ABSTRACT This study compared colony counts of mixed bacterial cultures on chromogenic spread plates using manual and Color QCount (Spiral Biotech, Inc., Norwood, MA) automated methods. Inoculum levels spanned 30–300 cfu/mL, 26 agar types were used and 581 plates were analyzed. Plates were prepared according to manufacturers' instructions, manually counted once by two scientists and counted in duplicate automatically. The correlation coefficient comparing automated and manual counts for the pooled population of data was 0.987. The slope and intercept for the linear regression line were 1.0067 and 0.031, respectively. The mean log value difference between automated and manual counts for pooled data was−0.042. The mean log value differences between manual and automated counts demonstrated that 83.8% of plates analyzed were within 0.1 log, and 98.2% were within 0.2 log. These results demonstrate that the Color QCount automatic counter is a suitable alternative to the standard method of manually counting colored colonies on chromogenic agar plates.PRACTICAL APPLICATIONSA variety of microbiology applications require users to count bacterial colonies on agar plates. Colonies are counted to 1) assess levels of contamination in the environment, water, food and dairy products; 2) conduct preservative and efficacy studies; and 3) determine the quality of pharmaceutical and medical products with microbial limits testing. There are several sources of variability in plating including inoculating errors, sampling errors, incubation errors, and counting errors. Errors in counting may worsen with user fatigue.Using an automated colony counter to complete the tedious job of manually counting bacterial colonies on agar plates will not only improve efficiency in microbiology laboratories by saving valuable time for alternative tasks but also may improve the accuracy and consistency of the counts.
ABSTRACT In this study, we demonstrated the simultaneous detection of Escherichia coli and Salmonella enteritidis, by coupling immunomagnetic separation (IMS) with quantum dots (QDs) labeling. QDs having different emission wavelengths were conjugated with anti‐ E. coli and anti‐ Salmonella antibodies. QD–antibody conjugates were used to label immunomagnetically separated bacteria and the fluorescence intensities were measured for enumerations of both species. The concentrations of primary antibodies used in IMS, the ratio of QDs to antibodies during the conjugation and the concentration of QD–antibody conjugates used in labeling were optimized to enhance the sensitivity of the assay. After labeling bacteria with QDs, the quenching observed between bead–bacteria complex and QDs was eliminated by separating QDs from the complex using sodium dodecyl sulfate solution. The fluorescence intensities due to the capturing of different concentrations of bacteria were measured and the working ranges were found to be 5 × 10 2 to 5 × 10 5 cfu/mL for E. coli and 4 × 10 2 to 4 × 10 5 cfu/mL for S. enteritidis . PRACTICAL APPLICATIONS In this study, antibody‐conjugated multicolor quantum dots (QDs) were used for simultaneous detection of Escherichia coli and Salmonella enteritidis . The results of this study indicate that QD labels can be used in multiplex, rapid and selective detection of bacteria with detection limits comparable with those of many novel methods in cases where the assay conditions are optimized. Furthermore, the assay can be modified for the simultaneous detection of more than two species through using QD labels having different emission wavelengths.
ABSTRACT Despite advances in the specificity and sensitivity of molecular biological technologies, the efficient recovery of DNA from low‐biomass samples remains extremely challenging. Optimal methods to purify biomolecules from such environments should (1) achieve the greatest total yield and (2) reflect the true microbial diversity of the sample. These attributes were assessed from five DNA purification regimes: a standard‐manual procedure, MoBio Ultraclean and Promega Wizard kits, and an automated Axcyte AutoLyser method with and without bead‐beating agitation. A homogenous mixture of known concentrations of nine distinct bacterial lineages isolated from low‐biomass environments was prepared and suitable aliquots of subsamples were processed in parallel. DNA products from each of these methods were then subjected to polymerase chain reaction (PCR), quantitative PCR and 16S rRNA clone‐library analysis. The Axcyte AutoLyser outperformed all other purification regimes examined. This automated method consistently both yielded the highest concentration of PCR‐amplifiable DNA, and reported species composition most consistent with the starting solution. PRACTICAL APPLICATIONS This communication carefully examines the effectiveness of common DNA purification regimes as well as an automated method. Comparative analyses convincingly demonstrate that the different methods not only result in different recovery of genomic DNA, but more importantly, different estimations of microbial diversity in the sample. This report will hopefully inspire investigators from various industries (pharmaceutical, ecological, medical, semiconductor, etc.) who find themselves in the initial phases of large‐scale studies to devote a significant effort into optimizing sample extraction protocols to achieve the most accurate information.
ABSTRACT The aim of the present research was to isolate and identify cellulolytic bacteria from the gut of the local termite Coptotermes curvignathus (Holmgren) present in the vicinity of the University of Putra Malaysia. The isolates were cultured in a medium containing carboxymethyl‐cellulose and cellobiose. The bacterial species were tentatively identified by using the Biolog reader as well as the Bergey's manual and later confirmed by 16S rRNA sequence homology. The species were all novel strains and identified as Bacillus cereus strain Razmin A, Enterobacter aerogenes strain Razmin B, Enterobacter cloacae strain Razmin C, Chryseobacterium kwangyangense strain Cb and Acinetobacter strain Raminalimon. Biolog reader was not able to identify one of the bacterial species in which it was identified as C. kwangyangense strain Cb by 16S rRNA sequence homology. The GenBank NCBI/EMBL accession numbers for the bacterial strains are EU294508, EU305608, EU305609, EU169201 and EU332791 for B. cereus Razmin A, E. aerogenes strain Razmin B, E. cloacae strain Razmin C, C. kwangyangense strain Cb and Acinetobacter strain Raminalimon, respectively.PRACTICAL APPLICATIONSThe experiment describes the isolation and identification of cellulolytic bacteria from termites, using Biolog reader and polymerase chain reaction technique. Termites are common insects in tropical regions and thrive on wood and cellulolytic materials. Hence, the bacteria isolated may be useful in the degradation of cellulosic materials to increase their digestibility and possibly production of metabolites and enzymes.
ABSTRACT Aceticlastic and hydrogenotrophic methanogens were comparatively investigated by 16S rRNA‐based fluorescence in situ hybridization (FISH) technique combined with Confocal Scanning Laser Microscopy (CSLM) to evaluate temperature influence on two functional groups of methanogens. Microorganisms were grown in the form of anaerobic granular sludge in two lab‐scale Upflow Anaerobic Sludge Bed (UASB) reactors fed with synthetic wastewater and operated at psychrophilic and mesophilic temperature conditions. Since hydrogenotrophic and aceticlastic methanogenesis are known to play a crucial role, digestion may be effectively blocked if these processes are ceased due to unfavorable environmental temperature conditions. Mesophilic (35 ± 2C) and psychrophilic (10 ± 1C) reactors were inoculated by the same mesophilic granules taken from a full‐scale UASB reactor. According to FISH results, Archaea representing methanogens were found dominating at bottom sampling ports of reactors and dominant member of Archaea was the genus aceticlastic Methanosaeta (MX825). Other aceticlastic methanogen such as Methanosarcina‐like (SARCI645) species were also identified which were higher in psychrophilic granules. Members of order Methanobacteriales (MB310) constituted the major hydrogenothrophic methanogens in both reactors, whereas other hydrogenothrophic methanogens members of order Methanococcales (MC1109) and Methanogenium (MG1200) relatives were absent. Abundance of originally mesophilic Methanosaeta‐related Archaea under low temperature conditions demonstrated the adaptive capacity of microorganisms to psychrophilic conditions. This might be attributed to enzymatic alterations in Methanosaeta cells originating from seed sludge, which were exposed to sub‐mesophilic temperatures at start‐up and then to psychrophilic conditions during gradual temperature decreases. Both sludge granules remained undisturbed and kept their rigidity even after exposure to very low temperatures. Quantification study was done using Image Pro‐plus Version 4.0. Archaeal cells detected with probe ARC915 were found around 60% of the 4,6‐diamidino‐2‐phenylindole stained cells at both reactors. Methanosaeta spp./Archaea ratios for mesophilic and psychrophilic UASB reactors were calculated as 71% and 84%, respectively. FISH and CSLM results together with quantification study showed that the microbial community of anaerobic granular sludges was dominated by Methanosaeta spp. which was identified as the major methanogenic Archaea.PRACTICAL APPLICATIONSSince effects on bioreactor performances were correlated to variations in microbial diversity, investigation of methanogenic diversity in anaerobic reactors is important during operation. Identification of microorganisms should be done for formation, stability, and physiological properties of the biomass in bioreactors, which is a key factor during process performance evaluation. Monitoring the changes in dominant archea of seed added at start‐up, gives information on system performance. A detailed investigation on diversity, structure and function of mixed microbial communities in anaerobic reactors is necessary to improve treatment efficiency and stability against inhibitory compounds. Among 16S rRNA based microbial identification techniques, FISH is a well‐known technique that helps determination of dominant species by giving a detailed analysis of microbial populations while CSLM is the most appropriate method for monitoring the formation of 3‐D structure of microbial biomass. In this study, temperature influence on aceticlastic and hydrogenotrophic methanogen groups was evaluated using FISH coupled with CSLM.
