Targeted Nanofitin-drug Conjugates Achieve Efficient Tumor Delivery and Therapeutic Effect in an EGFRpos Mouse Xenograft Model.

Adjusting the molecular size, the valency and the pharmacokinetics of drug conjugates are as many leverages to improve their therapeutic window, notably by affecting tumor penetration, renal clearance, and short systemic exposure. In that regard, small tumor-targeting ligands are gaining attention. In this study, we demonstrate the benefits of the small Nanofitin alternative scaffolds (7 kDa) as selective tumor-targeting modules for the generation of drug conjugates, focusing on Nanofitins B10 and D8 directed against the EGFR. Owing to their small size and monovalent format, the two Nanofitins displayed a fast and deep tumor penetration in EGFR-positive A431 xenografts in BALB/c nude mice after intravenous administration, yielding to a targeting of respectively 67.9% ± 14.1 and 98.9% ± 0.7 of the tumor cells as demonstrated by IHC. Conjugation with the monomethyl auristatin E toxin provided homogeneous Nanofitin-drug conjugates, with an overall yield of ≥97%, for in vivo assessment in a curative xenograft model using bioluminescent, EGFR-positive, A431 cells in BALB/c nude mice. Internalization was found critical for efficient release of the toxin. Hence, the intravenous administration of the D8-based construct showed significant antitumor effect in vivo as determined by monitoring tumor volumes and bioluminescence levels over 2 months.

Hybrid metabolic flux analysis and recombinant protein prediction in Pichia pastoris X-33 cultures expressing a single-chain antibody fragment.

Despite the growing importance of the Pichia pastoris expression system as industrial workhorse, the literature is almost absent in systematic studies on how culture medium composition affects central carbon fluxes and heterologous protein expression. In this study we investigate how 26 variations of the BSM+PTM1 medium impact central carbon fluxes and protein expression in a P. pastoris X-33 strain expressing a single-chain antibody fragment. To achieve this goal, we adopted a hybrid metabolic flux analysis (MFA) methodology, which is a modification of standard MFA to predict the rate of synthesis of recombinant proteins. Hybrid MFA combines the traditional parametric estimation of central carbon fluxes with non-parametric statistical modeling of product-related quantitative or qualitative measurements as a function of central carbon fluxes. It was observed that protein yield variability was 53.6 % (relative standard deviation) among the different experiments. Protein yield is much more sensitive to medium composition than biomass growth, which is mainly determined by the carbon source availability and main salts. Hybrid MFA was able to describe accurately the protein yield with normalized RMSE of 6.3 % over 5 independent experiments. The metabolic state that promotes high protein yields is characterized by high overall metabolic rates through main central carbon pathways concomitantly with a relative shift of carbon flux from biosynthetic towards energy generating pathways.

Analysis of culture media screening data by projection to latent pathways: The case of Pichia pastoris X-33.

Cell culture media formulations contain hundreds of individual components in water solutions which have complex interactions with metabolic pathways. The currently used statistical design methods are empirical and very limited to explore such a large design space. In a previous work we developed a computational method called projection to latent pathways (PLP), which was conceived to maximize covariance between envirome and fluxome data under the constraint of metabolic network elementary flux modes (EFM). More specifically, PLP identifies a minimal set of EFMs (i.e., pathways) with the highest possible correlation with envirome and fluxome measurements. In this paper we extend the concept for the analysis of culture media screening data to investigate how culture medium components up-regulate or down-regulate key metabolic pathways. A Pichia pastoris X-33 strain was cultivated in 26 shake flask experiments with variations in trace elements concentrations and basal medium dilution, based on the standard BSM+PTM1 medium. PLP identified 3 EFMs (growth, maintenance and by-product formation) describing 98.8% of the variance in observed fluxes. Furthermore, PLP presented an overall predictive power comparable to that of PLS regression. Our results show iron and manganese at concentrations close to the PTM1 standard inhibit overall metabolic activity, while the main salts concentration (BSM) affected mainly energy expenditures for cellular maintenance.

Design of pathway-level bioprocess monitoring and control strategies supported by metabolic networks.

In this chapter we explore the basic tools for the design of bioprocess monitoring, optimization, and control algorithms that incorporate a priori knowledge of metabolic networks. The main advantage is that this ultimately enables the targeting of intracellular control variables such as metabolic reactions or metabolic pathways directly linked with productivity and product quality. We analyze in particular design methods that target elementary modes of metabolic networks. The topics covered include the analysis of the structure of metabolic networks, computation and reduction of elementary modes, measurement methods for the envirome, envirome-guided metabolic reconstruction, and macroscopic dynamic modeling and control. These topics are illustrated with applications to a cultivation process of a recombinant Pichia pastoris X33 strain expressing a single-chain antibody fragment (scFv).

Cell functional enviromics: unravelling the function of environmental factors.

BACKGROUND: While functional genomics, focused on gene functions and gene-gene interactions, has become a very active field of research in molecular biology, equivalent methodologies embracing the environment and gene-environment interactions are relatively less developed. Understanding the function of environmental factors is, however, of paramount importance given the complex, interactive nature of environmental and genetic factors across multiple time scales. RESULTS: Here, we propose a systems biology framework, where the function of environmental factors is set at its core. We set forth a "reverse" functional analysis approach, whereby cellular functions are reconstructed from the analysis of dynamic envirome data. Our results show these data sets can be mapped to less than 20 core cellular functions in a typical mammalian cell culture, while explaining over 90% of flux data variance. A functional enviromics map can be created, which provides a template for manipulating the environmental factors to induce a desired phenotypic trait. CONCLUSION: Our results support the feasibility of cellular function reconstruction guided by the analysis and manipulation of dynamic envirome data.

Bioprocess iterative batch-to-batch optimization based on hybrid parametric/nonparametric models.

This paper presents a novel method for iterative batch-to-batch dynamic optimization of bioprocesses. The relationship between process performance and control inputs is established by means of hybrid grey-box models combining parametric and nonparametric structures. The bioreactor dynamics are defined by material balance equations, whereas the cell population subsystem is represented by an adjustable mixture of nonparametric and parametric models. Thus optimizations are possible without detailed mechanistic knowledge concerning the biological system. A clustering technique is used to supervise the reliability of the nonparametric subsystem during the optimization. Whenever the nonparametric outputs are unreliable, the objective function is penalized. The technique was evaluated with three simulation case studies. The overall results suggest that the convergence to the optimal process performance may be achieved after a small number of batches. The model unreliability risk constraint along with sampling scheduling are crucial to minimize the experimental effort required to attain a given process performance. In general terms, it may be concluded that the proposed method broadens the application of the hybrid parametric/nonparametric modeling technique to "newer" processes with higher potential for optimization.

Process development for the mass production of Ehrlichia ruminantium.

This work describes the optimization of a cost-effective process for the production of an inactivated bacterial vaccine against heartwater and the first attempt to produce the causative agent of this disease, the rickettsia Ehrlichia ruminantium (ER), using stirred tanks. In vitro, it is possible to produce ER using cultures of ruminant endothelial cells. Herein, mass production of these cells was optimized for stirring conditions. The effect of inoculum size, microcarrier type, concentration of serum at inoculation time and agitation rate upon maximum cell concentration were evaluated. Several strategies for the scale-up of cell inoculum were also tested. Afterwards, using the optimized parameters for cell growth, ER production in stirred tanks was validated for two ER strains (Gardel and Welgevonden). Critical parameters related with the infection strategy such as serum concentration at infection time, multiplicity and time of infection, and medium refeed strategy were analyzed. The results indicate that it is possible to produce ER in stirred tank bioreactors, under serum-free culture conditions, reaching a 6.5-fold increase in ER production yields. The suitability of this process was validated up to a 2-l scale and a preliminary cost estimation has shown that the stirred tanks are the least expensive culture method. Overall, these results are crucial to define a scaleable and fully controlled process for the production of a heartwater vaccine and open "new avenues" for the production of vaccines against other ehrlichial species, with emerging impact in human and animal health.

A procedure for high-yield spore production by Bacillus subtilis.

Bacillus subtilis spores have a number of potential applications, which include their use as probiotics and competitive exclusion agents to control zoonotic pathogens in animal production. The effect of cultivation conditions on Bacillus subtilis growth and sporulation was investigated in batch bioreactions performed at a 2-L scale. Studies of the cultivation conditions (pH, dissolved oxygen concentration, and media composition) led to an increase of the maximum concentration of vegetative cell from 2.6 x 10(9) to 2.2 x 10(10) cells mL(-)(1) and the spore concentration from 4.2 x 10(8) to 5.6 x 10(9) spores mL(-)(1). A fed-batch bioprocess was developed with the addition of a nutrient feeding solution using an exponential feeding profile obtained from the mass balance equations. Using the developed feeding profile, starting at the middle of the exponential growth phase and finishing in the late exponential phase, an increase of the maximum vegetative cell concentration and spore concentration up to 3.6 x 10(10) cells mL(-)(1) and 7.4 x 10(9) spores mL(-)(1), respectively, was obtained. Using the developed fed-batch bioreaction a 14-fold increase in the concentration of the vegetative cells was achieved. Moreover, the efficiency of sporulation under fed-batch bioreaction was 21%, which permitted a 19-fold increase in the final spore concentration, to a final value of 7.4 x 10(9) spores mL(-)(1). This represents a 3-fold increase relative to the highest reported value for Bacillus subtilis spore production.