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1.
J Biol Chem ; 289(21): 14448-57, 2014 May 23.
Artículo en Inglés | MEDLINE | ID: mdl-24706763

RESUMEN

Cell penetrating peptides (CPP) and cationic antibacterial peptides (CAP) have similar physicochemical properties and yet it is not understood how such similar peptides display different activities. To address this question, we used Iztli peptide 1 (IP-1) because it has both CPP and CAP activities. Combining experimental and computational modeling of the internalization of IP-1, we show it is not internalized by receptor-mediated endocytosis, yet it permeates into many different cell types, including fungi and human cells. We also show that IP-1 makes pores in the presence of high electrical potential at the membrane, such as those found in bacteria and mitochondria. These results provide the basis to understand the functional redundancy of CPPs and CAPs.


Asunto(s)
Antibacterianos/farmacología , Péptidos Catiónicos Antimicrobianos/farmacología , Péptidos de Penetración Celular/farmacología , Péptidos/farmacología , Algoritmos , Secuencia de Aminoácidos , Antibacterianos/química , Antibacterianos/metabolismo , Péptidos Catiónicos Antimicrobianos/química , Péptidos Catiónicos Antimicrobianos/farmacocinética , Membrana Celular/efectos de los fármacos , Membrana Celular/metabolismo , Péptidos de Penetración Celular/química , Péptidos de Penetración Celular/farmacocinética , Endocitosis/genética , Células HEK293 , Humanos , Cinética , Factor de Apareamiento , Viabilidad Microbiana/efectos de los fármacos , Viabilidad Microbiana/genética , Modelos Biológicos , Datos de Secuencia Molecular , Mutación , Péptidos/química , Péptidos/farmacocinética , Saccharomyces cerevisiae/efectos de los fármacos , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Proteínas de Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/metabolismo
2.
PLoS Comput Biol ; 10(6): e1003690, 2014 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-24967739

RESUMEN

Communication between cells is a ubiquitous feature of cell populations and is frequently realized by secretion and detection of signaling molecules. Direct visualization of the resulting complex gradients between secreting and receiving cells is often impossible due to the small size of diffusing molecules and because such visualization requires experimental perturbations such as attachment of fluorescent markers, which can change diffusion properties. We designed a method to estimate such extracellular concentration profiles in vivo by using spatiotemporal mathematical models derived from microscopic analysis. This method is applied to populations of thousands of haploid yeast cells during mating in order to quantify the extracellular distributions of the pheromone α-factor and the activity of the aspartyl protease Bar1. We demonstrate that Bar1 limits the range of the extracellular pheromone signal and is critical in establishing α-factor concentration gradients, which is crucial for effective mating. Moreover, haploid populations of wild type yeast cells, but not BAR1 deletion strains, create a pheromone pattern in which cells differentially grow and mate, with low pheromone regions where cells continue to bud and regions with higher pheromone levels and gradients where cells conjugate to form diploids. However, this effect seems to be exclusive to high-density cultures. Our results show a new role of Bar1 protease regulating the pheromone distribution within larger populations and not only locally inside an ascus or among few cells. As a consequence, wild type populations have not only higher mating efficiency, but also higher growth rates than mixed MATa bar1Δ/MATα cultures. We provide an explanation of how a rapidly diffusing molecule can be exploited by cells to provide spatial information that divides the population into different transcriptional programs and phenotypes.


Asunto(s)
Procesamiento de Imagen Asistido por Computador/métodos , Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/fisiología , Ácido Aspártico Endopeptidasas/metabolismo , Microscopía Confocal/métodos , Mutación , Feromonas/metabolismo , Saccharomyces cerevisiae/química , Saccharomyces cerevisiae/citología , Proteínas de Saccharomyces cerevisiae/metabolismo
3.
FASEB J ; 26(2): 546-54, 2012 Feb.
Artículo en Inglés | MEDLINE | ID: mdl-22002907

RESUMEN

Sic1, cyclin-dependent kinase inhibitor of budding yeast, is synthesized in anaphase and largely degraded at the S-phase onset to regulate timing of DNA synthesis. Sic1 interacts with phase-specific B-type cyclin (Clb)-kinase (Cdk1) complexes, central regulators in cell cycle control. Its appearance is timed to mediate reduction in kinase activities at appropriate stages. Clbs are unstable proteins with extremely short half-lives. Interactions of Sic1 with Clbs have been detected both in vitro and in vivo by high-throughput genome-wide screenings. Furthermore, we have recently shown that Sic1 regulates waves of Clbs, acting as a timer in their appearance, thus controlling Cdk1-Clbs activation. The molecular mechanism is not yet fully understood but is hypothesized to occur via stoichiometric binding of Sic1 to Cdk1-Clb complexes. Using Förster resonance energy transfer (FRET) via fluorescence lifetime imaging microscopy (FLIM), we showed association of Sic1 to Clb cyclins in living yeast cells. This finding is consistent with the notion that inhibition of kinase activity can occur over the whole cell cycle progression despite variable Sic1 levels. Specifically, Sic1/Clb3 interaction was observed for the first time, and Sic1/Clb2 and Sic1/Clb5 pairs were confirmed, but no Sic1/Clb4 interaction was found, which suggests that, despite high functional homology between Clbs, only some of them can target Sic1 function in vivo.


Asunto(s)
Ciclina B/metabolismo , Proteínas Inhibidoras de las Quinasas Dependientes de la Ciclina/metabolismo , Proteínas de Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/metabolismo , Proteínas Bacterianas/genética , Proteínas Bacterianas/metabolismo , Secuencia de Bases , Proteína Quinasa CDC2/metabolismo , Ciclo Celular , Ciclina B/genética , Proteínas Inhibidoras de las Quinasas Dependientes de la Ciclina/genética , Cartilla de ADN/genética , Transferencia Resonante de Energía de Fluorescencia , Proteínas Luminiscentes/genética , Proteínas Luminiscentes/metabolismo , Microscopía Fluorescente , Complejos Multiproteicos , Dominios y Motivos de Interacción de Proteínas , Proteínas Recombinantes de Fusión/genética , Proteínas Recombinantes de Fusión/metabolismo , Saccharomyces cerevisiae/citología , Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/genética
4.
J Biol Chem ; 286(24): 21835-43, 2011 Jun 17.
Artículo en Inglés | MEDLINE | ID: mdl-21521689

RESUMEN

The ATP binding cassette (ABC) transporter Aus1 is expressed under anaerobic growth conditions at the plasma membrane of the yeast Saccharomyces cerevisiae and is required for sterol uptake. These observations suggest that Aus1 promotes the translocation of sterols across membranes, but the precise transport mechanism has yet to be identified. In this study, an extraction and purification procedure was developed to characterize the Aus1 transporter. The detergent-solubilized protein was able to bind and hydrolyze ATP. Mutagenesis of the conserved lysine to methionine in the Walker A motif abolished ATP hydrolysis. Likewise, ATP hydrolysis was inhibited by classical inhibitors of ABC transporters. Upon reconstitution into proteoliposomes, the ATPase activity of Aus1 was specifically stimulated by phosphatidylserine (PS) in a stereoselective manner. We also found that Aus1-dependent sterol uptake, but not Aus1 expression and trafficking to the plasma membrane, was affected by changes in cellular PS levels. These results suggest a direct interaction between Aus1 and PS that is critical for the activity of the transporter.


Asunto(s)
Transportadoras de Casetes de Unión a ATP/metabolismo , Adenosina Trifosfato/química , Membrana Celular/metabolismo , Regulación Fúngica de la Expresión Génica , Proteínas de Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/metabolismo , Adenosina Trifosfatasas/química , Hidrólisis , Concentración 50 Inhibidora , Lípidos/química , Liposomas/química , Lisina/química , Metionina/química , Microscopía Confocal/métodos , Nucleótidos/química , Fosfatidilserinas/química
5.
NPJ Syst Biol Appl ; 4: 17, 2018.
Artículo en Inglés | MEDLINE | ID: mdl-29844922

RESUMEN

Gene expression is a stochastic process and its appropriate regulation is critical for cell cycle progression. Cellular stress response necessitates expression reprogramming and cell cycle arrest. While previous studies are mostly based on bulk experiments influenced by synchronization effects or lack temporal distribution, time-resolved methods on single cells are needed to understand eukaryotic cell cycle in context of noisy gene expression and external perturbations. Using smFISH, microscopy and morphological markers, we monitored mRNA abundances over cell cycle phases and calculated transcriptional noise for SIC1, CLN2, and CLB5, the main G1/S transition regulators in budding yeast. We employed mathematical modeling for in silico synchronization and for derivation of time-courses from single cell data. This approach disclosed detailed quantitative insights into transcriptional regulation with and without stress, not available from bulk experiments before. First, besides the main peak in G1 we found an upshift of CLN2 and CLB5 expression in late mitosis. Second, all three genes showed basal expression throughout cell cycle enlightening that transcription is not divided in on and off but rather in high and low phases. Finally, exposing cells to osmotic stress revealed different periods of transcriptional inhibition for CLN2 and CLB5 and the impact of stress on cell cycle phase duration. Combining experimental and computational approaches allowed us to precisely assess cell cycle progression timing, as well as gene expression dynamics.

6.
Front Microbiol ; 9: 1240, 2018.
Artículo en Inglés | MEDLINE | ID: mdl-29963019

RESUMEN

Although most antibiotics act on cells that are actively dividing and non-dividing cells such as in microbe sporulation or cancer stem cells represent a new paradigm for the control of disease. In addition to their relevance to health, such antibiotics may promote our understanding of the relationship between the cell cycle and cell death. No antibiotic specifically acting on microbial cells arrested in their cell cycle has been identified until the present time. In this study we used an antimicrobial peptide derived from α-pheromone, IP-1, targeted against MATa Saccharomyces cerevisiae cells in order to assess its dependence on cell cycle arrest to kill cells. Analysis by flow cytometry and fluorescence microscopy of various null mutations of genes involved in biological processes activated by the pheromone pathway (the mitogen-activated protein kinase pathway, cell cycle arrest, cell proliferation, autophagy, calcium influx) showed that IP-1 requires arrest in G0/G1 in order to kill yeast cells. Isolating cells in different cell cycle phases by elutriation provided further evidence that entry into cell cycle arrest, and not into G1 phase, is necessary if our peptide is to kill yeast cells. We also describe a variant of IP-1 that does not activate the pheromone pathway and consequently does not kill yeast cells that express the pheromone's receptor; the use of this variant peptide in combination with different cell cycle inhibitors that induce cell cycle arrest independently of the pheromone pathway confirmed that it is cell cycle arrest that is required for the cell death induced by this peptide in yeast. We show that the cell death induced by IP-1 differs from that induced by α-pheromone and depends on FIG1 in a way independent of the cell cycle arrest induced by the pheromone. Thus, IP-1 is the first molecule described that specifically kills microbial cells during cell cycle arrest, a subject of interest beyond the process of mating in yeast cells. The experimental system described in this study should be useful in the study of the mechanisms at play in the communication between cell cycle arrest and cell death on other organisms, hence promoting the development of new antibiotics.

7.
FEBS J ; 279(22): 4213-30, 2012 Nov.
Artículo en Inglés | MEDLINE | ID: mdl-23013467

RESUMEN

The cell division cycle orchestrates cellular growth and division. The machinery underpinning the cell division cycle is well characterized, but the actual cue(s) driving the cell division cycle remains unknown. In rapidly growing and dividing yeast cells, this cue has been proposed to be cell size. Presumably, a mechanism communicating cell size acts as gatekeeper for the cell division cycle via the G(1) network, which triggers G(1) exit only when a critical size has been reached. Here, we evaluate this hypothesis with a minimal core model linking metabolism, growth and the cell division cycle. Using this model, we (a) present support for coordinated regulation of G(1)/S and G(2)/M transition in Saccharomyces cerevisiae in response to altered growth conditions, (b) illustrate the intrinsic antagonism between G(1) progression and cell size and (c) provide evidence that the coupling of growth and division is sufficient to allow for size homeostasis without directly communicating or measuring cell size. We show that even with a rudimentary version of the G(1) network consisting of a single unregulated cyclin, size homeostasis is maintained in populations during autocatalytic growth when the geometric constraint on nutrient supply is considered. Taken together, our results support the notion that cell size is a consequence rather than a regulator of growth and division.


Asunto(s)
Ciclo Celular/fisiología , Proliferación Celular , Tamaño de la Célula , Modelos Biológicos , Saccharomyces cerevisiae/crecimiento & desarrollo , Transducción de Señal , Simulación por Computador , Homeostasis , Saccharomyces cerevisiae/metabolismo
8.
Mol Biosyst ; 7(10): 2804-12, 2011 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-21717009

RESUMEN

The budding yeast genome comprises roughly 6000 genes generating a number of about 10 000 mRNA copies, which gives a general estimation of 1-2 mRNA copies generated per gene. What does this observation implicate for cellular processes and their regulation? Whether the number of mRNA molecules produced is important for setting the amount of proteins implicated in a particular function is at present unknown. In this context, we studied cell cycle control as one of the highly fine tuned processes that guarantee the precise timing of events essential for cell growth. Here, we developed a stochastic model that addresses the effect of varying the mRNA amount of Sic1, inhibitor of the Cdk1-Clb5 kinase activity, and the resulting noise on Sic1/Clb5 balance at the G1/S transition. We considered a range of SIC1 transcripts number according to our experimental data derived from the MS2 mRNA tagging system. Computational simulation revealed that an increased amount of SIC1 mRNAs lead to an amplified dispersion of Sic1 protein levels, suggesting mRNA control being critical to set timing of Sic1 downregulation and, therefore, S phase onset. Moreover, Sic1/Clb5 balance is strongly influenced by Clb5 production in both daughter and mother cells in order to maintain the characteristic time of S phase entry overall the population. Furthermore, CLB5 mRNA molecules calculated to reproduce temporal dynamics of Sic1 and Clb5 for daughter and mother cells agree with recent data obtained from more complex networks. Thus, the results presented here provide novel insights into the influence that the mRNA amount and, indirectly, the transcription process exploit on cell cycle progression.


Asunto(s)
Ciclo Celular , Proteínas Inhibidoras de las Quinasas Dependientes de la Ciclina/metabolismo , ARN Mensajero/genética , Proteínas de Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/citología , Secuencia de Bases , Clonación Molecular , Proteínas Inhibidoras de las Quinasas Dependientes de la Ciclina/genética , Cartilla de ADN , Proteínas de Saccharomyces cerevisiae/genética , Procesos Estocásticos
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