The Population Biology of Bacterial Plasmids: A PRIORI Conditions for the Existence of Mobilizable Nonconjugative Factors

A mathematical model for the population dynamics of nonconjugative plasmids that can be mobilized by conjugative factors is presented. In the analysis of the properties of this model, primary consideration is given to the conditions under which these nonself-transmissible extrachromosomal elements could become established and would be maintained in bacterial populations. The results of this analysis demonstrate the existence of conditions where, as a consequence of infectious transmission via mobilization, nonconjugative plasmids could become established and be maintained even when the bacteria carrying them have lower reproductive fitnesses than plasmid-free members of the population. However, these existence conditions are stringent and suggest therefore, that it is highly unlikely that plasmids of this type would become established and maintained without some direct selection favoring their carriage. The general implications of these results and limitations of the model are discussed. Brief consideration is also given to the implications of these theoretical findings to the problems of the spread of multiple antibiotic resistance plasmids (R-factors) and the risk of contaminating natural populations of bacteria with chimeric plasmids produced by work with recombinant DNA.     

Influence of Nutrient Availability on the Interaction Between Spotted Knapweed and Bluebunch Wheatgrass

Centaurea maculosa (Lam.) (spotted knapweed) reduces wildlife and livestock habitat biodiversity and increases erosion. Nutrient availability to plants may be used to accelerate succession away from spotted knapweed. Early‐successional plant communities often have high nutrient availability, whereas late‐successional communities are often found on lower nutrient soils. We hypothesized that removal of nutrients would change the competitive advantage from spotted knapweed to Pseudoroegneria spicatum (bluebunch wheatgrass) (late seral). In two addition series matrices, background densities of Secale cereale (annual rye) and Elymus elimoides (bottlebrush squirreltail) (3,000 seeds/m²) were used to remove nutrients from the soil. In another set of addition series matrices, nitrogen (33 kg/ha) or phosphorus (33 kg/ha) were added to the soil. Nutrient analysis of soil and vegetation indicated that annual rye and bottlebrush squirreltail reduced nutrient availability in soils. In another matrix, neither a background density nor nutrients were added. Data were fit into Watkinson's curvilinear model to determine the competitive relationship between bluebunch wheatgrass and spotted knapweed. This allowed comparison of the equivalence ratios (C) generated from each addition series. The C parameters are the per‐plant equivalent of bluebunch wheatgrass or spotted knapweed and can be interpreted as the ratio of intra‐to‐interspecific competition. The C parameters are also the equivalence ratio of the number of spotted knapweed it takes to have equivalent effect on bluebunch wheatgrass or the number of bluebunch wheatgrass having the equivalent effect on spotted knapweed. Without nutrient manipulation, spotted knapweed was more competitive than bluebunch wheatgrass. The C for bluebunch wheatgrass was 0.17, indicating that 0.17 knapweed plants were competitively equivalent to one wheatgrass. Annual rye changed the competitive balance in favor of bluebunch wheatgrass (C = 9.9). Addition of nitrogen, phosphorus, or the mid‐seral species did not change the competitive relationship between the two species. This preliminary study suggests that succession from spotted knapweed to late‐seral bluebunch wheatgrass community may be accelerated by altering resource availability.     

Reconstructing Mammalian Sleep Dynamics with Data Assimilation

Data assimilation is a valuable tool in the study of any complex system, where measurements are incomplete, uncertain, or both. It enables the user to take advantage of all available information including experimental measurements and short-term model forecasts of a system. Although data assimilation has been used to study other biological systems, the study of the sleep-wake regulatory network has yet to benefit from this toolset. We present a data assimilation framework based on the unscented Kalman filter (UKF) for combining sparse measurements together with a relatively high-dimensional nonlinear computational model to estimate the state of a model of the sleep-wake regulatory system. We demonstrate with simulation studies that a few noisy variables can be used to accurately reconstruct the remaining hidden variables. We introduce a metric for ranking relative partial observability of computational models, within the UKF framework, that allows us to choose the optimal variables for measurement and also provides a methodology for optimizing framework parameters such as UKF covariance inflation. In addition, we demonstrate a parameter estimation method that allows us to track non-stationary model parameters and accommodate slow dynamics not included in the UKF filter model. Finally, we show that we can even use observed discretized sleep-state, which is not one of the model variables, to reconstruct model state and estimate unknown parameters. Sleep is implicated in many neurological disorders from epilepsy to schizophrenia, but simultaneous observation of the many brain components that regulate this behavior is difficult. We anticipate that this data assimilation framework will enable better understanding of the detailed interactions governing sleep and wake behavior and provide for better, more targeted, therapies.     

The genetic proteome: Using genetics to inform the proteome of mycobacterial pathogens

Mycobacterial pathogens pose a sustained threat to human health. There is a critical need for new diagnostics, therapeutics, and vaccines targeting both tuberculous and nontuberculous mycobacterial species. Understanding the basic mechanisms used by diverse mycobacterial species to cause disease will facilitate efforts to design new approaches toward detection, treatment, and prevention of mycobacterial disease. Molecular, genetic, and biochemical approaches have been widely employed to define fundamental aspects of mycobacterial physiology and virulence. The recent expansion of genetic tools in mycobacteria has further increased the accessibility of forward genetic approaches. Proteomics has also emerged as a powerful approach to further our understanding of diverse mycobacterial species. Detection of large numbers of proteins and their modifications from complex mixtures of mycobacterial proteins is now routine, with efforts of quantification of these datasets becoming more robust. In this review, we discuss the “genetic proteome,” how the power of genetics, molecular biology, and biochemistry informs and amplifies the quality of subsequent analytical approaches and maximizes the potential of hypothesis-driven mycobacterial research. Published proteomics datasets can be used for hypothesis generation and effective post hoc supplementation to experimental data. Overall, we highlight how the integration of proteomics, genetic, molecular, and biochemical approaches can be employed successfully to define fundamental aspects of mycobacterial pathobiology.     

Biochemical synthesis of chirally pure Rp oligonucleotide phosphorothioates

Oligonucleotide phosphorothioates have been synthesized using procaryotic DNA polymerase and oligonucleotide template/primer. The method facilitates the recovery of DNA polymerase and template/primer and is successful at the milligram scale. This revised version was published online in November 2006 with corrections to the Cover Date.     

IgG subclass specificity to C1q determined by surface plasmon resonance using Protein L capture technique

Recombinant monoclonal antibodies (mAbs) have become an important category of biological therapeutics. mAbs share the same structures and biological functions as endogenous IgG molecules. One function is complement-dependent cytotoxicity (CDC) initiation by binding of C1q. Traditionally, ELISA methods have been utilized to measure C1q binding. A new robust capture method was established in this study to measure the binding affinity of C1q to antibodies by surface plasmon resonance (SPR). The utility of this method was demonstrated by determination of the difference in IgG subclass specificity of C1q binding.