scholarly journals Triclosan resistant bacteria in sewage effluent and cross-resistance to antibiotics

2017 ◽  
Vol 76 (6) ◽  
pp. 1500-1509 ◽  
Author(s):  
I. Coetzee ◽  
C. C. Bezuidenhout ◽  
J. J. Bezuidenhout
Keyword(s):  
High Performance ◽  
Treatment Plant ◽  
16S Rrna Gene Sequencing ◽  
Plate Count ◽  
Cross Resistance ◽  
Resistant Bacteria ◽  
Rrna Gene ◽  
Sewage Effluent ◽  
Resistance To Antibiotics ◽  
The Impact

The purpose of this study was to identify triclosan tolerant heterotrophic plate count (HPC) bacteria from sewage effluent and to determine cross-resistance to antibiotics. R2 agar supplemented with triclosan was utilised to isolate triclosan resistant bacteria and 16S rRNA gene sequencing was conducted to identify the isolates. Minimum inhibitory concentrations (MICs) of organisms were determined at selected concentrations of triclosan and cross-resistance to various antibiotics was performed. High-performance liquid chromatography was conducted to quantify levels of triclosan in sewage water. Forty-four HPC were isolated and identified as the five main genera, namely, Bacillus, Pseudomonas, Enterococcus, Brevibacillus and Paenibacillus. MIC values of these isolates ranged from 0.125 mg/L to >1 mg/L of triclosan, while combination of antimicrobials indicated synergism or antagonism. Levels of triclosan within the wastewater treatment plant (WWTP) ranged between 0.026 and 1.488 ppb. Triclosan concentrations were reduced by the WWTP, but small concentrations enter receiving freshwater bodies. Results presented indicate that these levels are sufficient to maintain triclosan resistant bacteria under controlled conditions. Further studies are thus needed into the impact of this scenario on such natural receiving water bodies.

scholarly journals Prophylactic Treatment of Undernourished Mice with Cotrimoxazole Induces a Different Profile of Dysbiosis with Functional Metabolic Alterations

2021 ◽  
Author(s):  
Livia Budziarek Eslabao ◽  
Gabriela Farias Gubert ◽  
Lucas C. Beltrame ◽  
Isis M. A. de Mello ◽  
Oscar Bruna-Romero ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Prophylactic Treatment ◽  
Wide Spectrum ◽  
Clinical Signs ◽  
16S Rrna Gene Sequencing ◽  
Significant Loss ◽  
World Health ◽  
Resistant Bacteria ◽  
Rrna Gene ◽  
The Impact

Childhood malnutrition affects physiology and development, it increases infection rate which may not present clinical signs in severe cases. To overcome this issue, the World Health Organization recommends prophylactic treatment with Cotrimoxazole (SXT) along with nutritional recovery. This treatment is controversial since evidence of reduction in morbidity and mortality is not a consensus and could induce the development of antibiotic resistant bacteria. Moreover, the impact of the use of this wide-spectrum antibiotic on gut microbiota, in a critical period of development and weakness, is unknown. To understand how SXT prophylaxis could affect gut microbiota in undernutrition, we induced protein-energy undernutrition in weaning C57BL/6 mice for three weeks and treated animals with SXT for two weeks. Using 16S rRNA gene sequencing we compared the taxonomic composition and metabolic pathways of control mice, animals submitted to undernutrition (UND), treated with SXT, or undernourished and SXT treated (UND+SXT). Undernutrition protocol was responsible for increasing Bacteroidetes and decreasing Firmicutes abundance. We identified that UND mice had a significant increase in predicted pathways related to metabolic syndromes later in life. The prophylactic SXT treatment alone resulted in significant loss in community richness and beta diversity. In addition, we identified the reduction of 6 families in SXT treated mice, including the butyrate producers Lachnospiraceae and Ruminococcaceae. The double challenge (UND+SXT) resulted in a reduction in Clostridiaceae family and in the urea cycle pathway, both related to the fermentation of amino acids, the intestinal epithelial permeability, and the healthy gut environment. Our results show that SXT prophylaxis during an undernourishment period in young mice did not re-establish the undernourished microbiota community composition similar to healthy controls, but induces a distinct dysbiotic profile, with functional metabolic consequences.

scholarly journals Effects of Psychotropics on the Microbiome in Patients With Depression and Anxiety: Considerations in a Naturalistic Clinical Setting

2020 ◽  
Author(s):  
Yoshihiro Tomizawa ◽  
Shunya Kurokawa ◽  
Daiki Ishii ◽  
Katsuma Miyaho ◽  
Chiharu Ishii ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Microbial Diversity ◽  
Depressive Disorders ◽  
Alpha Diversity ◽  
16S Rrna Gene Sequencing ◽  
Shannon Index ◽  
Rrna Gene ◽  
Depression And Anxiety ◽  
The Impact ◽  
Whole Tree

Abstract Background The antibacterial effects of psychotropics may be part of their pharmacological effects when treating depression. However, limited studies have focused on gut microbiota in relation to prescribed medication. Method We longitudinally investigated the relationship between patients’ prescribed medications and intestinal bacterial diversity in a naturalistic treatment course for patients with major depressive disorders and anxiety disorders. Patients were recruited and their stool was collected at 3 time points during their usual psychiatric treatments. Gut microbiota were analyzed using 16S rRNA gene sequencing. We examined the impact of psychotropics (i.e., antidepressants, anxiolytics, antipsychotics) on their gut microbial diversity and functions. Results We collected 246 stool samples from 40 patients. Despite no differences in microbial diversity between medication groups at the baseline, over the course of treatment, phylogenic diversity whole-tree diversity decreased in patients on antipsychotics compared with patients without (P = .027), and beta diversity followed this trend. Based on a fixed-effect model, antipsychotics predicted microbial diversity; the higher doses correlated with less diversity based on the Shannon index and phylogenic diversity whole tree (estimate = −0.00254, SE = 0.000595, P < .0001; estimate = −0.02644, SE = 0.00833, P = .002, respectively). Conclusion Antipsychotics may play a role in decreasing the alpha diversity of the gut microbiome among patients with depression and anxiety, and our results indicate a relationship with medication dosage. Future studies are warranted and should consider patients’ types and doses of antipsychotics in order to further elucidate the mechanisms of gut-brain interactions in psychiatric disorders.

scholarly journals Refinement of metabolite detection in cystic fibrosis sputum reveals heme negatively correlates with lung function

2018 ◽  
Author(s):  
Nathaniel R. Glasser ◽  
Ryan C. Hunter ◽  
Theodore G. Liou ◽  
Dianne K. Newman ◽  
Keyword(s):  
Mass Spectrometry ◽  
Cystic Fibrosis ◽  
Lung Function ◽  
High Performance ◽  
16S Rrna Gene Sequencing ◽  
Initial Study ◽  
Rrna Gene ◽  
Sequencing Data ◽  
Unknown Compound ◽  
Mountain West

SummaryPseudomonas aeruginosalung infections are a leading cause of morbidity and mortality in cystic fibrosis (CF) patients (1, 2). Our laboratory has studied a class of small molecules produced byP. aeruginosaknown as phenazines, including pyocyanin and its biogenic precursor phenazine-1-carboxylic acid (PCA). As phenazines are known virulence factors (3), we and others have explored the possibility of using phenazine concentrations as a marker for disease progression (4–6). Previously, we reported that sputum concentrations of pyocyanin and PCA negatively correlate with lung function in cystic fibrosis patients (6). Our study used high performance liquid chromatography (HPLC) to quantify phenazines by UV–vis absorbance after extraction from lung sputum. Since our initial study, methods for metabolite analysis have advanced considerably, aided in large part by usage of mass spectrometry (LC-MS) and tandem mass spectrometry (LC-MS/MS). Because a more recent study employing LC-MS/MS revealed a surprising decoupling ofP. aeruginosametabolites in sputum and the detection ofP. aeruginosathrough culturing or microbiome profiles (4), we decided to check whether we could reproduce our previous findings by analyzing sputum samples from a different patient cohort with a new LC-MS instrument in our laboratory. Our new samples were provided by the Mountain West CF Consortium Sputum Biomarker study (7). In the course of performing our new analyses, comparison of our old HPLC data to our new LC-MS data led us to realize that the peak previously assigned to PCA instead originates from heme, and the peak assigned to pyocyanin originates from an as-yet unknown compound. This correction only affects the measurements of phenazines in sputum, and we are confident in the phenazine measurements from isolated cultures and the 16S rRNA gene sequencing data from that study (6). Here we outline the basis for our correction and present additional data showing that heme concentration negatively correlates with lung function in cystic fibrosis patients.

199 Do the Microbiomes of Horses Process Nutrients Differently Based on Keeper Status?

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 106-106
Author(s):  
Alexa C Johnson ◽  
Amy S Biddle
Keyword(s):  
Fixed Effects ◽  
High Performance ◽  
16S Rrna Gene Sequencing ◽  
Gas Production ◽  
Rrna Gene ◽  
Total N ◽  
Fermentation Products ◽  
Fecal Samples ◽  
Α Diversity ◽  
C 50

Abstract This study reports the differential response of the equine gut microbiome to protein and/or carbohydrate based on keeper status (easy keeper (EK), medium keeper (MK), hard keeper (HK)). Anaerobic equine fecal samples (n = 12 total, n = 3 / EK, MK, HK of four breeds) inoculated microcosms with three dietary conditions (C = Carb (cornmeal), P = Protein (soybean meal), and M = mix (50% C, 50% P)). Over 48 hours, fermentation products were measured using colorimetric assays and high-performance liquid chromatography. Microbial populations were surveyed using 16S rRNA gene sequencing analyzed by QIIME2. Linear mixed models were fit with fixed effects of Treatment and Keeper status and their interactions, with random effects of HorseID. Differences in fermentation products by keeper status included: MK had higher pH and greater gas production, EK produced higher hydrogen sulfide, and HK had greater total protein. Total SCFA was not different between keeper status (P = 0.89) but the acetate: propionate ratio was highest for HK (2.45mM) and lowest for EK (1.85mM) (P = 0.05). Isobutyrate production was highest in HK (2.34mM) compared to MK (0.85mM) and EK (0.17mM). Treatment had significant effects across all measurements; M and C treatment values were similar reflecting microbial preferences for carbohydrates before protein. P treated trials had increased fermentation outputs due to lower acidity effects. Keeper status had no effect on α-diversity (P > 0.05) however HK horses were least affected by treatments. P treated samples were more diverse than C and M (P < 0.001). Spearman correlation of Keeper x Treatment identified Oligosphaeria spp. in EK (r = 0.49) and Fusobacteria spp. in HK whole fecal samples (r = 0.37). These data suggest that while the compositions of the gut microbiomes of keeper groups were similar, they were functionally different in processing key nutrients.

Characterization of bacteria and antibiotic resistance in commercially-produced cheeses sold in China

2021 ◽  
Author(s):  
Jinghui Yao ◽  
Jing Gao ◽  
Jianming Guo ◽  
Hengan Wang ◽  
En Zhang ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Lactic Acid ◽  
Lactic Acid Bacteria ◽  
Acquired Resistance ◽  
Antibiotic Resistance Genes ◽  
16S Rrna Gene Sequencing ◽  
Multidrug Resistant ◽  
Resistant Bacteria ◽  
Rrna Gene ◽  
Rrna Gene Sequencing

The consumption of cheese in China is increasing rapidly. Little is known about the microbiota, the presence of antibiotic-resistant bacteria, or the distribution of antibiotic resistance genes (ARGs) in commercially-produced cheeses sold in China. These are important criteria for evaluating quality and safety. Thus, this study assessed the metagenomics of fifteen types of cheese using 16S rRNA gene sequencing. Fourteen bacterial genera were detected. Lactococcus , Lactobacillus , and Streptococcus were dominant based on numbers of sequence reads. Multidrug-resistant lactic acid bacteria were isolated from most of the types of cheese. The isolates showed 100% and 91.7% resistance to streptomycin and sulfamethoxazole, respectively, and genes involved in acquired resistance to streptomycin ( strB) and sulfonamides ( sul2) were detected with high frequency. To analyze the distribution of ARGs in the cheeses in overall, 309 ARGs from eight categories of ARG and nine transposase genes were profiled. A total of 169 ARGs were detected in the 15 cheeses; their occurrence and abundance varied significantly between cheeses. Our study demonstrates that there is various diversity of the bacteria and ARGs in cheeses sold in China. The risks associated with multidrug resistance of dominant lactic acid bacteria are of great concern.

scholarly journals Identification of a Shared Microbiomic and Metabolomic Profile in Systemic Autoimmune Diseases

2019 ◽  
Vol 8 (9) ◽  
pp. 1291 ◽  
Author(s):  
Bellocchi ◽  
Fernández-Ochoa ◽  
Montanelli ◽  
Vigone ◽  
Santaniello ◽  
...  
Keyword(s):  
Autoimmune Diseases ◽  
Lupus Erythematosus ◽  
High Performance ◽  
16S Rrna Gene Sequencing ◽  
Study Groups ◽  
Mass Spectrometry Analysis ◽  
Rrna Gene ◽  
Operating Characteristics ◽  
Systemic Autoimmune Diseases ◽  
Spectrometry Analysis

Dysbiosis has been described in systemic autoimmune diseases (SADs), including systemic lupus erythematosus (SLE), Sjögren’s syndrome (SjS), and primary anti-phosholipid syndrome (PAPS), however the biological implications of these associations are often elusive. Stool and plasma samples from 114 subjects, including in SLE (n = 27), SjS (n = 23), PAPs (n = 11) and undifferentiated connective tissue (UCTD, n = 26) patients, and geographically-matched healthy controls (HCs, n = 27), were collected for microbiome (16s rRNA gene sequencing) and metabolome (high-performance liquid chromatography coupled to mass spectrometry) analysis to identify shared characteristics across diseases. Out of 130 identified microbial genera, a subset of 29 bacteria was able to differentiate study groups (area under receiver operating characteristics (AUROC) = 0.730 ± 0.025). A fair classification was obtained with a subset of 41 metabolic peaks out of 254 (AUROC = 0.748 ± 0.021). In both models, HCs were well separated from SADs, while UCTD largely overlapped with the other diseases. In all of the SADs pro-tolerogenic bacteria were reduced, while pathobiont genera were increased. Metabolic alterations included two clusters comprised of: (a) members of the acylcarnitine family, positively correlating with a Prevotella-enriched cluster and negatively correlating with a butyrate-producing bacteria-enriched cluster; and (b) phospholipids, negatively correlating with butyrate-producing bacteria. These findings demonstrate a strong interaction between intestinal microbiota and metabolic function in patients with SADs.

scholarly journals In Vitro Fecal Fermentation Patterns of Arabinoxylan from Rice Bran on Gut Microbiota in Normal Weight and Overweight/Obese Subjects

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1560-1560
Author(s):  
Inah Gu ◽  
Wing Shun Lam ◽  
Daya Marasini ◽  
Cindi Brownmiller ◽  
Brett Savary ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Rice Bran ◽  
Block Design ◽  
16S Rrna Gene Sequencing ◽  
Short Chain Fatty Acids ◽  
Normal Weight ◽  
Rrna Gene ◽  
Gut Health ◽  
The Impact

Abstract Objectives Arabinoxylan is a non-starch polysaccharide and rich in wheat, rice and many other cereal grains. Diets high in fiber help promoting gut health in obesity. The objective of this study was to investigate the impact of arabinoxylan from rice bran on the gut microbiota and short chain fatty acids (SCFA) in normal weight (NW) and overweight/obese (OO) subjects through in vitro fecal fermentation. Methods Arabinoxylan was extracted from rice bran fiber. For in vitro fecal fermentation, each fecal sample from NW (n = 6, 3 males and 3 females) and OO (n = 7, 3 males and 4 females) was diluted into anaerobic medium with three treatments: control (no substrates), fructooligosaccharides (FOS, a well-known prebiotic), and arabinoxylan. Samples were incubated at 37˚C and aliquots were taken at 0, 4, 8, 12 and 24 h. SCFA content from samples at all timepoints was analyzed using HPLC. Samples at 0 and 24 h were used for gut microbiota analysis through 16S rRNA gene sequencing. Statistical analyses were performed for the randomized complete block design, where the weight classes are confounded with blocks (subjects). Friedman test was used to determine the difference at 5% level of significance. Results As a result, arabinoxylan treatment significantly increased total SCFA concentration in both NW and OO subjects than control (P < 0.05), comparable to FOS treatment. Between weight classes under arabinoxylan treatment, OO group showed a significantly higher total SCFA content than NW group (P < 0.05). Arabinoxylan changed gut microbial population at the genus level, stimulating Bifidobacterium, Collinsella and Blautia and decreasing Clostridium XIVa and b, Dorea and Oscillibacter (P < 0.05). In addition, different microbiome population was shown in weight classes with three treatments, showing higher Bacteroides in NW and higher Prevotella in OO. Conclusions These results showed that arabinoxylan from rice bran modified gut microbiota in both weight classes, increasing total SCFA content. This study suggests that arabinoxylan from rice bran may have a potential impact on microbial gut health in obesity with prebiotic activities. Funding Sources University of Arkansas.

scholarly journals The impact of feed efficiency selection on the ruminal, cecal, and fecal microbiomes of Angus steers from a commercial feedlot

2020 ◽  
Vol 98 (7) ◽  
Author(s):  
Christina B Welch ◽  
Jeferson M Lourenco ◽  
Dylan B Davis ◽  
Taylor R Krause ◽  
Mia N Carmichael ◽  
...  
Keyword(s):  
Feed Efficiency ◽  
Bacterial Population ◽  
Diversity Index ◽  
16S Rrna Gene Sequencing ◽  
Nutrient Utilization ◽  
Rrna Gene ◽  
Feedlot Steers ◽  
Taxonomic Profile ◽  
Bacterial Richness ◽  
The Impact

Abstract Feed is the greatest cost of animal production, so reducing it is critical to increase producer profits. In ruminants, the microbial population within the gastrointestinal tract (GIT) is critical to nutrient digestion and absorption in both the rumen and the hindgut. The objective of this study was to determine the bacterial taxonomic profile of the rumen, cecum, and feces of feedlot steers at slaughter in order to link feed efficiency and the GIT bacterial populations from these three locations. Twenty commercial Angus steers were selected and divided into two groups according to their residual feed intake (RFI) classification determined during the feedlot-finishing period: high-RFI (n = 10) and low-RFI (n = 10). After the ruminal, cecal, and fecal samples were collected at slaughter, DNA extraction and 16S rRNA gene sequencing were performed on them to determine their bacterial composition. One-way ANOVA was performed on the animal performance data, alpha diversities, and bacterial abundances using RFI classification as the fixed effect. Overall, the ruminal bacterial population was the most different in terms of taxonomic profile compared with the cecal and fecal populations as revealed by beta diversity analysis (P < 0.001). Moreover, bacterial richness (Chao1) was greatest (P = 0.01) in the rumen of the high-RFI group compared with the low-RFI group. In contrast, bacterial richness and diversity in the intestinal environment showed that Chao1 was greater (P = 0.01) in the cecum, and the Shannon diversity index was greater in both the cecum and feces of low-RFI compared with high-RFI steers (P = 0.01 and P < 0.001, respectively). Ruminococcaceae was more abundant in the low-RFI group in the cecum and feces (P = 0.01); fecal Bifidobacteriaceae was more abundant in high-RFI steers (P = 0.03). No correlations (P ≥ 0.13) between any ruminal bacterial family and RFI were detected; however, Ruminococcaceae, Mogibacteriaceae, Christensenellaceae, and BS11 were negatively correlated with RFI (P < 0.05) in the cecum and feces. Succinivibrionaceae in the cecum was positively correlated with RFI (P = 0.05), and fecal Bifidobacteriaceae was positively correlated with RFI (P = 0.03). Results collectively indicate that in addition to the ruminal bacteria, the lower gut bacterial population has a significant impact on feed efficiency and nutrient utilization in feedlot steers; therefore, the intestinal bacteria should also be considered when examining the basis of ruminant feed efficiency.

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