the two vertical lines represent the 25th percentiles to the 75th percentiles. The whiskers of the boxplots show 1.5 interquartile range (IQR) below the 25th percentiles and 1.5 IQR above the 75th percentiles. The mean are shown in blue diamond dots.</p>
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<p>Jaccard index boxplots for simulated data. Two-subclass and three-subclass scenarios are considered. Three different cases of proportion of zeros (ZP) are evaluated - high ZP, medium ZP, and low ZP, are presented in left, middle, and right, respectively. For each box of the boxplots, the center line represents the median, the two vertical lines represent the 25th percentiles to the 75th percentiles. The whiskers of the boxplots show 1.5 interquartile range (IQR) below the 25th percentiles and 1.5 IQR above the 75th percentiles. The mean are shown in blue diamond dots.</p>
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10 pages, 982 KiB  
Article
The Microbiota Profile in Inflamed and Non-Inflamed Ileal Pouch–Anal Anastomosis
by Sabrina Just Kousgaard, Thomas Yssing Michaelsen, Hans Linde Nielsen, Karina Frahm Kirk, Mads Albertsen and Ole Thorlacius-Ussing
Microorganisms 2020, 8(10), 1611; https://doi.org/10.3390/microorganisms8101611 - 20 Oct 2020
Cited by 5 | Viewed by 2281
Abstract
The objective was to determine the bacterial composition in inflamed and non-inflamed pouches for comparison to the microbiota of healthy individuals. Pouch patients and healthy individuals were included between November 2017 and June 2019 at the Department of Gastrointestinal Surgery, Aalborg University Hospital, [...] Read more.
The objective was to determine the bacterial composition in inflamed and non-inflamed pouches for comparison to the microbiota of healthy individuals. Pouch patients and healthy individuals were included between November 2017 and June 2019 at the Department of Gastrointestinal Surgery, Aalborg University Hospital, Denmark. A faecal sample was collected from all participants for microbiota analysis using 16S rRNA amplicon sequencing. Overall, 38 participants were included in the study. Eleven patients with a normally functioning pouch, 9 patients with chronic pouchitis, 6 patients with familial adenomatous polyposis, and 12 healthy individuals. Patients with chronic pouchitis had overall lower microbial diversity and richness compared to patients with a normal pouch function (p < 0.001 and p = 0.009) and healthy individuals (p < 0.001 and p < 0.001). No significant difference was found between patients with familial adenomatous polyposis and chronic pouchitis (microbial diversity p = 0.39 and richness p = 0.78). Several taxa from the family Enterobacteriaceae, especially genus Escherichia, were associated primarily with patients with chronic pouchitis, while taxa from the genus Bacteroides primarily were associated with healthy individuals and patients with a normally functioning pouch. Finally, a microbial composition gradient could be established from healthy individuals through patients with normal pouch function and familial adenomatous polyposis to patients with chronic pouchitis. Full article
(This article belongs to the Section Gut Microbiota)
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<p>The Shannon diversity index (<b>A</b>) and number of amplicon sequencing variants (ASVs) for species richness (<b>B</b>) in healthy individuals and patients with normal pouch function, familial adenomatous polyposis (FAP), and chronic pouchitis. <span class="html-italic">p</span>-values were calculated using the Wilcoxon rank-sum test and adjusted for multiple comparisons using the Holm’s method.</p>
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<p>Microbial composition in healthy individuals and patients with normal pouch function, familial adenomatous polyposis (FAP), and chronic pouchitis. The top 20 most abundant genera with phylum names, ordered from top to bottom by mean abundance, are shown for all patients and healthy individuals in (<b>A</b>). A principal component analysis (PCA) plot of the first two components for all samples from the patients and healthy individuals is shown in (<b>B</b>) and coloured accordingly. In (<b>C</b>) are the top 20 most influential amplicon sequencing variants (ASVs) on the first principal component (PC1) ordered from top to bottom by absolute value. Names are shown on the <span class="html-italic">y</span>-axis, with corresponding weights on the <span class="html-italic">x</span>-axis.</p>
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9 pages, 1236 KiB  
Communication
Detailed Molecular Interactions of Favipiravir with SARS-CoV-2, SARS-CoV, MERS-CoV, and Influenza Virus Polymerases In Silico
by Mitsuru Sada, Takeshi Saraya, Haruyuki Ishii, Kaori Okayama, Yuriko Hayashi, Takeshi Tsugawa, Atsuyoshi Nishina, Koichi Murakami, Makoto Kuroda, Akihide Ryo and Hirokazu Kimura
Microorganisms 2020, 8(10), 1610; https://doi.org/10.3390/microorganisms8101610 - 20 Oct 2020
Cited by 30 | Viewed by 5644
Abstract
Favipiravir was initially developed as an antiviral drug against influenza and is currently used in clinical trials against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection (COVID-19). This agent is presumably involved in RNA chain termination during influenza virus replication, although the molecular interactions [...] Read more.
Favipiravir was initially developed as an antiviral drug against influenza and is currently used in clinical trials against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection (COVID-19). This agent is presumably involved in RNA chain termination during influenza virus replication, although the molecular interactions underlying its potential impact on the coronaviruses including SARS-CoV-2, SARS-CoV, and Middle East respiratory syndrome coronavirus (MERS-CoV) remain unclear. We performed in silico studies to elucidate detailed molecular interactions between favipiravir and the SARS-CoV-2, SARS-CoV, MERS-CoV, and influenza virus RNA-dependent RNA polymerases (RdRp). As a result, no interactions between favipiravir ribofuranosyl-5′-triphosphate (F-RTP), the active form of favipiravir, and the active sites of RdRps (PB1 proteins) from influenza A (H1N1)pdm09 virus were found, yet the agent bound to the tunnel of the replication genome of PB1 protein leading to the inhibition of replicated RNA passage. In contrast, F-RTP bound to the active sites of coronavirus RdRp in the presence of the agent and RdRp. Further, the agent bound to the replicated RNA terminus in the presence of agent, magnesium ions, nucleotide triphosphate, and RdRp proteins. These results suggest that favipiravir exhibits distinct mechanisms of action against influenza virus and various coronaviruses. Full article
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<p>Detailed interactions between favipiravir ribofuranosyl-5′-triphosphate (F-RTP) and the active sites (red-colored regions) of (<b>a</b>) influenza H3N2 PB1 protein, (<b>b</b>) influenza H1N1 PB1 protein, (<b>c</b>) severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) RNA-dependent RNA polymerases (RdRp), (<b>d</b>) SARS-CoV RdRp, and (<b>e</b>) Middle East respiratory syndrome coronavirus (MERS-CoV) RdRp. Three-dimensional configurations of F-RTP and proteins were constructed with space-filling or stick models.</p>
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<p>Detailed interactions among favipiravir ribofuranosyl-5′-triphosphate (F-RTP), nucleotide triphosphate (NTP), ions, and the active sites (red-colored regions) of (<b>a</b>) influenza H1N1, (<b>b</b>) severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), (<b>c</b>) SARS-CoV, and (<b>d</b>) Middle East respiratory syndrome coronavirus (MERS-CoV) RNA-dependent RNA polymerases (RdRp). Three-dimensional configurations of F-RTP, NTP, ions, and RdRp protein were constructed with space-filling or stick models.</p>
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16 pages, 1590 KiB  
Article
Biofilm Produced In Vitro by Piscirickettsia salmonis Generates Differential Cytotoxicity Levels and Expression Patterns of Immune Genes in the Atlantic Salmon Cell Line SHK-1
by Natacha Santibañez, Matías Vega, Tatiana Pérez, Alejandro Yáñez, Roxana González-Stegmaier, Jaime Figueroa, Ricardo Enríquez, Cristian Oliver and Alex Romero
Microorganisms 2020, 8(10), 1609; https://doi.org/10.3390/microorganisms8101609 - 20 Oct 2020
Cited by 19 | Viewed by 4356
Abstract
Piscirickettsia salmonis is the causative agent of Piscirickettsiosis, an infectious disease with a high economic impact on the Chilean salmonid aquaculture industry. This bacterium produces biofilm as a potential resistance and persistence strategy against stressful environmental stimuli. However, the in vitro culture conditions [...] Read more.
Piscirickettsia salmonis is the causative agent of Piscirickettsiosis, an infectious disease with a high economic impact on the Chilean salmonid aquaculture industry. This bacterium produces biofilm as a potential resistance and persistence strategy against stressful environmental stimuli. However, the in vitro culture conditions that modulate biofilm formation as well as the effect of sessile bacteria on virulence and immune gene expression in host cells have not been described for P. salmonis. Therefore, this study aimed to analyze the biofilm formation by P. salmonis isolates under several NaCl and iron concentrations and to evaluate the virulence of planktonic and sessile bacteria, together with the immune gene expression induced by these bacterial conditions in an Atlantic salmon macrophage cell line. Our results showed that NaCl and Fe significantly increased biofilm production in the LF-89 type strain and EM-90-like isolates. Additionally, the planktonic EM-90 isolate and sessile LF-89 generated the highest virulence levels, associated with differential expression of il-1β, il-8, nf-κb, and iκb-α genes in SHK-1 cells. These results suggest that there is no single virulence pattern or gene expression profile induced by the planktonic or sessile condition of P. salmonis, which are dependent on each strain and bacterial condition used. Full article
(This article belongs to the Section Biofilm)
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<p><span class="html-italic">P. salmonis</span> biofilm formation cultured under different NaCl and ferric citrate concentrations. (<b>A</b>) Representative CV staining of biofilm produced by <span class="html-italic">P. salmonis</span> LF-89 type strain and isolates LF-89-like 1, EM-90-like 1, and EM-like 2 at eight days (100× magnification). Biofilm quantification for <span class="html-italic">P. salmonis</span> LF-89 (<b>B</b>) and isolates LF-89-like 1 (<b>C</b>), EM-90-like 1 (<b>D</b>), and EM-90-like 2 (<b>E</b>) grown for 0, 2, 4, and 8 days. Values are presented as the mean ± SEM (<span class="html-italic">n</span> = 5). A two-way ANOVA followed by a Tukey HDS was performed to define the differences between media variation. Different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Cytotoxicity assay in SHK-1 cells infected with planktonic and sessile <span class="html-italic">P. salmonis</span>. SHK-1 cells were infected with planktonic or sessile <span class="html-italic">P. salmonis</span> (MOI = 10). Results are expressed as cytotoxicity percentage means ± standard error of each sample in triplicate. Asterisks indicate significant differences (* <span class="html-italic">p</span> &lt; 0.05 and **** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Analysis of the immune gene expression induced by planktonic and sessile <span class="html-italic">P. salmonis</span>. SHK-1 cells were infected with <span class="html-italic">P. salmonis</span> LF-89<sup>T</sup> or EM-90-like 2 strain in planktonic or sessile conditions for 2, 4, 6, 12, and 24 h, and the mRNA levels of <span class="html-italic">il-1β</span> (<b>A</b>,<b>B</b>), <span class="html-italic">il-8</span> (<b>C</b>,<b>D</b>), <span class="html-italic">nf-κb</span> (<b>E</b>,<b>F</b>), and <span class="html-italic">iκb-α</span> (<b>G</b>,<b>H</b>) were analyzed by qRT-PCR. The expression of <span class="html-italic">ef-1α</span> was used as a normalizer. The graph depicts the average ± standard deviation of the gene expression fold change. Control cells were used as a calibrator (dotted line). Asterisks above the bars indicate statistically significant differences evaluated using Tukey’s multiple comparison test (<span class="html-italic">p</span> &lt; 0.05).</p>
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18 pages, 2630 KiB  
Article
An Alcohol Dehydrogenase 3 (ADH3) from Entamoeba histolytica Is Involved in the Detoxification of Toxic Aldehydes
by Constantin König, Martin Meyer, Corinna Lender, Sarah Nehls, Tina Wallaschkowski, Tobias Holm, Thorben Matthies, Dirk Lercher, Jenny Matthiesen, Helena Fehling, Thomas Roeder, Sophia Reindl, Maria Rosenthal, Nahla Galal Metwally, Hannelore Lotter and Iris Bruchhaus
Microorganisms 2020, 8(10), 1608; https://doi.org/10.3390/microorganisms8101608 - 19 Oct 2020
Cited by 5 | Viewed by 2930
Abstract
Recently, a putative alcohol dehydrogenase 3, termed EhADH3B of the Entamoeba histolytica isolate HM-1:IMSS was identified, which is expressed at higher levels in non-pathogenic than in pathogenic amoebae and whose overexpression reduces the virulence of pathogenic amoebae. In an in silico analysis performed [...] Read more.
Recently, a putative alcohol dehydrogenase 3, termed EhADH3B of the Entamoeba histolytica isolate HM-1:IMSS was identified, which is expressed at higher levels in non-pathogenic than in pathogenic amoebae and whose overexpression reduces the virulence of pathogenic amoebae. In an in silico analysis performed in this study, we assigned EhADH3B to a four-member ADH3 family, with ehadh3b present as a duplicate (ehadh3ba/ehadh3bb). In long-term laboratory cultures a mutation was identified at position 496 of ehadh3ba, which codes for a stop codon, which was not the case for amoebae isolated from human stool samples. When using transfectants that overexpress or silence ehadh3bb, we found no or little effect on growth, size, erythrophagocytosis, motility, hemolytic or cysteine peptidase activity. Biochemical characterization of the recombinant EhADH3Bb revealed that this protein forms a dimer containing Ni2+ or Zn2+ as a co-factor and that the enzyme converts acetaldehyde and formaldehyde in the presence of NADPH. A catalytic activity based on alcohols as substrates was not detected. Based on the results, we postulate that EhADH3Bb can reduce free acetaldehyde released by hydrolysis from bifunctional acetaldehyde/alcohol dehydrogenase-bound thiohemiacetal and that it is involved in detoxification of toxic aldehydes produced by the host or the gut microbiota. Full article
(This article belongs to the Special Issue Virulence and Parasitism of Parasitic Protozoa)
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<p>Localization of the EhADH3B coding genes EHI_160670 <span class="html-italic">(ehadh3b<sup>a</sup></span>) and EHI_088020 <span class="html-italic">(ehadh3b<sup>b</sup></span>) in the genome of <span class="html-italic">E. histolytica</span> (AmoebaDB, release 48 beta, 27 August 2020) and sequence analysis of EHI_088020 of different <span class="html-italic">E. histolytica</span> isolates. (<b>A</b>). The gene EHI-160670 (yellow) is located at the beginning of the contig DS571485 and the gene EHI_088020 (red) is located in contig DS571307 at position 5583 to 6731. The genomic region around the genes EHI_160067 and EHI_088020 was amplified and sequenced in 14 different <span class="html-italic">E. histolytica</span> isolates using the primers shown in <b>A</b>. (<b>B</b>). In EHI_088020 a mutation at position 496 (C-T (yellow)) coding for a stop codon was identified in some of the isolates investigated.</p>
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<p>Phenotypical characterization of <span class="html-italic">ehadh3b<sup>b</sup></span> overexpressing and silencing transfectants. Hemolytic activity (<b>A</b>), cysteine peptidase activity (<b>B</b>), erythrophagocytosis (<b>C</b>), doubling time (<b>D</b>), motility (<b>E</b>), and size (<b>F</b>) was determined of B2<sup>p</sup> transfectants overexpressing <span class="html-italic">ehadh3b<sup>b</sup></span> in comparison to the respective control amoebae transfected with pNC and of B8<sup>np</sup> transfectants were expression of <span class="html-italic">ehadh3b<sup>b</sup></span> was silenced using B8<sup>np</sup> trophozoites as control. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Recombinant expression, investigation of the oligomeric state and putative metal cofactor binding of EhADH3B<sup>b</sup>. (<b>A</b>). <span class="html-italic">ehadh3b<sup>b</sup></span> was recombinantly expressed in <span class="html-italic">E. coli</span> as a GST-fusion protein and purified using affinity chromatography. After purification and cleavage of the GST tag, the recombinant ADH3B<sup>b</sup> (recADH3B<sup>b</sup>) can be displayed as a 43 kDa protein band after SDS-PAGE and Coomassie staining. (<b>B</b>). Size exclusion chromatography of recADH3B<sup>b</sup> was performed on a HiLoad 16/60 Superdex prep grade column in a buffer containing 50 mM Tris, 150 mM NaCl, 10 mM EDTA, 1 mM DTT, 10% glycine, pH 8.0. Elution peaks of standard proteins are indicated by dotted lines in the elution profile of the target protein (black solid line). An elution peak of the target protein at 82 mL and subsequent detection of the protein in the respective elution fractions by SDS-PAGE indicates that recADH3B<sup>b</sup> is present as a dimer in solution. (<b>C</b>). Thermal stabilization assay for the determination of the putative metal cofactor of recEhADH3B<sup>b</sup> by addition of different metal ions at a concentration of 2 mM. The melting curve of recEhADH3B<sup>b</sup> without addition of metal ions was used as a control for the assay. The relative fluorescence is displayed as a function of temperature.</p>
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<p>Determination of the enzymatic activity of recEhADH3B<sup>b</sup>. (<b>A</b>). The catalytic activity of recEhADH3B<sup>b</sup> was determined with a range of substrates (formaldehyde (50 mM), acetaldehyde (20 mM), propionaldehyde and butyraldehyde, methanol, ethanol, propanol, butanol (all 100 mM)) in the presence of 0.7 mM NADP(H) at pH 7.4. (<b>B–D</b>) Enzyme kinetic of recEhADH3B<sup>b</sup> using acetaldehyde as substrate. (<b>E</b>,<b>F</b>) Enzyme kinetic of recEhADH3B<sup>b</sup> using formaldehyde as substrate. (<b>B</b>,<b>E</b>) Time dependence of enzymatic activity; (<b>C</b>,<b>F</b>) Michaelis-Menten plot; (<b>D</b>,<b>G</b>) Lineweaver–Burk plot.</p>
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<p>Influence of different metal ions and pH on the activity of recEhADH3B<sup>b</sup>. (<b>A</b>) After removal of possible metal ions by EDTA (10 mM), the purified recEhADH3B<sup>b</sup> was dialysed against an EDTA-free buffer and incubated for 1 h at 4 °C with different metal ions (1 mM). Activity was measured using acetaldehyde (20 mM) as substrate as well as NADPH (0.7 mM). As control EDTA-treated and dialysed recEhADH3B<sup>b</sup> was used. Assays were performed in duplicate. Shown is the relative activity, where the activity of recEhADH3B<sup>b</sup> in the presence of Ni<sup>2+</sup> was set as 100%. (<b>B</b>) Dialyzed recEhADH3B<sup>b</sup> incubated with Ni<sup>2+</sup> was used to determine the influence of the pH on acetaldehyde dehydrogenase activity. Shown is the relative activity, where the activity of recEhADH3B<sup>b</sup> in the presence of Ni<sup>2+</sup> was set as 100%.</p>
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<p>Localization of EhADH3B<sup>b</sup> in clone B8<sup>np</sup> using polyclonal EhADH3B<sup>b</sup> antibodies in and A1<sup>np</sup> transfectants expressing EhADH3B<sup>b</sup> as c-myc fusion protein using anti c-myc for detection. Trophozoites were fixed with paraformaldehyde and treated with (+) or without (−) saponin. Afterwards, the trophozoites were incubated with specific antiserum (diluted 1:200 in NaPBS ± saponin), followed by Alexa Fluor<sup>®</sup>488 goat anti-mouse secondary antibody. Localization was assessed by fluorescence microscopy (Leica, DM BR, Wetzlar, Germany).</p>
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<p>Localization of EhADH3B<sup>b</sup> in clone A1<sup>np</sup> using polyclonal EhADH3B<sup>b</sup> antibodies confocal microscope (Olympus IX81 microscope with the FluoView Version 1.7b software; Olympus, Hamburg, Germany). Amoebae were fixed with paraformaldehyde and treated with: (<b>A</b>) (+) or (<b>B</b>) without (−) saponin. The trophozoites were incubated with anti-EhEADH3B (diluted 1:200 in NaPBS ± saponin), followed by Alexa Fluor<sup>®</sup>488 goat anti-mouse secondary antibody. Hoechst staining was used to visualize nuclei.</p>
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12 pages, 635 KiB  
Article
Effects of Different Stress Parameters on Growth and on Oleuropein-Degrading Abilities of Lactiplantibacillus plantarum Strains Selected as Tailored Starter Cultures for Naturally Table Olives
by Amanda Vaccalluzzo, Alessandra Pino, Maria De Angelis, Joaquín Bautista-Gallego, Flora Valeria Romeo, Paola Foti, Cinzia Caggia and Cinzia L Randazzo
Microorganisms 2020, 8(10), 1607; https://doi.org/10.3390/microorganisms8101607 - 19 Oct 2020
Cited by 15 | Viewed by 2577
Abstract
The use of β-glucosidase positive strains, as tailored-starter cultures for table olives fermentation, is a useful biotechnological tool applied to accelerate the debittering process. Nowadays, strains belonging to Lactiplantibacillus plantarum species are selected for their high versatility and tolerance to stress conditions. The [...] Read more.
The use of β-glucosidase positive strains, as tailored-starter cultures for table olives fermentation, is a useful biotechnological tool applied to accelerate the debittering process. Nowadays, strains belonging to Lactiplantibacillus plantarum species are selected for their high versatility and tolerance to stress conditions. The present study investigated the effect of different stress factors (pH, temperature and NaCl) on growth and on oleuropein-degrading abilities of selected L. plantarum strains. In addition, the presence of the beta-glucosidase gene was investigated by applying a PCR based approach. Results revealed that, overall, the performances of the tested strains appeared to be robust toward the different stressors. However, the temperature of 16 °C significantly affected the growth performance of the strains both singularly and in combination with other stressing factors since it prolongs the latency phase and reduces the maximum growth rate of strains. Similarly, the oleuropein degradation was mainly affected by the low temperature, especially in presence of low salt content. Despite all strains displayed the ability to reduce the oleuropein content, the beta-glucosidase gene was detected in five out of the nine selected strains, demonstrating that the ability to hydrolyze the oleuropein is not closely related to the presence of beta-glucosidase. Data of the present study suggest that is extremely important to test the technological performances of strains at process conditions in order to achieve a good selection of tailored starter cultures for table olives. Full article
(This article belongs to the Special Issue Microbial Populations of Fermented Foods)
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<p>Survival rate plot of the strains, expressed in percentage, under single and combined stress conditions at 32 °C.</p>
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<p>Survival rate plot of the strains, expressed in percentage values, under single and combined stress conditions at 16 °C.</p>
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10 pages, 1413 KiB  
Article
Electrically Charged Disinfectant Containing Calcium Hydrogen Carbonate Mesoscopic Crystals as a Potential Measure to Control Xanthomonas campestris pv. campestris on Cabbage Seeds
by Akikazu Sakudo, Makoto Haritani, Koichi Furusaki, Rumiko Onishi and Takashi Onodera
Microorganisms 2020, 8(10), 1606; https://doi.org/10.3390/microorganisms8101606 - 19 Oct 2020
Cited by 6 | Viewed by 3979
Abstract
Xanthomonas campestris pv. campestris (Xcc) is an important seed-borne bacterial pathogen that causes black rot in brassica. Current seed disinfection methods for Xcc have disadvantages; chemical treatment has associated environmental risks, hot water immersion reduces germination, and dry heat treatment is [...] Read more.
Xanthomonas campestris pv. campestris (Xcc) is an important seed-borne bacterial pathogen that causes black rot in brassica. Current seed disinfection methods for Xcc have disadvantages; chemical treatment has associated environmental risks, hot water immersion reduces germination, and dry heat treatment is protracted. Here, we treated Xcc-contaminated seeds with CAC-717, a recently developed disinfectant produced by applying an electric field and water flow to distilled water containing calcium hydrogen carbonate to produce mesoscopic crystals. The decimal reduction time (D-value) of Xcc suspension (8.22 log10 colony forming units (CFU)/mL) by CAC-717 treatment was 0.319 min. Treatment of Xcc-contaminated cabbage seeds at 25 °C for 30 min with CAC-717 significantly reduced bacterial cell numbers recovered from the seeds (0.36 log10 CFU/mL (SEM (standard error of the mean) = 0.23 log10 CFU/mL)) compared with distilled water treatment (3.52 log10 CFU/mL (SEM = 0.12 log10 CFU/mL)). Moreover, there was a lower incidence of black rot after treatment with CAC-717 (26.67% ± 3.33%) versus distilled water (56.67% ± 8.82%). For non-contaminated seeds, there was no significant difference in germination rate and plant stem length between distilled water and CAC-717 treatment after 5 days of cultivation. In conclusion, CAC-717 is a promising seed disinfectant without deleterious effects on germination or plant growth. Full article
(This article belongs to the Section Microbial Biotechnology)
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<p>Preparation of Material (A) and Material (B1–B6). (<b>a</b>) To produce Material (A), Material (A1) was mixed with an equal weight of Material (A1-1) and Material (A1-2). Material (A1-1) was a dried and pulverized mixture of 10% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) field thistle (leaf part, stem part, and flower part), 60% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) mugwort (leaf part and stem part), and 30% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) <span class="html-italic">Farfugium japonicum</span> (leaf part and stem part). Material (A1-2) was a dried and pulverized mixture of 20% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) <span class="html-italic">Rosa multiflora</span> (leaf part, flower part), 10% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) <span class="html-italic">Geum japonicum</span> (leaf part and stem part), and 70% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) raspberry (leaf part, stem part, and flower part). Material (A2) was a dried mixture of 25% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) <span class="html-italic">Acer</span> (leaf part and stem part), 25% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) <span class="html-italic">Betula platyphylla</span> var. <span class="html-italic">japonica</span> (leaf part, stem part, and bark part), and 50% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) <span class="html-italic">Cryptomeria japonica</span> (leaf part, stem part, and bark part). Then, Material (A1) and Material (A2) was mixed at a ratio of 1:3 to obtain Material (A). (<b>b</b>) To produce Material (B), various combinations of limestone, fossil coral, shell, and activated carbon were used to obtain Material (B1), Material (B2), Material (B3), Material (B4), Material (B5), and Material (B6). Material (B1) comprised 70% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) limestone, 15% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) fossil coral, and 15% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) shell. Material (B2) comprised 40% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) limestone, 15% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) fossil coral, 40% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) shell, and 5% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) activated carbon. Material (B3) comprised 80% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) limestone, 15% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) fossil coral, and 5% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) shell. Material (B4) comprised 90% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) limestone, 5% fossil coral, and 5% shell. Material (B5) comprised 80% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) limestone, 10% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) fossil coral, and 10% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) shell. Material (B6) comprised 60% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) limestone, 30% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) fossil coral, and 10% (<span class="html-italic">w</span>/<span class="html-italic">w</span>) shell.</p>
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<p>Reduction of viable cell number of <span class="html-italic">Xanthomonas campestris</span> pv. <span class="html-italic">campestris</span> (<span class="html-italic">Xcc</span>) after CAC-717 treatment. <span class="html-italic">Xcc</span> suspension (8.22 log<sub>10</sub> colony forming units (CFU)/mL) was mixed with an equal quantity of CAC-717 (<b>a</b>) and incubated at 25 °C for the indicated times (0, 0.5, 1, 2, or 5 min). As a control, <span class="html-italic">Xcc</span> suspension mixed with an equal quantity of distilled water was subjected to incubation at 25 °C (<b>b</b>) or 50 °C (<b>c</b>) for the indicated times (0, 0.5, 1, 2, or 5 min). After treatment, the samples were plated on yeast extract–dextrose–CaCO<sub>3</sub> (YDC) medium at 25 °C for 3 days, and the bacterial cell number was determined as colony forming units (CFU)/mL. Data shown as mean ± SEM (standard error of the mean) of triplicates and are representative of two independent experiments; * and ** indicate significant differences (<span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01, respectively) versus the control (0 min) by non-repeated measured analysis of variance (ANOVA) followed by Bonferroni correction. NS: no significant difference versus control (0 min).</p>
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<p>Reduction of viable cell number of <span class="html-italic">Xcc</span> in <span class="html-italic">Xcc</span>-contaminated seeds after CAC-717 treatment. Cabbage seeds contaminated with <span class="html-italic">Xcc</span> were treated with distilled water or CAC-717 at 25 °C for 30 min, and <span class="html-italic">Xcc</span> was recovered from the seeds as described in Methods. The samples were then plated and incubated on YDC medium at 25 °C, and the viable cell number (CFU/mL) was counted after 3 days. Data shown as mean ± SEM of triplicates and are representative of two independent experiments; * indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05) between the two groups by Mann–Whitney U-test.</p>
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<p>Reduced disease incidence in <span class="html-italic">Xcc</span>-contaminated seeds after CAC-717 treatment. Cabbage seeds contaminated with <span class="html-italic">Xcc</span> were treated with distilled water or CAC-717 at 25 °C for 30 min. The seeds were then cultured at 25 °C for 5 days, and the incidence of disease in the seeds was evaluated as described in Methods. Data shown as mean ± SEM of triplicates and are representative of two independent experiments; * indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05) between the two groups by Mann–Whitney U-test.</p>
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<p>No change in germination rate of non-contaminated cabbage seeds after CAC-717 treatment. Non-contaminated cabbage seeds were treated with distilled water or CAC-717 at 25 °C for 30 min. The germination rate was then measured as described in Methods. Data shown as mean ± SEM of triplicates and are representative of two independent experiments. There was no significant difference (NS) between the two groups by Mann–Whitney U-test.</p>
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<p>No change in plant stem length of non-contaminated cabbage seeds after CAC-717 treatment. Non-contaminated cabbage seeds were treated with distilled water or CAC-717 at 25 °C for 30 min. Plant stem length was then measured as described in Methods. Data shown as mean ± SEM of triplicates and are representative of two independent experiments. There was no significant difference (NS) between the two groups by Mann–Whitney U-test.</p>
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15 pages, 976 KiB  
Article
Effects of Wormwood (Artemisia montana) Essential Oils on Digestibility, Fermentation Indices, and Microbial Diversity in the Rumen
by Seong Shin Lee, Dong Hyeon Kim, Dimas Hand Vidya Paradhipta, Hyuk Jun Lee, Hee Yoon, Young Ho Joo, Adegbola T. Adesogan and Sam Churl Kim
Microorganisms 2020, 8(10), 1605; https://doi.org/10.3390/microorganisms8101605 - 18 Oct 2020
Cited by 20 | Viewed by 3131
Abstract
This study investigated the effects of essential oil (EO) from three Korean wormwood (Artemisia Montana) plants on in vitro ruminal digestibility, fermentation, and microbial diversity. Dried (0.5 g) soybean meal (SBM) or bermudagrass hay (BGH) were incubated in buffered rumen fluid [...] Read more.
This study investigated the effects of essential oil (EO) from three Korean wormwood (Artemisia Montana) plants on in vitro ruminal digestibility, fermentation, and microbial diversity. Dried (0.5 g) soybean meal (SBM) or bermudagrass hay (BGH) were incubated in buffered rumen fluid (40 mL) for 72 h with or without EO (5 mg/kg) from Ganghwa (GA), Injin (IN), or San (SA) wormwood (Experiment 1). Both SA and IN improved (p < 0.05) dry matter digestibility (DMD) of BGH, while GA reduced (p < 0.05) total short-chain fatty acid of BGH and SBM. Besides, SA increased (p < 0.05) numbers of Ruminococcus albus and Streptococcus bovis in SBM. Experiment 2 examined different doses (0, 0.1, 1, and 10 mg/kg) of SA, the most promising EO from Experiment 1. Applying SA at 10 mg/kg gave the highest DMD (L; p < 0.01) and neutral detergent fiber (Q; p < 0.05) digestibility for BGH. Applying SA at 1 mg/kg gave the highest R. albus population (Q; p < 0.05) in SBM. Therefore, SA was better than GA and IN at improving rumen fermentation, and the 0.1 to 1 and 10 mg/kg doses improved ruminal fermentation and in vitro digestibility of SBM and BGH, respectively. Full article
(This article belongs to the Section Gut Microbiota)
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<p>Effects of adding essential oils from different wormwood species to soybean meal (SBM) (<b>A</b>) or bermudagrass hay (BGH) (<b>B</b>) on fold changes of rumen microbial populations compared to that of the blank after 72 h of in vitro incubation in buffered rumen fluid. CON, without essential oil application; GA, Ganghwa essential oil applied; IN, Injin essential oil applied; SA, San essential oil applied. a–c: Means for the same microbe with different letters differ significantly (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of applying essentials oil from San wormwood at increasing levels to SBM (<b>A</b>) or BGH (<b>B</b>) substrates on fold changes of rumen microbial populations compared to that of the blank after 72 h of in vitro incubation in buffered rumen fluid. The San essential oil was applied at 0, 0.1, 1, and 1 mg/kg per 40 mL of buffered rumen fluid. The <span class="html-italic">p</span>-value indicated the polynomial contrast analysis; L, Linear effect; Q, Quadratic effect; C, Cubic effect. a–c: Means for the same microbe with different letters differ significantly (<span class="html-italic">p</span> &lt; 0.05).</p>
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23 pages, 3194 KiB  
Article
Spatial Changes in Microbial Communities along Different Functional Zones of a Free-Water Surface Wetland
by Mikhail V. Semenov, George S. Krasnov, Ksenia Y. Rybka, Sergey L. Kharitonov, Yulia A. Zavgorodnyaya, Anna V. Yudina and Nataliya M. Shchegolkova
Microorganisms 2020, 8(10), 1604; https://doi.org/10.3390/microorganisms8101604 - 18 Oct 2020
Cited by 12 | Viewed by 3200
Abstract
Constructed wetlands (CWs) are complicated ecosystems that include vegetation, sediments, and the associated microbiome mediating numerous processes in wastewater treatment. CWs have various functional zones where contrasting biochemical processes occur. Since these zones are characterized by different particle-size composition, physicochemical conditions, and vegetation, [...] Read more.
Constructed wetlands (CWs) are complicated ecosystems that include vegetation, sediments, and the associated microbiome mediating numerous processes in wastewater treatment. CWs have various functional zones where contrasting biochemical processes occur. Since these zones are characterized by different particle-size composition, physicochemical conditions, and vegetation, one can expect the presence of distinct microbiomes across different CW zones. Here, we investigated spatial changes in microbiomes along different functional zones of a free-water surface wetland located in Moscow, Russia. The microbiome structure was analyzed using Illumina MiSeq amplicon sequencing. We also determined particle diameter and surface area of sediments, as well as chemical composition of organic pollutants in different CW zones. Specific organic particle aggregates similar to activated sludge flocs were identified in the sediments. The highest accumulation of hydrocarbons was found in the zones with predominant sedimentation of fine fractions. Phytofilters had the highest rate of organic pollutants decomposition and predominance of Smithella, Ignavibacterium, and Methanothrix. The sedimentation tank had lower microbial diversity, and higher relative abundances of Parcubacteria, Proteiniclasticum, and Macellibacteroides, as well as higher predicted abundances of genes related to methanogenesis and methanotrophy. Thus, spatial changes in microbiomes of constructed wetlands can be associated with different types of wastewater treatment processes. Full article
(This article belongs to the Special Issue Precision Microbiomics: Environment to Human Health)
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<p>Scheme of the constructed wetland studied. Zone I represents sand traps and grids; zone II—phytofilters; zone III—sedimentation tank; zone IV—phyto-treament; zone V—additional phyto-treatment. One or several sub-zones were selected in each functional zone.</p>
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<p>Chemical composition of organic pollutants in sediments of different zones of the constructed wetland. (<b>A</b>) hydrocarbons; (<b>B</b>) phthalates; (<b>C</b>) light polycyclic aromatic hydrocarbons (PAHs); (<b>D</b>) heavy PAHs.</p>
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<p>Physical composition of particles in sediments of different zones of the constructed wetland. (<b>A</b>) particle size distribution before and after ultrasonic; (<b>B</b>) mean weighted diameter of particles; (<b>C</b>) surface area of particles.</p>
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<p>Relative abundances of microbial taxa of considered functional zones of the constructed wetland at the phylum (<b>A</b>) and the class (<b>B</b>) levels. The data are presented for phyla and classes with abundance of more than 0.5%.</p>
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<p>Relative abundances of top 30 microbial taxa of considered functional zones of the constructed wetland at the genus level. The data is given as square roots of the read counts. Abundances of prokaryotic genera increase in a row: white–yellow–red–violet–dark blue.</p>
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<p>Alpha diversity (numbers of observed genera and Shannon indexes) of microbial communities of different functional zones of the constructed wetland.</p>
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<p>Microbiome clustering dendrogram of different functional zones of the constructed wetland based on Bray−Curtis (BC) distance matrix.</p>
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<p>Predicted microbial functional profiles of different zones of the constructed wetland. Processes were divided on two groups: (<b>A</b>) aerobic, low abundant processes; (<b>B</b>) anaerobic, abundant processes.</p>
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<p>The distribution of potentially pathogenic microbial genera in different zones of the CW. The pathogenicity of <span class="html-italic">Romboutsia</span> has not yet been confirmed, but they were included to the figure as they are typical human gut inhabitants.</p>
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20 pages, 974 KiB  
Article
Combined Comparative Genomics and Gene Expression Analyses Provide Insights into the Terpene Synthases Inventory in Trichoderma
by Isabel Vicente, Riccardo Baroncelli, María Eugenia Morán-Diez, Rodolfo Bernardi, Grazia Puntoni, Rosa Hermosa, Enrique Monte, Giovanni Vannacci and Sabrina Sarrocco
Microorganisms 2020, 8(10), 1603; https://doi.org/10.3390/microorganisms8101603 - 18 Oct 2020
Cited by 26 | Viewed by 4574
Abstract
Trichoderma is a fungal genus comprising species used as biocontrol agents in crop plant protection and with high value for industry. The beneficial effects of these species are supported by the secondary metabolites they produce. Terpenoid compounds are key players in the interaction [...] Read more.
Trichoderma is a fungal genus comprising species used as biocontrol agents in crop plant protection and with high value for industry. The beneficial effects of these species are supported by the secondary metabolites they produce. Terpenoid compounds are key players in the interaction of Trichoderma spp. with the environment and with their fungal and plant hosts; however, most of the terpene synthase (TS) genes involved in their biosynthesis have yet not been characterized. Here, we combined comparative genomics of TSs of 21 strains belonging to 17 Trichoderma spp., and gene expression studies on TSs using T. gamsii T6085 as a model. An overview of the diversity within the TS-gene family and the regulation of TS genes is provided. We identified 15 groups of TSs, and the presence of clade-specific enzymes revealed a variety of terpenoid chemotypes evolved to cover different ecological demands. We propose that functional differentiation of gene family members is the driver for the high number of TS genes found in the genomes of Trichoderma. Expression studies provide a picture in which different TS genes are regulated in many ways, which is a strong indication of different biological functions. Full article
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<p>Genomic inventory for terpenoid biosynthesis in <span class="html-italic">Trichoderma</span> spp. Terpene synthase (TS) proteins sharing conserved domains are highlighted in different colors: HAD-like (light blue), TRI5 (dark green), terpene synthase C (light green), squalene synthase-phytoene synthase (orange), prenyl transferase (red), squalene/hopene cyclase (light and dark brown), kaurene synthase and/or ent-copalyl diphosphate synthase (grey), and polyprenyl synthase and/or TS C (dark blue). Putative functions of terpene cyclases (TCs) and prenyl transferases (PTs) were assigned based on phylogenetic analysis performed with terpene synthase proteins with known function from filamentous fungi (<a href="#app1-microorganisms-08-01603" class="html-app">Table S2</a>) [<a href="#B53-microorganisms-08-01603" class="html-bibr">53</a>,<a href="#B54-microorganisms-08-01603" class="html-bibr">54</a>,<a href="#B55-microorganisms-08-01603" class="html-bibr">55</a>,<a href="#B56-microorganisms-08-01603" class="html-bibr">56</a>,<a href="#B57-microorganisms-08-01603" class="html-bibr">57</a>,<a href="#B58-microorganisms-08-01603" class="html-bibr">58</a>,<a href="#B59-microorganisms-08-01603" class="html-bibr">59</a>,<a href="#B60-microorganisms-08-01603" class="html-bibr">60</a>,<a href="#B61-microorganisms-08-01603" class="html-bibr">61</a>,<a href="#B62-microorganisms-08-01603" class="html-bibr">62</a>,<a href="#B63-microorganisms-08-01603" class="html-bibr">63</a>,<a href="#B64-microorganisms-08-01603" class="html-bibr">64</a>,<a href="#B65-microorganisms-08-01603" class="html-bibr">65</a>,<a href="#B66-microorganisms-08-01603" class="html-bibr">66</a>,<a href="#B67-microorganisms-08-01603" class="html-bibr">67</a>,<a href="#B68-microorganisms-08-01603" class="html-bibr">68</a>,<a href="#B69-microorganisms-08-01603" class="html-bibr">69</a>,<a href="#B70-microorganisms-08-01603" class="html-bibr">70</a>,<a href="#B71-microorganisms-08-01603" class="html-bibr">71</a>,<a href="#B72-microorganisms-08-01603" class="html-bibr">72</a>,<a href="#B73-microorganisms-08-01603" class="html-bibr">73</a>,<a href="#B74-microorganisms-08-01603" class="html-bibr">74</a>,<a href="#B75-microorganisms-08-01603" class="html-bibr">75</a>,<a href="#B76-microorganisms-08-01603" class="html-bibr">76</a>,<a href="#B77-microorganisms-08-01603" class="html-bibr">77</a>,<a href="#B78-microorganisms-08-01603" class="html-bibr">78</a>,<a href="#B79-microorganisms-08-01603" class="html-bibr">79</a>]. Proteins which did not clustered with any known protein were designed as uncharacterized TSs. Aspartate-rich motifs of Class I, Class II and Bifunctional enzymes were identified in the amino-acidic sequences of each group of proteins. Bootstrap values &gt; 50 are shown in the correspondent branches of the tree.</p>
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<p>Trichodiene synthases in <span class="html-italic">Trichoderma</span> spp. (<b>a</b>) Phylogenetic relations among trichodiene synthase (TRI5) proteins in <span class="html-italic">Trichoderma</span> spp. and multiple alignment of the active center of the proteins were obtained using MAFFT v7.450 [<a href="#B52-microorganisms-08-01603" class="html-bibr">52</a>] and FasTree v2.1.11 [<a href="#B81-microorganisms-08-01603" class="html-bibr">81</a>]. Aspartate-rich metal binding motifs are indicated with asterisks. (<b>b</b>) Biosynthetic gene cluster containing <span class="html-italic">tri5</span> and putative functions of the enclosing genes found in strains of <span class="html-italic">T. gamsii</span>. (<b>c</b>) Phylogenetic distribution of <span class="html-italic">tri5</span> and their associated biosynthetic gene clusters in <span class="html-italic">Trichoderma</span> spp. Phylogenetic relations of <span class="html-italic">Trichoderma</span> spp. were obtained using MAFFT v7.450 [<a href="#B52-microorganisms-08-01603" class="html-bibr">52</a>] and FasTree v2.1.11 [<a href="#B81-microorganisms-08-01603" class="html-bibr">81</a>], using concatenated alignment of <span class="html-italic">actin</span>, <span class="html-italic">calmodulin</span> and <span class="html-italic">transcription elongation factor-1</span> genes. Phylogenetic clades, according to Kubicek et al. (2019) [<a href="#B30-microorganisms-08-01603" class="html-bibr">30</a>], are shown in two different grey colors. Genes belonging to variants of the TRI loci reported in species of the clade Brevicompactum and <span class="html-italic">B. bassiana</span>, respectively, are shown in light blue. Genes found associated to <span class="html-italic">tri5</span> (in purple) in <span class="html-italic">T. gamsii</span> are shown in red.</p>
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<p>Gene expression studies of terpene synthase genes in <span class="html-italic">T. gamsii</span> T6085 in different environment conditions. (<b>a</b>) Liquid cultures of <span class="html-italic">T. gamsii</span> T6085 (<span class="html-italic">Tgam</span>) in different substrates. Total RNA was extracted from 4-day-old mycelium of <span class="html-italic">Tgam</span> grown on minimal medium without sucrose (MM) (basal condition, 2<sup>−ΔΔ<span class="html-italic">C</span>t</sup> = 1), or MM with 0.9% sucrose, MM 0.5 mM H<sub>2</sub>O<sub>2</sub>, MM with only 0.01% of nitrogen (N starvation), or 200 mM NaCl, respectively. Grey color bars represent relative expression values of TS genes on each condition. (<b>b</b>) Interaction of <span class="html-italic">Tgam</span> with <span class="html-italic">F. graminearum</span> (<span class="html-italic">Fgra</span>) on wheat spikes. Total RNA was extracted from wheat spikes colonized by <span class="html-italic">Tgam</span> alone (basal condition, 2<sup>−ΔΔ<span class="html-italic">C</span>t</sup> = 1) or by <span class="html-italic">Tgam</span> + <span class="html-italic">Fgra</span>, 6 days after inoculation of the pathogen. (<b>c</b>) Interaction of <span class="html-italic">Tgam</span> with wheat roots. Total RNA was extracted from mycelium of <span class="html-italic">Tgam</span> grown on PDA for 3 days (basal condition, 2<sup>−ΔΔ<span class="html-italic">C</span>t</sup> = 1) and from wheat roots colonized by <span class="html-italic">Tgam</span> for 3 days. The β-<span class="html-italic">tubulin</span> gene was used as control for data normalization. Values are means of three independent biological replicates with the corresponding standard deviation. Fold change in sample relative to control is expressed as 2<sup>−ΔΔ<span class="html-italic">C</span>t</sup>. Statistically significant values are indicated with asterisks (<span class="html-italic">p</span> ≥ 0.05 no significative; 0.05 &gt; <span class="html-italic">p</span> ≥ 0.01 = *; 0.01&gt; <span class="html-italic">p</span> ≥ 0.001 = **; <span class="html-italic">p</span> &lt; 0.001 = ***).</p>
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6 pages, 469 KiB  
Communication
A Preliminary Study on the Presence of Salmonella in Lymph Nodes of Sows at Processing Plants in the United States
by Roger B. Harvey, Keri N. Norman, Robin C. Anderson and David J. Nisbet
Microorganisms 2020, 8(10), 1602; https://doi.org/10.3390/microorganisms8101602 - 18 Oct 2020
Cited by 6 | Viewed by 2305
Abstract
Salmonella-contaminated lymph nodes (LN), when included into edible meat products, are a potential source of Salmonella foodborne disease. In this survey, ventral superficial cervical and mandibular LN were tested for the presence of Salmonella from two sow processing plants in the midwestern [...] Read more.
Salmonella-contaminated lymph nodes (LN), when included into edible meat products, are a potential source of Salmonella foodborne disease. In this survey, ventral superficial cervical and mandibular LN were tested for the presence of Salmonella from two sow processing plants in the midwestern United States. Results indicate that both LN can be contaminated with Salmonella; mandibular LN have higher prevalence (p < 0.05) of Salmonella than cervical LN (16% vs. 0.91%), and the majority (>90%) of Salmonella isolates are pan-susceptible or resistant to one antimicrobial, while 9.78% of isolates were multi-drug-resistant (MDR-resistant to three or more classes of antimicrobials). Intervention methods to prevent foodborne disease could include elimination of these LN from pork products or inclusion of LN only into products that are destined for cooking. Integrated multi-faceted intervention methods need to be developed to reduce Salmonella in the food chain. Full article
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<p>Prevalence of <span class="html-italic">Salmonella</span> in lymph nodes of sows at processing.</p>
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12 pages, 1766 KiB  
Article
Bacterial Community Dynamics Distinguish Poultry Compost from Dairy Compost and Non-Amended Soils Planted with Spinach
by Deborah A. Neher, Marie A. Limoges, Thomas R. Weicht, Manan Sharma, Patricia D. Millner and Catherine Donnelly
Microorganisms 2020, 8(10), 1601; https://doi.org/10.3390/microorganisms8101601 - 18 Oct 2020
Cited by 15 | Viewed by 3123
Abstract
The aim of this study was to determine whether and how poultry litter compost and dairy manure compost alter the microbial communities within field soils planted with spinach. In three successive years, separate experimental plots on two fields received randomly assigned compost treatments [...] Read more.
The aim of this study was to determine whether and how poultry litter compost and dairy manure compost alter the microbial communities within field soils planted with spinach. In three successive years, separate experimental plots on two fields received randomly assigned compost treatments varying in animal origin: dairy manure (DMC), poultry litter (PLC), or neither (NoC). The composition and function of bacterial and fungal communities were characterized by the amplicon sequencing of marker genes and by the ecoenzyme activity, respectively. The temporal autocorrelation within and among years was adjusted by principal response curves (PRC) to analyze the effect of compost on community composition among treatments. Bacteria in the phylum Bacteriodetes, classes Flavobacteriia and Spingobacteriales (Fluviicola, Flavobacteriia, and Pedobacter), were two to four times more abundant in soils amended with PLC than DMC or NoC consistently among fields and years. Fungi in the phylum Ascomycota were relatively abundant, but their composition was field-specific and without treatment differences. The ecoenzyme data verify that the effects of PLC and DMC on soil communities are based on their microbial composition and not a response to the C source or nutrient content of the compost. Full article
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<p>First principal response curve coefficient (PRC.1 with explained fitted variation in parentheses) of the 16S amplicon sequences for (<b>a</b>) Lilac and (<b>b</b>) Wheelock. Curves represent the deviation between a compost treatment (dashed: dairy manure; solid: poultry litter) from a non-amended control (dotted-dash) as a function of time, with 0 as the day of compost amendment in 2015 and the continuous calendar time until the end of the 2017 season. Symbols mark the sampling times. The weights of the 25 best-fit OTUs are shown on the right axis. Missing taxonomic information occurs if higher resolution was not available (na) for the OTU. Monte Carlo permutation tests permuting whole time series were applied to compute the statistical significance (<span class="html-italic">n</span> = 186 for Lilac, 181 for Wheelock).</p>
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<p>First principal response curve coefficient (PRC.1 with explained fitted variation in parentheses) of the ITS amplicon sequences for (<b>a</b>) Lilac and (<b>b</b>) Wheelock. Curves represent the deviation between a compost treatment (dashed: dairy manure; solid: poultry litter) from a non-amended control (dotted-dash) as a function of time, with 0 as the day of compost amendment in 2015 and the continuous calendar time until the end of 2017 season. Symbols mark the sampling times. The weights of the 25 best-fit OTUs are shown on the right axis. Missing taxonomic information occurs if a higher resolution was not available for the OTU (Unclassified: Uncl). Monte Carlo permutation tests permuting whole time series were applied to compute the statistical significance (<span class="html-italic">n</span> = 137 for Lilac, 165 for Wheelock).</p>
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<p>Order of magnitude in amplicon abundance compared to the no-compost control. Both fields and three years were combined. Bar colors represent phyla Sphingobacteriia (yellow), Flavobacteriia (orange), γ-Proteobacteria (purple), and Fibrobacteria (brown).</p>
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<p>Ecoenzyme activity of C:N (<span class="html-italic">y</span>-axis) as a function of C:P (<span class="html-italic">x</span>-axis) over time, with a dashed line representing the 1:1 reference. Treatments are organized by column: (<b>a</b>,<b>d</b>,<b>g</b>) no compost, (<b>b</b>,<b>e</b>,<b>h</b>) dairy compost, and (<b>c</b>,<b>f</b>,<b>i</b>) poultry litter compost. C, N, and P activity were measured by BG: β-1,4-glucosidase, NAG: β-1,4-N-acetylglucosaminidase plus LUC: L-leucine aminopeptidase, and AP: phosphatase, respectively. Each row represents a study year: (<b>a</b>–<b>c</b>) 2015, (<b>d</b>–<b>f</b>) 2016, and (<b>g</b>–<b>i</b>) 2017. Within each panel, colors represent the sampling times within a year: (1) black; (2) blue; (3) green; (4) red; (5) purple; (6) orange; (7) fuchsia; (8) brown. Fields are labeled as Lilac soil (open circle) and Wheelock soil (closed circle).</p>
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14 pages, 3296 KiB  
Article
In silico Investigation on the Inhibiting Role of Nicotine/Caffeine by Blocking the S Protein of SARS-CoV-2 Versus ACE2 Receptor
by Saeedeh Mohammadi, Mohammad Heidarizadeh, Mehrnaz Entesari, Ayoub Esmailpour, Mohammad Esmailpour, Rasoul Moradi, Nader Sakhaee and Esmail Doustkhah
Microorganisms 2020, 8(10), 1600; https://doi.org/10.3390/microorganisms8101600 - 17 Oct 2020
Cited by 23 | Viewed by 7797
Abstract
In this paper, we studied the in silico interaction of angiotensin-converting enzyme 2 (ACE2) human receptor with two bioactive compounds, i.e., nicotine and caffeine, via molecular dynamic (MD) simulations. The simulations reveal the efficient blocking of ACE2 by caffeine and nicotine in the [...] Read more.
In this paper, we studied the in silico interaction of angiotensin-converting enzyme 2 (ACE2) human receptor with two bioactive compounds, i.e., nicotine and caffeine, via molecular dynamic (MD) simulations. The simulations reveal the efficient blocking of ACE2 by caffeine and nicotine in the exposure to the spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We have selected the two most important active sites of ACE2-S protein, i.e., 6LZG and 6VW1, which are critically responsible in the interaction of S protein to the receptor and thus, we investigated their interaction with nicotine and caffeine through MD simulations. Caffeine and nicotine are interesting structures for interactions because of their similar structure to the candidate antiviral drugs. Our results reveal that caffeine or nicotine in a specific molar ratio to 6LZG shows a very strong interaction and indicate that caffeine is more efficient in the interaction with 6LZG and further blocking of this site against S protein binding. Further, we investigated the interaction of ACE2 receptor- S protein with nicotine or caffeine when mixed with candidate or approved antiviral drugs for SARS-CoV-2 therapy. Our MD simulations suggest that the combination of caffeine with ribavirin shows a stronger interaction with 6VW1, while in case of favipiravir+nicotine, 6LZG shows potent efficacy of these interaction, proposing the potent efficacy of these combinations for blocking ACE2 receptor against SARS-CoV-2. Full article
(This article belongs to the Section Molecular Microbiology and Immunology)
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<p>Comparing the chemical structure of (<b>a</b>) favipiravir with nicotine and (<b>b</b>) caffeine with valganciclovir; their similarities from chemical structure point of view are highlighted in yellow.</p>
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<p>The phytochemical structures of antiviral drugs studied.</p>
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<p>Interaction between ACE2/SARS-CoV-2-CTD (6LZG) complex with (<b>a</b>) nicotine and (<b>b</b>) caffeine. The green regions (and the corresponding magnified inlays) represent the active sites.</p>
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<p>Energies and temperatures versus simulation time for (<b>a</b>) total, (<b>b</b>) non-bonded, and (<b>c</b>) potential energies. The plots show the temperatures for (<b>d</b>) CTD-ACE2+caffeine (6LZG+C), (<b>e</b>) RBD-ACE2+hydroxychloroquine+caffeine (6VW1+HC), and (<b>f</b>) CTD-ACE2+favipiravir+nicotine (6LZG+FN).</p>
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<p>The interaction energies (IEs) for different ratios of (<b>a</b>) caffeine and (<b>b</b>) nicotine structures with 6LZG and 6VW1.</p>
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<p>The interaction and non-bonded energies for drug and caffeine/nicotine structures with 6VW1 (RBD-ACE2) and 6LZG (CTD-ACE2). (<b>a</b>,<b>b</b>) The interaction energies caffeine and nicotine, (<b>c</b>,<b>d</b>) the non-bonded energies caffeine and nicotine, respectively.</p>
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<p>The bond and van der Waals energies for drug and caffeine/nicotine structures with 6VW1 (RBD-ACE2) and 6LZG (CTD-ACE2). (<b>a</b>,<b>b</b>) The bond energies caffeine and nicotine, (<b>c</b>,<b>d</b>) the van der Waals energies caffeine and nicotine, respectively.</p>
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<p>The interaction energies for different ratios of the structures of favipiravir and ribavirin with ACE2/SARS-CoV-2-CTD (6LZG) and RBD-ACE2 (6VW1). The 6LZG+F and 6VW1+R display 6LZG+favipiravir and 6VW1+ribavirin, respectively.</p>
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12 pages, 1648 KiB  
Article
Identification and Elimination of the Clinically Relevant Multi-Resistant Environmental Bacteria Ralstonia insidiosa in Primary Cell Culture
by Dennis Nurjadi, Sébastien Boutin, Katja Schmidt, Melinda Ahmels and Daniel Hasche
Microorganisms 2020, 8(10), 1599; https://doi.org/10.3390/microorganisms8101599 - 17 Oct 2020
Cited by 11 | Viewed by 4523
Abstract
In times of spreading multidrug-resistant bacteria, species identification and decontamination of cell cultures can be challenging. Here, we describe a mobile cell culture contaminant with “black dot”-like microscopic appearance in newly established irreplaceable hybridoma cell lines and its identification. Using 16S rRNA gene [...] Read more.
In times of spreading multidrug-resistant bacteria, species identification and decontamination of cell cultures can be challenging. Here, we describe a mobile cell culture contaminant with “black dot”-like microscopic appearance in newly established irreplaceable hybridoma cell lines and its identification. Using 16S rRNA gene sequencing, species-specific PCRs, whole genome sequencing (WGS), and MALDI-TOF mass spectrometry, the contaminant was identified as the ubiquitous environmental and clinically relevant Gram-negative bacterium Ralstonia insidiosa (R. insidiosa), a strong biofilm producer. Further characterizations by transmission electron microscopy (TEM) and biochemical API test were not conclusive. Whole genome sequencing of our R. insidiosa isolate revealed numerous drug-resistance determinants. Genome-wide comparison to other Ralstonia species could not unambiguously designate our isolate to R. insidiosa (<95% average nucleotide identity) suggesting a potential novel species or subspecies, closely related to R. insidiosa and R. pickettii. After determining the antibiotic susceptibility profile, the hybridoma cell culture was successfully decontaminated with ciprofloxacin without affecting antibody production. Full article
(This article belongs to the Section Antimicrobial Agents and Resistance)
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<p>Microscopic observation of the contamination. (<b>A</b>) Contaminated hybridoma culture visualized with a 20× objective. (<b>B</b>) Propagated contamination visualized with a 40× objective. Only a few dead hybridoma cells were left, while bacteria produced a biofilm. #: vital hybridoma cells, *: dead hybridoma cell, grey arrows: swimming bacteria, black arrows: attached bacteria in a biofilm. (<b>C</b>) TEM picture of the bacteria at 20,000× magnification. (<b>D</b>) TEM picture of the bacteria at 40,000× magnification.</p>
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<p>PCR, biochemical and phylogenetic analyses of the contamination. (<b>A</b>) 16S rRNA gene amplification for sequencing with two different primer combinations (CC: sample from contaminated cell culture; H<sub>2</sub>O: water control). (<b>B</b>) Specific identification of <span class="html-italic">Ralstonia</span> species via PCR (CC: sample from contaminated cell culture; PC: pure culture of <span class="html-italic">R. insidiosa</span>; H<sub>2</sub>O: water control). (<b>C</b>) Gram stain of <span class="html-italic">R. insidiosa</span> pure culture originating from the cell culture visualized with a 100× objective (scale bar: 5 µm). (<b>D</b>) Image of the API<sup>®</sup> 20 NE test strip 48 h after inoculation. (<b>E</b>) Phylogenetic tree based on the core genome (378 genes) of all complete genomes of <span class="html-italic">Ralstonia</span> spp. found in the Refseq database. The framed tree is based on the core genome (3497 genes) of complete and draft genomes of <span class="html-italic">R. insidiosa</span> strains.</p>
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13 pages, 2061 KiB  
Article
Crucial Role of the C-Terminal Domain of Hfq Protein in Genomic Instability
by Virali J. Parekh, Frank Wien, Wilfried Grange, Thomas A. De Long, Véronique Arluison and Richard R. Sinden
Microorganisms 2020, 8(10), 1598; https://doi.org/10.3390/microorganisms8101598 - 17 Oct 2020
Cited by 10 | Viewed by 4611
Abstract
G-rich DNA repeats that can form G-quadruplex structures are prevalent in bacterial genomes and are frequently associated with regulatory regions of genes involved in virulence, antigenic variation, and antibiotic resistance. These sequences are also inherently mutagenic and can lead to changes affecting cell [...] Read more.
G-rich DNA repeats that can form G-quadruplex structures are prevalent in bacterial genomes and are frequently associated with regulatory regions of genes involved in virulence, antigenic variation, and antibiotic resistance. These sequences are also inherently mutagenic and can lead to changes affecting cell survival and adaptation. Transcription of the G-quadruplex-forming repeat (G3T)n in E. coli, when mRNA comprised the G-rich strand, promotes G-quadruplex formation in DNA and increases rates of deletion of G-quadruplex-forming sequences. The genomic instability of G-quadruplex repeats may be a source of genetic variability that can influence alterations and evolution of bacteria. The DNA chaperone Hfq is involved in the genetic instability of these G-quadruplex sequences. Inactivation of the hfq gene decreases the genetic instability of G-quadruplex, demonstrating that the genomic instability of this regulatory element can be influenced by the E. coli highly pleiotropic Hfq protein, which is involved in small noncoding RNA regulation pathways, and DNA organization and packaging. We have shown previously that the protein binds to and stabilizes these sequences, increasing rates of their genomic instability. Here, we extend this analysis to characterize the role of the C-terminal domain of Hfq protein in interaction with G-quadruplex structures. This allows to better understand the function of this specific region of the Hfq protein in genomic instability. Full article
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Graphical abstract

Graphical abstract
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<p>Mutation rates for (G<sub>3</sub>T)<sub>8</sub> repeats in plasmids pBR325 and pBR235 in MG1655 <span class="html-italic">hfq</span>-Cm<sup>r</sup> (reference strain), MG1655 HfqNTR72-Cm<sup>r</sup> (∆CTR), and MG1655 <span class="html-italic">hfq</span>::Cm<sup>r</sup> (∆<span class="html-italic">hfq</span>) [<a href="#B38-microorganisms-08-01598" class="html-bibr">38</a>]. Mutation rates were determined as described under Materials and Methods. Data for MG1655 <span class="html-italic">hfq</span>-Cm<sup>r</sup> and MG1655 NTR72-Cm<sup>r</sup> with both pBR325 and pBR235 represent results from two independent Luria–Delbrück fluctuation analyses. Results for plasmids in MG1655 <span class="html-italic">Δhfq</span>::Cm<sup>r</sup> represent a single Luria–Delbrück fluctuation analysis. Error bars represent 84% confidence intervals. Numbers represent false discovery rates.</p>
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<p>Hfq Binding to (G<sub>3</sub>T)<sub>4</sub>. (<b>A</b>) Hfq-CTR binding to (G<sub>3</sub>T)<sub>4</sub>, (G<sub>3</sub>T)<sub>4</sub> concentration 0.1 μM, while Hfq-CTR concentration ranged from 0 to 3 μM. (<b>B</b>) Graphic analysis of Hfq-CTR binding to (G<sub>3</sub>T)<sub>4</sub> shown in A. (<b>C</b>) controls: Hfq-NTR and wild type Hfq binding to (G<sub>3</sub>T)<sub>4</sub>.</p>
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<p>Synchrotron radiation circular dichroism (SRCD) analysis of the (G<sub>3</sub>T)<sub>4</sub> quadruplex complexed to Hfq-CTR. Spectra of (G<sub>3</sub>T)<sub>4</sub> in the absence (red) and presence of Hfq-CTR (blue). Hfq alone (green). The spectrum of the complex (blue) is similar to the sum of the (G<sub>3</sub>T)<sub>4</sub> and Hfq-CTR spectra (dotted black), differing only in the strength of its amplitudes. This signifies most likely that upon complex formation, an enhancement of already existing structural features in the quadruplex is occurring. It is not clear whether the Hfq-CTR in contact with (G<sub>3</sub>T)<sub>4</sub> changes its structure, to form amyloids, which would change the 210–220 nm amplitudes of the spectrum [<a href="#B38-microorganisms-08-01598" class="html-bibr">38</a>].</p>
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<p>Model of direct and indirect effects of Hfq on genome instability. Description of the figure is included in the text. Direct effects: Green ovals represent DNA Pol III; blue ovals, RNA polymerase. Hfq is represented by the donut. Indirect effects: MutS is represented by the brown ovals. Red arrows represent increased or decreased levels.</p>
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