Microbial community composition controls carbon flux across litter types in early phase of litter decomposition.

Leaf litter decomposition is a major carbon input to soil, making it a target for increasing soil carbon storage through microbiome engineering. We expand upon previous findings to show with multiple leaf litter types that microbial composition can drive variation in carbon flow from litter decomposition and specific microbial community features are associated with synonymous patterns of carbon flow among litter types. Although plant litter type selects for different decomposer communities, within a litter type, microbial composition drives variation in the quantity of dissolved organic carbon (DOC) measured at the end of the decomposition period. Bacterial richness was negatively correlated with DOC quantity, supporting our hypothesis that across multiple litter types there are common microbial traits linked to carbon flow patterns. Variation in DOC abundance (i.e. high versus low DOC) driven by microbial composition is tentatively due to differences in bacterial metabolism of labile compounds, rather than catabolism of non-labile substrates such as lignin. The temporal asynchrony of metabolic processes across litter types may be a substantial impediment to discovering more microbial features common to synonymous patterns of carbon flow among litters. Overall, our findings support the concept that carbon flow may be programmed by manipulating microbial community composition.

Tracking Replicate Divergence in Microbial Community Composition and Function in Experimental Microcosms.

The study of microbial community functions necessitates replicating microbial communities. Variation in community development over time renders this an imperfect process. Thus, anticipating the likely degree of variation among replicate communities may aid in experimental design. We examined divergence in replicate community composition and function among 128 naturally assembled starting communities obtained from soils, each replicated three times, following a 30-day microcosm incubation period. Bacterial and fungal communities diverged in both composition and function among replicates, but remained much more similar to each other than to communities from different starting inocula. Variation in bacterial community composition among replicates was, however, correlated with variation in dissolved organic carbon production. A smaller-scale experiment testing nine starting communities showed that divergence was similar whether replicates were incubated on sterile or non-sterile pine litter, suggesting the impact of a pre-existing community on replicate divergence is minor. However, replicates in this experiment which were incubated for 114 days diverged more than those incubated for 30 days, suggesting experiments that run over long time periods will likely see greater variation among replicate community composition. These results suggest that while replicates diverge at a community level, such divergence is unlikely to severely impede the study of community function.

Reduction of diffusion broadening in flow by analysis of time-gated single-molecule data.

We describe the application of Extreme Value Statistics to the analysis of discrete species that possess distinguishable properties (fluorescence wavelength, fluorescence intensity, light scattering, etc.) as they cross a well-defined observation/probe region. Time-gated selection and extreme value data analysis result in increased resolution in analytical determinations. When only the data corresponding to the smallest crossing times are selected for analysis, the width of the diffusion band decreases for the measured parameter. The molecules with the smallest crossing times diffuse preferentially along the flow direction. A Monte Carlo technique and the probability density function (pdf) for a freely diffusing species are used to generate data streams to provide a theoretical basis for the aforementioned phenomenon. These calculations are included to characterize the effect of the average flow rate and the diffusion constant. We have also included a procedure for extracting the normal diffusion constant (D) from the Extreme Value Distribution. In contrast to standard flow analysis, which requires long path lengths, our approach is particularly suited for measurements in picolitre and nanolitre volumes and provides another dimension to single-molecule measurements in cellular size volumes. We believe that this is a general phenomenon that depends upon the details of the pdf, which can be complex.

Soil Bacterial and Fungal Richness Forecast Patterns of Early Pine Litter Decomposition.

Discovering widespread microbial processes that drive unexpected variation in carbon cycling may improve modeling and management of soil carbon (Prescott, 2010; Wieder et al., 2015a, 2018). A first step is to identify community features linked to carbon cycle variation. We addressed this challenge using an epidemiological approach with 206 soil communities decomposing Ponderosa pine litter in 618 microcosms. Carbon flow from litter decomposition was measured over a 6-week incubation. Cumulative CO2 from microbial respiration varied two-fold among microcosms and dissolved organic carbon (DOC) from litter decomposition varied five-fold, demonstrating large functional variation despite constant environmental conditions where strong selection is expected. To investigate microbial features driving DOC concentration, two microbial community cohorts were delineated as "high" and "low" DOC. For each cohort, communities from the original soils and from the final microcosm communities after the 6-week incubation with litter were taxonomically profiled. A logistic model including total biomass, fungal richness, and bacterial richness measured in the original soils or in the final microcosm communities predicted the DOC cohort with 72 (P < 0.05) and 80 (P < 0.001) percent accuracy, respectively. The strongest predictors of the DOC cohort were biomass and either fungal richness (in the original soils) or bacterial richness (in the final microcosm communities). Successful forecasting of functional patterns after lengthy community succession in a new environment reveals strong historical contingencies. Forecasting future community function is a key advance beyond correlation of functional variance with end-state community features. The importance of taxon richness-the same feature linked to carbon fate in gut microbiome studies-underscores the need for increased understanding of biotic mechanisms that can shape richness in microbial communities independent of physicochemical conditions.

Evaluation of different nucleic acid stains for sensitive double-stranded DNA analysis with capillary electrophoretic separation.

This paper outlines the first use of SYTOX Orange, SYTO 82 and SYTO 25 nucleic acid stains for on-column staining of double-stranded DNA (dsDNA) fragments separated by capillary electrophoresis (CE). Low-viscosity, replaceable poly(vinylpyrrolidone) (PVP) polymer solution was used as the sieving matrix on an uncoated fused-silica capillary. The effects of PVP concentration, electric field strength, and incorporated nucleic acid stain concentrations on separation efficiency were examined for a wide range of DNA fragment sizes. Our study was focused on using nucleic acid stains efficiently excitable at a wavelength of 532 nm. Among the five tested nucleic acid stains, SYTOX Orange stain was shown to have the best sensitivity for dsDNA detection by CE. About a 500-fold lower detection limit was obtained compared to commonly used ethidium bromide and propidium iodide. SYTOX Orange stain also provided a wide linear dynamic range for direct DNA quantitation with on-line CE detection. Use of SYTOX Orange stain can greatly improve the measurement of DNA fragments by CE, which will enable an expanded set of applications in genomics and diagnostics.

Differentiation of Bacillus anthracis, B. cereus, and B. thuringiensis by using pulsed-field gel electrophoresis.

A pulsed-field gel electrophoresis (PFGE) method was developed for discriminating Bacillus anthracis from B. cereus and B. thuringiensis. A worldwide collection of 25 B. anthracis isolates showed high-profile homology, and these isolates were unambiguously distinguished from B. cereus and B. thuringiensis isolates by cluster analysis of the whole-genome macrorestriction enzyme digestion patterns generated by NotI.

Fingerprinting of single viral genomes.

We demonstrate the use of technology developed for optical mapping to acquire DNA fingerprints from single genomes for the purpose of discrimination and identification of bacteria and viruses. Single genome fingerprinting (SGF) provides not only the size but also the order of the restriction fragments, which adds another dimension to the information that can be used for discrimination. Analysis of single organisms may eliminate the need to culture cells and thereby significantly reduce analysis time. In addition, samples containing mixtures of several organisms can be analyzed. For analysis, cells are embedded in an agarose matrix, lysed, and processed to yield intact DNA. The DNA is then deposited on a derivatized glass substrate. The elongated genome is digested with a restriction enzyme and stained with the intercalating dye YOYO-1. DNA is then quantitatively imaged with a fluorescence microscope and the fragments are sized to an accuracy >or=90% by their fluorescence intensity and contour length. Single genome fingerprints were obtained from pure samples of adenovirus, from bacteriophages lambda and T4 GT7, and from a mixture of the three viral genomes. SGF will enable the fingerprinting of uncultured and unamplified samples and allow rapid identification of microorganisms with applications in forensics, medicine, public health, and environmental microbiology.

Probing the kinetics of SYTOX Orange stain binding to double-stranded DNA with implications for DNA analysis.

Rapid binding kinetics of SYTOX Orange stain with double-stranded DNA (dsDNA) was revealed on the DNA fragment sizing flow cytometer. We demonstrated for the first time that the dye molecules could be adsorbed onto the capillary surface and native DNA fragments can be dynamically stained while passing through the capillary. High-quality burst size distribution histograms were obtained for DNA samples analyzed immediately after staining, dilution, or mixing. These observations indicated that rapid interactions exist between SYTOX Orange dye molecules and dsDNA. A stopped-flow fluorescence apparatus was set up to capture the fast association traces of intercalating dyes binding to dsDNA. Kinetic equations were derived to fit the association curves for determination of association rates and to model the dynamic staining, dilution, and mixing processes of DNA samples stained with intercalating dyes. The measured association rates for both SYTOX Orange and PicoGreen stains intercalating into dsDNA were on the order of 10(8) M-1 s-1, suggesting a diffusion-controlled process. Simulations indicate that reequilibration can be reached in seconds upon staining, dilution, or mixing. Insight into the kinetics of DNA binding dyes will help implement efficient sample-handling practices in DNA analysis, including DNA fragment sizing flow cytometry.

Statistics of single-molecule measurements: applications in flow-cytometry sizing of DNA fragments.

BACKGROUND: The measurement of physical properties from single molecules has been demonstrated. However, the majority of single-molecule studies report values based on relatively large data sets (e.g., N > 50). While there are studies that report physical quantities based on small sample sets, there has not been a detailed statistical analysis relating sample size to the reliability of derived parameters. METHODS: Monte Carlo simulations and multinomial analysis, dependent on quantifiable experimental parameters, were used to determine the minimum number of single-molecule measurements required to produce an accurate estimate of a population mean. Simulation results were applied to the fluorescence-based sizing of DNA fragments by ultrasensitive flow cytometry (FCM). RESULTS: Our simulations show, for an analytical technique with a 10% CV, that the average of as few as five single-molecule measurements would provide a mean value within one SD of the population mean. Additional simulations determined the number of measurements required to obtain the desired number of replicates for each subpopulation within a mixture. Application of these results to flow cytometry data for lambda/HindIII and S. aureus Mu50/SmaI DNA digests produced accurate DNA fingerprints from as few as 98 single-molecule measurements. CONCLUSIONS: A surprisingly small number of single-molecule measurements are required to obtain a mean measurement descriptive of a normally-distributed parent population.

Performance assessment of DNA fragment sizing by high-sensitivity flow cytometry and pulsed-field gel electrophoresis.

The sizing of restriction fragments is the chief analytical technique utilized in the production of DNA fingerprints. Few techniques have been able to compete with pulsed-field gel electrophoresis (PFGE), which is capable of discriminating among bacteria at species and strain levels by resolving restriction fragments. However, an ultrasensitive flow cytometer (FCM) developed in our lab has also demonstrated the ability to discriminate bacteria at species and strain levels. The abilities of FCM warrant a quantitative parallel comparison with PFGE to assess and evaluate the accuracy and precision of DNA fragment sizing by both techniques. Replicate samples of Staphylococcus aureus Mu50 were analyzed along with two clinical S. aureus isolates. The absolute fragment sizing accuracy was determined for PFGE (5% +/- 2%) and FCM (4% +/- 4%), with sequence-predicted Mu50 SmaI fragment sizes used as a reference. Precision was determined by simple arithmetic methods (relative standard deviation for PFGE [RSD(PFGE) ] = 3% +/- 2% and RSD(FCM) = 1.2% +/- 0.8%) as well as by the use of dendrograms derived from Dice coefficient-unweighted pair group method with arithmetic averages (UPGMA) and Pearson-UPGMA analyses. All quantitative measures of PFGE and FCM precision were equivalent, within error. The precision of both methods was not limited by any single sample preparation or analysis step that was tracked in this study. Additionally, we determined that the curve-based clustering of fingerprint data provided a more informative and useful assessment than did traditional band-based methods.