Bioprocess design and economic analysis for the commercial production of environmentally friendly bioinsecticides from Bacillus thuringiensis HD-1 kurstaki

A production process for B. thuringiensis (Bt) bioinsecticides was designed in detail, including alternative batch, low-density fed-batch (LDFB), and high-density fed-batch (HDFB) fermentation configurations. Capital and operating costs, as well as profitability based on simple rate of return, were performed using a purpose-written FORTRAN program, explicitly analyzing production of a water-based flowable product used in forestry applications.The total capital cost was 18 million dollars (Canadian dollars) for a stand-alone plant with base-scale capacity of 3 x 10(7) billion international units (BIU)/year. Raw material costs amounted to 1.5 million dollars yearly, of which approximately half was for formulation ingredients. Per-unit production cost rose sharply for scales of less than 1 x 10(7) BIU/year, but was little affected by scale above 3 x 10(7) BIU/year. Product cost was much lower at all scales for a LDFB as opposed to batch fermentation process, but HDFB gave relatively little additional cost benefit. Profitability analysis performed by co-varying scale and selling price showed that break-even occurred at a price of 0.45 dollars/BIU for a batch process at base scale, while with LDFB fermentation the same production volume sold at 0.35 dollars/BIU gave a 12% rate of return. Since the assumed base scale would represent 8-15% of current world Bt bioinsecticide production, based on value or volume, it was concluded that profitability would require some or all of the following elements: targeting higher-value markets such as disease vector control, in addition to forestry; a potentially lower plant capacity (although at least 1 x 10(7) BIU/year;) and coproduction of other large-volume microbial products to absorb capacity and match bioinsecticide output to market demand.     

Bayesian experimental design for nonlinear mixed-effects models with application to HIV dynamics

Bayesian experimental design is investigated for Bayesian analysis of nonlinear mixed-effects models. Existence of the posterior risk for parameter estimation is shown. When the same prior distribution is used for both design and inference, existence of the preposterior risk for design is also proven. If the prior distribution used in design is different from that used for inference, sufficient conditions are established for existence of the preposterior risk for design. A case study of design for an experiment in population HIV dynamics is provided.     

Can contact potentials reliably predict stability of proteins?

The simplest approximation of interaction potential between amino acid residues in proteins is the contact potential, which defines the effective free energy of a protein conformation by a set of amino acid contacts formed in this conformation. Finding a contact potential capable of predicting free energies of protein states across a variety of protein families will aid protein folding and engineering in silico on a computationally tractable time-scale. We test the ability of contact potentials to accurately and transferably (across various protein families) predict stability changes of proteins upon mutations. We develop a new methodology to determine the contact potentials in proteins from experimental measurements of changes in protein's thermodynamic stabilities (DeltaDeltaG) upon mutations. We apply our methodology to derive sets of contact interaction parameters for a hierarchy of interaction models including solvation and multi-body contact parameters. We test how well our models reproduce experimental measurements by statistical tests. We evaluate the maximum accuracy of predictions obtained by using contact potentials and the correlation between parameters derived from different data-sets of experimental (DeltaDeltaG) values. We argue that it is impossible to reach experimental accuracy and derive fully transferable contact parameters using the contact models of potentials. However, contact parameters may yield reliable predictions of DeltaDeltaG for datasets of mutations confined to the same amino acid positions in the sequence of a single protein.     

A simple physical model for the prediction and design of protein-DNA interactions

Protein-DNA interactions are crucial for many biological processes. Attempts to model these interactions have generally taken the form of amino acid-base recognition codes or purely sequence-based profile methods, which depend on the availability of extensive sequence and structural information for specific structural families, neglect side-chain conformational variability, and lack generality beyond the structural family used to train the model. Here, we take advantage of recent advances in rotamer-based protein design and the large number of structurally characterized protein-DNA complexes to develop and parameterize a simple physical model for protein-DNA interactions. The model shows considerable promise for redesigning amino acids at protein-DNA interfaces, as design calculations recover the amino acid residue identities and conformations at these interfaces with accuracies comparable to sequence recovery in globular proteins. The model shows promise also for predicting DNA-binding specificity for fixed protein sequences: native DNA sequences are selected correctly from pools of competing DNA substrates; however, incorporation of backbone movement will likely be required to improve performance in homology modeling applications. Interestingly, optimization of zinc finger protein amino acid sequences for high-affinity binding to specific DNA sequences results in proteins with little or no predicted specificity, suggesting that naturally occurring DNA-binding proteins are optimized for specificity rather than affinity. When combined with algorithms that optimize specificity directly, the simple computational model developed here should be useful for the engineering of proteins with novel DNA-binding specificities.     

The effect of hormones on bone growth is mediated through mechanical stress

Mechanical stresses play a key role in regulating cell growth and cell differentiation. Using mechanical and physiological data available in the literature, we are able to construct a growth curve of a child, which we compare to the standard curve. It appears likely that the impact of hormones on pubertal growth rate sprout followed by growth arrest can be solely explained by increased mechanical stresses. The uptake of hormones by the muscles results in increased mechanical stress on the chondrocyte before and at the puberty, resulting in a peak in growth followed by growth cessation.     

Potential automata. Application to the genetic code III

In previous notes, we have described both mathematical properties of potential (n-switches) and potential-Hamiltonian (Liénard systems) continuous differential systems, and also biological applications, especially those concerning primitive cyclic RNAs related to the genetic code. In the present note, we give a general definition of a potential automaton, and we show that a discrete Hopfield-like system already introduced by Goles et al. is a good candidate for such a potential automaton: it has a Lyapunov functional that decreases on its trajectories and whose time derivative is just its discrete velocity. Then we apply this new notion of potential automaton to the genetic code. We show in particular that the consideration of only physicochemical properties of amino-acids, like their molecular weight, hydrophobicity and ability to create hydrogen bonds suffices to build a potential decreasing on trajectories corresponding to the synonymy classes of the genetic code. Such an 'a minima' construction reinforces the classical stereochemical hypothesis about the origin of the genetic code and authorizes new views about the optimality of its synonymy classes.     

Effects of suspended mussel culture on benthic-pelagic coupling in a coastal upwelling system (Ría de Vigo, NW Iberian Peninsula)

The influence of suspended mussel culture on the benthic-pelagic coupling was evaluated in the Ría de Vigo, in the coastal upwelling system of the NW Iberian Peninsula, during the month of July 2004. Measurements of water column properties were carried out at three stations in the Ría de Vigo: under a mussel raft (1), and at two reference sites in the main channel (2) and in the inner part (3) of the Ría. Dissolved nutrients, dissolved oxygen and inorganic carbon benthic fluxes were measured by means of a benthic chamber at stations 1 and 3. Sediment traps were deployed at 6 locations to estimate vertical fluxes. The water column structure at the three study stations was very similar, characterized by upwelling conditions during the second week of July and a posterior stratification showing a strong thermocline, with a depth fluctuation mainly modulated by the shelf wind regime. Vertical POC fluxes underneath the mussel raft (3 g C m⁻² d^− 1) were 3 times higher than those obtained between rafts and 10 times higher than in the main channel reference site. Dissolved oxygen, ammonium, silicate and phosphate benthic fluxes were significantly higher under the raft than at the inner Ría reference site. A 1D carbon budget showed the importance of benthic metabolism under the raft (2.3 ± 0.8 g C m^− 2 d^− 1), being higher than the organic carbon produced at the photic layer (0.7 ± 0.3 g C m^− 2 d^− 1), as a result of higher organic loading compared to the inner Ría reference site. The results show for the first time the important role that suspended mussel cultures play in the benthic-pelagic coupling in this coastal upwelling ecosystem.