Isolation, identification, and characterization of resistant bacteria to antibiotics from pharmaceutical effluent and study of their antibiotic resistance.

Pharmaceutical effluents primarily enter aquatic environments through the discharge of treated and untreated wastewater from various sources, including hospitals, pharmaceutical manufacturing facilities, and households. Microbes sourced from pharmaceutical effluents such as Pseudomonas spp. pose a significant public health concern because of their high levels of resistance to multiple drugs and extreme multidrug resistance. Therefore, the present study was conducted for the isolation, identification, and molecular characterization of selected isolates from pharmaceutical effluents and also determined their antibiotic sensitivity patterns. From June 2016 to March 2017, a study was conducted on four well-known pharmaceutical companies specializing in antibiotic production in Dhaka and Gazipur. Four wastewater samples were collected from various origins and then brought to the Bacteriology laboratory for microbiological examination. Twelve pure isolates were obtained and characterized through cultural and biochemical tests while molecular identification of Pseudomonas spp. was performed using the 16S rRNA gene sequence. Twelve commercially available antibiotics were used for antibiotic sensitivity tests using Kirby-Bauer disk diffusion methods. We isolated the most predominant isolates, Pseudomonas aeruginosa (41.67%), followed by Bacillus spp. (33.33%) and Staphylococcus spp. (25%) respectively. Among 12 antibiotics, ciprofloxacin is 100% sensitive against P. aeruginosa, while the remaining 11 antibiotics are 100% resistant. Bacillus spp. showed 100% resistance to all antibiotics while 50% sensitive to vancomycin and 100% to chloramphenicol, respectively. Staphylococcus spp. was 100% resistant to all antibiotics. Our research suggested that P. aeruginosa is the reservoir of antibiotic resistance genes and spreads disease to humans from the environment. The findings of this study, i.e., the isolation, identification, and characterization of antibiotic-resistant bacteria from pharmaceutical effluent have highlighted, comprehended, and mitigated the dissemination of antibiotic resistance and opportunistic bacteria.

Antimicrobial Resistance Profile of Common Foodborne Pathogens Recovered from Livestock and Poultry in Bangladesh.

Multidrug-resistant (MDR) foodborne pathogens have created a great challenge to the supply and consumption of safe & healthy animal-source foods. The study was conducted to identify the common foodborne pathogens from animal-source foods & by-products with their antimicrobial drug susceptibility and resistance gene profile. The common foodborne pathogens Escherichia coli (E. coli), Salmonella, Streptococcus, Staphylococcus, and Campylobacter species were identified in livestock and poultry food products. The prevalence of foodborne pathogens was found higher in poultry food & by-product compared with livestock (p < 0.05). The antimicrobial drug susceptibility results revealed decreased susceptibility to penicillin, ampicillin, amoxicillin, levofloxacin, ciprofloxacin, tetracycline, neomycin, streptomycin, and sulfamethoxazole-trimethoprim whilst gentamicin was found comparatively more sensitive. Regardless of sources, the overall MDR pattern of E. coli, Salmonella, Staphylococcus, and Streptococcus were found to be 88.33%, 75%, 95%, and 100%, respectively. The genotypic resistance showed a prevalence of blaTEM, blaSHV, blaCMY, tetA, tetB, sul1, aadA1, aac(3)-IV, and ereA resistance genes. The phenotype and genotype resistance patterns of isolated pathogens from livestock and poultry had harmony and good concordance, and sul1 & tetA resistance genes had a higher prevalence. Good agricultural practices along with proper biosecurity may reduce the rampant use of antimicrobial drugs. In addition, proper handling, processing, storage, and transportation of foods may decline the spread of MDR foodborne pathogens in the food chain.

Spatially explicit database on crop-livestock management, soil, climate, greenhouse gas emissions and mitigation potential for all of Bangladesh.

This data article provides spatially explicit data on greenhouse gas (GHG) emissions and mitigation potential at various administrative levels for the whole of Bangladesh. The results arising from analysis of this database are presented in research article "Quantifying opportunities for greenhouse gas emissions mitigation using big data from smallholder crop and livestock farmers across Bangladesh" [1]. We collected crop and livestock management data and associated soil and climatic data from variety of primary and secondary sources outlined below in our methodology. The datafiles on crops and livestock contain model outputs for three greenhouse gases (CO2, CH4 and N2O) and their global warming potential, which are linked, to the information on crop/livestock management, soil and climatic conditions presented in the supplementary data of the associated manuscript. The datafiles on mitigation potential contain district-level annual GHG mitigation potential by 2030 and 2050 segregated by different crops/livestock types and mitigation options. This dataset is useful for Bangladesh's GHG accounting from the agricultural sector, and can be used to update its nationally determined contributions. Administrative level emissions and mitigation potential estimates segregated by crop-livestock types and mitigation options are useful to prioritize agricultural research and development interventions consistent with food security and environmental goals and to organize agricultural extension and support services to better inform farmers on food production and move towards GHG mitigation goals.

Quantifying opportunities for greenhouse gas emissions mitigation using big data from smallholder crop and livestock farmers across Bangladesh.

Climate change is and will continue to have significant implications for agricultural systems. While adaptation to climate change should be the priority for smallholder production systems, adoption of cost-effective mitigation options in agriculture not only contributes to food security but also reduces the extent of climate change and future adaptation needs. Utilizing management data from 16,413 and 12,548 crop and livestock farmers and associated soil and climatic data, we estimated GHG emissions generated from crop and livestock production using crop and livestock models, respectively. Mitigation measures in crop and livestock production, their mitigation potential and cost/benefit of adoption were then obtained from literature review, stakeholder consultations and expert opinion. We applied the identified mitigation measures to a realistic scale of adoption scenario in the short- (2030) and long-term (2050). Our results were then validated through stakeholders consultations. Here, we present identified mitigation options, their mitigation potentials and cost or benefit of adoption in the form of Marginal Abatement Cost Curves (MACC). Based on our analysis, total GHG emissions from agricultural sector in Bangladesh for the year 2014-15 is 76.79 million tonne (Mt) carbon-dioxide equivalent (CO2e). Business-as-usual GHG emissions from the agricultural sector in Bangladesh are approximately 86.87 and 100.44 Mt CO2e year-1 by 2030 and 2050, respectively. Adoption of climate-smart crop and livestock management options to reduce emissions considering a realistic adoption scenario would offer GHG mitigation opportunities of 9.51 and 14.21 Mt CO2e year-1 by 2030 and 2050, respectively. Of this mitigation potential, 70-75% can be achieved through cost-saving options that could benefit smallholder farmers. Realization of this potential mitigation benefit, however, largely depends on the degree to which supportive policies and measures can encourage farmers' adoption of the identified climate smart agricultural techniques. Therefore, government should focus on facilitating uptake of these options through appropriate policy interventions, incentive mechanisms and strengthening agricultural extension programs.

Isolation of multidrug-resistant Escherichia coli from turkeys in Dinajpur, Bangladesh, and their antibiogram profile.

OBJECTIVE: The study was carried out for molecular characterization and antibiotic resistance analysis of Escherichia coli isolated from different turkey farms in Dinajpur, Bangladesh. MATERIALS AND METHODS: A total of 45 samples comprising feces (n = 23) and cloacal swabs (n = 22) were collected randomly from turkeys. The samples were subjected to isolation and identification of E. coli by cultural and biochemical characteristics, followed by polymerase chain reaction and sequencing. An antibiogram of the isolated E. coli isolates was carried out by following the Kirby-Bauer disk diffusion method. RESULTS: Out of the 45 samples, 28 (62.21%) were positive for E. coli, of which 16 (35.55%) fecal samples were positive and 12 (26.66%) cloacal swabs were positive. The antibiotic sensitivity analysis revealed that all the E. coli isolates were 100% sensitive to levofloxacin, norfloxacin, neomycin, gentamicin, and nitrofurantoin. On the other hand, all the isolates were 100% resistant to amoxicillin, azithromycin, erythromycin, tetracycline, bacitracin, cephalexin, nalidixic acid, vancomycin, methicilin, piperacillin, pefloxacin, novobiocin, cefepime, trimethoprim, netilmicin, and aztreonam. CONCLUSION: This study's results uncover the occurrence and antibiotic resistance pattern of E. coli in the study area's turkeys.

Molecular Detection of Multidrug Resistant Staphylococcus aureus Isolated from Bovine Mastitis Milk in Bangladesh.

The current study was conducted to isolate and identify multidrug-resistant Staphylococcus aureus (MDR-SA) from mastitis milk samples and to determine their antimicrobial susceptibility pattern. A total of 48 bovine mastitis (BM) milk samples were collected from different parts of the Rangpur division, Bangladesh. After the collection of milk samples, mastitis was confirmed using the California mastitis test. Isolation and identification of Staphylococcus aureus were performed using conventional cultural and biochemical tests as well as using molecular methods of PCR. Nucleotide sequence analysis of the 23S rRNA gene of Staphylococcus aureus was determined. The antibiogram of the isolated bacteria was conducted using the disc diffusion method. Phylogenetic analysis of 23S rRNA was done using MEGA 7, ClustalW multiple sequence alignment, and NCBI-BLAST tools, where the sequence of the isolate showed 98% to 99% identity. Antibiogram test using 15 antimicrobial agents showed that all of the Staphylococcus aureus isolates were classified as multidrug-resistant (MDR). It was found that the isolates were resistant to tetracycline, novobiocin, methicillin, vancomycin, and cephradine, and the isolates were sensitive to ciprofloxacin, azithromycin, norfloxacin, levofloxacin, gentamicin, and amoxicillin. The detection of MDR-SA in mastitis milk is alarming and represents a great public health concern. The findings of the present study help identify Staphylococcus aureus at the molecular level using 23S rRNA gene sequencing and will help select the appropriate and effective antimicrobial agent to control BM in the northern part of Bangladesh.

Isolation of multi-drug resistant Klebsiella sp. from bovine mastitis samples in Rangpur, Bangladesh.

OBJECTIVE: The objective of this study was to identify the multi-drug resistance (MDR) Klebsiella sp. from mastitis milk samples. MATERIALS AND METHODS: In the current research, 48 clinical mastitis milk samples were collected from Rangpur division, Bangladesh. Confirmation of bovine mastitis (BM) was done by the California Mastitis Test (CMT). All the CMT positive isolates were subjected for the identification of Klebsiella sp. using through a series of cultural and biochemical tests. MDR Klebsiella sp. isolates were determined using the disk diffusion method, and minimum inhibitory zones were measured by following Clinical and Laboratory Standards Institute. MDR patterns of the isolates were also subjected to study by using housefly (Musca domestica). RESULTS: Among the isolates, 62.5% (n = 30/48) revealed the presence of Klebsiella sp. Eight antimicrobial agents including Amoxicillin, Novobiocin, Erythromycin, Vancomycin, Cephradine, Tetracycline, Bacitracin, Methicillin, and housefly (M. domestica) showed complete resistance to Klebsiella sp. On the other hand, Chloramphenicol, Gentamicin, Ciprofloxacin, Azithromycin, Norfloxacin, Levofloxacin, and Nalidixic acid showed sensitivity. CONCLUSION: This study helps to treat BM with effective antibiotics and helps in an epidemiological study in Rangpur division as well as helps to create public health awareness.

Study of a common azo food dye in mice model: Toxicity reports and its relation to carcinogenicity.

This study was conducted to evaluate the toxic effects of an azo dye carmoisine widely used in foods and to investigate its relation to carcinogenicity. Carmoisine administered into mice orally in four different doses as control, low, medium, and high equivalent to 0, 4, 200, and 400 mg/kg bw, respectively, for 120 days. The key toxicological endpoint was observed including animal body weight, organ weights, hematology, biochemistry, and molecular biology assessment. The body weights of medium- and high-dose carmoisine-treated mice group were significantly decreased as compared to the control mice group. Platelet, white blood cell and monocyte counts of treated group were considerably higher, while Hb and red blood cell counts were drastically lower than the control group. The biochemical parameters such as serum alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, total protein, globulin, urea, and creatinine level were significantly increased, while serum cholesterol level was decreased after treatment as compared to the control. RT-PCR results showed that expression of Bcl-x and PARP gene was intensively increased, whereas expression of p53 gene was decreased in the mouse liver tissues treated with carmoisine. This study revealed that high-dose (400 mg/kg bw) treatment of carmoisine was attributable to renal failure and hepatotoxicity. It also would be suspected as a culprit for liver oncogenesis.

Selective isolation and noninvasive analysis of circulating cancer stem cells through Raman imaging.

Circulating cancer stem cells (CCSCs), a rare circulating tumor cell (CTC) type, recently arose as a useful resource for monitoring and characterizing both cancers and their metastatic derivatives. However, due to the scarcity of CCSCs among hematologic cells in the blood and the complexity of the phenotype confirmation process, CCSC research can be extremely challenging. Hence, we report a nanoparticle-mediated Raman imaging method for CCSC characterization which profiles CCSCs based on their surface marker expression phenotypes. We have developed an integrated combinatorial Raman-Active Nanoprobe (RAN) system combined with a microfluidic chip to successfully process complete blood samples. CCSCs and CTCs were detected (90% efficiency) and classified in accordance with their respective surface marker expression via completely distinct Raman signals of RANs. Selectively isolated CCSCs (93% accuracy) were employed for both in vitro and in vivo tumor phenotyping to identify the tumorigenicity of the CCSCs. We utilized our new method to predict metastasis by screening blood samples from xenograft models, showing that upon CCSC detection, all subjects exhibited liver metastasis. Having highly efficient detection and noninvasive isolation capabilities, we have demonstrated that our RAN-based Raman imaging method will be valuable for predicting cancer metastasis and relapse via CCSC detection. Moreover, the exclusion of peak overlapping in CCSC analysis with our Raman imaging method will allow to expand the RAN families for various cancer types, therefore, increasing therapeutic efficacy by providing detailed molecular features of tumor subtypes.

Gold Nanosphere-Deposited Substrate for Distinguishing of Breast Cancer Subtypes Using Surface-Enhanced Raman Spectroscopy.

Raman spectroscopy, as a nondestructive spectral technique, served as an efficient tool for investigating the molecular information of complex biological systems including cells. But the limitation of the technique is its low signal intensity. This inherent problem can be overcomed by using surface-enhanced Raman scattering (SERS) technique. SERS can be achieved by roughening the surface of a substrate with noble metal nanoparticles. But preparation of homogenous SERS substrate with higher enhancement property is a big challenge. In this study, we report a homogenous gold (Au) nanosphere deposited ITO substrate that can significantly increase the Raman signals from analytes. By using this substrate we successfully characterize and distinguish two different sub-types of breast cancer cells. SERS method is simple, label free and non-toxic. Our newly developed Au nanosphere deposited substrate can be used as an effective platform for molecular detection, characterization, and distinguishing different cells originated from same or different organs.

Controlling differentiation of adipose-derived stem cells using combinatorial graphene hybrid-pattern arrays.

Control of stem cell fate by modulating biophysical cues (e.g., micropatterns, nanopatterns, elasticity and porosity of the substrates) has emerged as an attractive approach in stem cell-based research. Here, we report a method for fabricating combinatorial patterns of graphene oxide (GO) to effectively control the differentiation of human adipose-derived mesenchymal stem cells (hADMSCs). In particular, GO line patterns were highly effective for modulating the morphology of hADMSCs, resulting in enhanced differentiation of hADMSCs into osteoblasts. Moreover, by generating GO grid patterns, we demonstrate the highly efficient conversion of mesodermal stem cells to ectodermal neuronal cells (conversion efficiency = 30%), due to the ability of the grid patterns to mimic interconnected/elongated neuronal networks. This work provides an early demonstration of developing combinatorial graphene hybrid-pattern arrays for the control of stem cell differentiation, which can potentially lead to more effective stem cell-based treatment of incurable diseases/disorders.

In situ monitoring of doxorubicin release from biohybrid nanoparticles modified with antibody and cell-penetrating peptides in breast cancer cells using surface-enhanced Raman spectroscopy.

In situ monitoring of drug release in cancer cells is very important for real-time assessment of drug release dynamics in chemotherapy. In this study, we report label-free in situ monitoring and control of intracellular anti-cancer drug delivery process using biohybrid nanoparticles based on surface-enhanced Raman spectroscopy (SERS) for the first time. Each biohybrid nanoparticle consisted of gold nanoparticle, cell-penetrating peptide (Tat peptide), and cancer-targeting antibody to increase the efficacy of the anti-cancer drug delivery with specific targeting and increased uptake rate. The doxorubicin (Dox)-loaded biohybrid nanoparticles were showed specific SERS spectra of Dox, specifically immobilized on the target cell membrane and quickly penetrated into the cells when treated on the mixed cell culture condition. The intracellular release of Dox from the biohybrid nanoparticle was continuously monitored with time-dependent change of intracellular SERS signals of Dox. The releasing rate of Dox was successfully controlled with the addition of glutathione on the cells. The anti-cancer effect of intracellular released Dox was confirmed with cell viability assay. With the proposed monitoring system, specific cancer cell targeting and improved uptake of the anti-cancer drug were detected and time-dependent intracellular release of the anti-cancer drug was monitored successfully. The proposed novel in situ monitoring system can be used as a spectroscopic analysis tool for label-free monitoring of the time-dependent release of various kinds of anti-cancer drugs inside cells.