A simple structured model for recombinant IDShr protein production in Pichia pastoris

Mendoza, D.F.; Enciso, Néstor Ariel Algecira; Ruiz, Henry Córdoba; Avellaneda, Luis Alejandro Barrera

doi:10.1007/s10529-008-9750-1

Cited by 11 publications

(6 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To overcome these limitations, constraints-based models have been combined with data-driven expressions for protein productivity, such as kinetic, growth-rate associated, functions described above [18,34] or more sophisticated relationships built through projection to latent structures [30].…”

Section: Introductionmentioning

confidence: 99%

Estimation of recombinant protein production in Pichia pastoris based on a constraint-based model

Tortajada

Llaneras

Ramón

et al. 2012

Journal of Process Control

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Estimation of recombinant protein production in Pichia pastoris based on a constraint-based model

Tortajada

Llaneras

Ramón

et al. 2012

Journal of Process Control

View full text Add to dashboard Cite

“…Other hybrid approaches have been used to overcome the limitations of constraintbased models to produce valid estimates for protein productivity, for example combining them with data-driven expressions for protein productivity, such as kinetic, growth-rate associated, functions described above (Ren et al, 2003;Mendoza-Muñoz et al, 2008) or more sophisticated relationships built through projection to latent structures (Carinhas et al, 2011). Note that in these cases, the structure and not only the value of parameters depends on the particular experimental system analysed.…”

Section: Discussionmentioning

confidence: 99%

“…A typical inhibition profile is well documented at high methanol concentrations, and many authors fit growth profiles on methanol to uncompetitive inhibition models such as Haldane model (Ren et al, 2003;Zhang et al, 2000;Mendoza-Muñoz et al, 2008). Other references use Monod model also for growth on methanol, but in a limited range of concentrations (D'Anjou and Daugulis, 1997;Curvers et al, 2002;Jahic et al, 2002;Oliveira et al, 2005;Jungo et al, 2007).…”

Section: Monod Modelmentioning

confidence: 99%

“…More detailed models considering induction, proteolysis, transcription and translation phenomena have also been used in this context, but these are necessarily proteinspecific (Chung et al, 2010;Çelik et al, 2010;Sohn et al, 2010) or require extensive parameter fitting (Mendoza-Muñoz et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…To overcome these limitations, constraints-based models have been combined with data-driven expressions for protein productivity, such as kinetic, growth-rate associated, functions described above (Ren et al, 2003;Mendoza-Muñoz et al, 2008) or more sophisticated relationships built through projection to latent structures (Carinhas et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Process development for the obtention and use of recombinant glycosidases: expression, modelling and immobilisation

Serra¹

View full text Add to dashboard Cite

"There is a driving force more powerful than steam, electricity and nuclear power: the will." Albert Einstein 5 AgradecimientosQuiero dar las gracias a todas las personas que me han acompañado estos años y a las que debo, por distintas razones pero todas importantes, haber conseguido llevar a cabo esta tesis.A mis directores, Daniel, por darme su confianza desde el principio y ejemplo, día tras día, y Jesús, por descubrirme la biología de sistemas y su respaldo incondicional y permanente. A los dos, por pensar que es buena idea mezclar a biólogos e ingenieros, por ofrecerme la oportunidad de trabajar con ellos, y haber encontrado siempre tiempo para ayudarme.A la empresa Biopolis, por financiar mis cursos de formación y permitirme dedicar parte de mi tiempo a realizar este trabajo de investigación.A todo el Departamento de Ingeniería de Sistemas y Automática, por su profesionalidad, y por facilitarme siempre compatibilizar mi trabajo con la realización de la tesis doctoral, y en particular a Jose Luis y Quique por decidir un buen día aplicar su trabajo a estos bichos tan complejos.Muchas gracias a Kiko, por todas las tardes de trabajo y artículos compartidos, por su rigor y generosidad en la colaboración, sin la que gran parte de esta tesis no habría existido.A Pedro, Daniel y Jamal, del Instituto de Ciencia de los Materiales de la Universitat de València, por proporcionarme su ayuda, materiales para la inmovilización e ideas para el análisis y la discusión a lo largo de todos estos años.A todos los compañeros de Biopolis que han estado a mi lado cada día. Muchas gracias a mis más queridos moleculares Verónica, Alex, Antonia, Bea, Dani, Diego -con su ayuda salió el mejor transformante! -Dunja y Silbia, por demostrarme que lo imposible puede ser, y que vale la pena. Gracias a Esther, por animarme más y mejor que nadie. Gracias a María por sus consejos y HPLC inestimables. Gracias a Boro, Empar, Bea, Angela, Roseta, Josep, Patri, Aida, Pepa, Fernando, Silvia, Nuria, Rosa, Maria, Marta, Vicente, Bruno, Nico, Jose y Javi, y a Iryna, Ana, Lola, Jose, Vicky, Carlos, Nacho, Montse, Daniel y Violeta. Gracias a Emma, Chari, David y Mercedes por acogerme en su día en la planta piloto. Gracias a los chicos de Life, y especialmente a Cristina, Juan y Paco por tener siempre una sonrisa fuera de horario.A Jaime Primo y Mª Angeles Lluch, por abrirme las puertas de la biotecnología. A Chelo, Rosa y Miguel Ángel, por iniciarme en la investigación. A Jose Luis y Auxi y todas sus chicas, por acogerme con absoluta generosidad en su laboratorio y enseñarme cómo clonan los profesionales. Gracias también a los investigadores del IATA, Andrew, Marga, Luisa, Adela, Oscar, Juanan, Jose Vicente, Salvador y Paloma, por su apoyo imprescindible en los comienzos.A mis padres y mi hermana Carmela, por quererme y apoyarme siempre, y a toda mi familia, y especialmente, a mis abuelos, por creer en mí. A ellos, y los amigos que ya son de casa, por darme fuerzas y perspectiva. A Alfonso, porque sin él nada sería importante.¡Por fin! Gracias a todos...

show abstract

Integrating metabolic modeling and population heterogeneity analysis into optimizing recombinant protein production by Komagataella (Pichia) pastoris

Theron

Berríos

Delvigne

et al. 2017

Appl Microbiol Biotechnol

View full text Add to dashboard Cite

The methylotrophic yeast Komagataella (Pichia) pastoris has become one of the most utilized cell factories for the production of recombinant proteins over the last three decades. This success story is linked to its specific physiological traits, i.e., the ability to grow at high cell density in inexpensive culture medium and to secrete proteins at high yield. Exploiting methanol metabolism is at the core of most P. pastoris-based processes but comes with its own challenges. Co-feeding cultures with glycerol/sorbitol and methanol is a promising approach, which can benefit from improved understanding and prediction of metabolic response. The development of profitable processes relies on the construction and selection of efficient producing strains from less efficient ones but also depends on the ability to master the bioreactor process itself. More specifically, how a bioreactor processes could be monitored and controlled to obtain high yield of production. In this review, new perspectives are detailed regarding a multi-faceted approach to recombinant protein production processes by P. pastoris; including gaining improved understanding of the metabolic pathways involved, accounting for variations in transcriptional and translational efficiency at the single cell level and efficient monitoring and control of methanol levels at the bioreactor level.

show abstract

A simple structured model for recombinant IDShr protein production in Pichia pastoris

Cited by 11 publications

References 28 publications

Estimation of recombinant protein production in Pichia pastoris based on a constraint-based model

Estimation of recombinant protein production in Pichia pastoris based on a constraint-based model

Process development for the obtention and use of recombinant glycosidases: expression, modelling and immobilisation

Integrating metabolic modeling and population heterogeneity analysis into optimizing recombinant protein production by Komagataella (Pichia) pastoris

Contact Info

Product

Resources

About