Copy Number Protein Research Articles

Skeletal muscle from aged American Quarter Horses shows impairments in mitochondrial biogenesis and expression of autophagy markers

Aging is associated with decreased mitochondrial content and function in skeletal muscle, possibly due to compromised biogenesis and autophagic removal of dysfunctional mitochondria. The aim of this study was to compare markers of mitochondrial content and biogenesis and of autophagy between skeletal muscle from young and aged American Quarter Horses. Citrate synthase protein and mtDNA copy number were decreased in triceps brachii (TB) muscle (P<0.05) from aged horses, suggesting an age-related decline in mitochondrial content. Concomitantly, mRNA expression of PGC-1α and TFAM, regulators of mitochondrial biogenesis, was lower in aged compared to young TB (P<0.05). Expression of autophagy markers suggested an age-associated decline of autophagy. The autophagosomal cargo protein SQSTM/p62 accumulated with age in both muscles (P<0.05). Expression of Autophagy-related protein Atg5 (P<0.05) and the autophagosome-bound form of Microtubule-associated protein light chain 3 (LC3-II; P<0.05) were lower in aged compared to young TB. While LC3 transcript level was elevated in aged compared to young GM (P<0.001), protein expression of LC3-II was unaffected. Gene expression of Lysosomal Membrane-Associated Protein 2 (LAMP2) was not affected by age in either muscle. However, LAMP2 protein expression declined with age (P<0.05), suggesting a decline in autophagosome-lysosome fusion. Taken together, our data indicate that equine skeletal muscle mitochondrial content and biogenesis were impaired with age. Further, autophagosome formation and lysosomal degradation were negatively affected in aged TB and GM, respectively. Future research needs to explore whether interventions targeting these cellular processes can prolong health and performance of aging American Quarter Horses.

Stochastic fluctuations can reveal the feedback signs of gene regulatory networks at the single-molecule level

Understanding the relationship between spontaneous stochastic fluctuations and the topology of the underlying gene regulatory network is of fundamental importance for the study of single-cell stochastic gene expression. Here by solving the analytical steady-state distribution of the protein copy number in a general kinetic model of stochastic gene expression with nonlinear feedback regulation, we reveal the relationship between stochastic fluctuations and feedback topology at the single-molecule level, which provides novel insights into how and to what extent a feedback loop can enhance or suppress molecular fluctuations. Based on such relationship, we also develop an effective method to extract the topological information of a gene regulatory network from single-cell gene expression data. The theory is demonstrated by numerical simulations and, more importantly, validated quantitatively by single-cell data analysis of a synthetic gene circuit integrated in human kidney cells.

Emergent Lévy behavior in single-cell stochastic gene expression.

Single-cell gene expression is inherently stochastic; its emergent behavior can be defined in terms of the chemical master equation describing the evolution of the mRNA and protein copy numbers as the latter tends to infinity. We establish two types of "macroscopic limits": the Kurtz limit is consistent with the classical chemical kinetics, while the Lévy limit provides a theoretical foundation for an empirical equation proposed in N. Friedman etal., Phys. Rev. Lett. 97, 168302 (2006)PRLTAO0031-900710.1103/PhysRevLett.97.168302. Furthermore, we clarify the biochemical implications and ranges of applicability for various macroscopic limits and calculate a comprehensive analytic expression for the protein concentration distribution in autoregulatory gene networks. The relationship between our work and modern population genetics is discussed.

Protein Phosphatase Magnesium-Dependent 1δ (PPM1D) Expression as a Prognostic Marker in Adult Supratentorial Diffuse Astrocytic and Oligodendroglial Tumors.

BackgroundProtein phosphatase magnesium-dependent 1δ (PPM1D) is a p53-induced serine/threonine phosphatase, which is overexpressed in various human cancers. A recent study reported that a mutation in the PPM1D gene is associated with poor prognosis in brainstem gliomas. In this study, we evaluated the utility of PPM1D as a prognostic biomarker of adult supratentorial diffuse astrocytic and oligodendroglial tumors.MethodsTo investigate PPM1D protein expression, mRNA expression, and copy number changes, immunohistochemistry, RNAscope in situ hybridization, and fluorescence in situ hybridization were performed in 84 adult supratentorial diffuse gliomas. We further analyzed clinical characteristics and overall survival (OS) according to PPM1D protein expression, and examined its correlation with other glioma biomarkers such as isocitrate dehydrogenase (IDH) mutation, and p53 expression.ResultsForty-six cases (54.8%) were PPM1D-positive. PPM1D expression levels were significantly correlated with PPM1D transcript levels (p= .035), but marginally with PPM1D gene amplification (p=.079). Patients with high-grade gliomas showed a higher frequency of PPM1D expression than those with low-grade gliomas (p <.001). Multivariate analysis demonstrated that PPM1D expression (hazard ratio [HR], 2.58; p=.032), age over 60 years (HR, 2.55; p=.018), and IDH1 mutation (HR, 0.18; p=.002) were significantly independent prognostic factors; p53 expression had no prognostic significance (p=.986). The patients with tumor expressing PPM1D showed a shorter OS (p=.003). Moreover, patients with tumor harboring wild-type IDH1 and PPM1D expression had the worst OS (p<.001).ConclusionsOur data suggest that a subset of gliomas express PPM1D; PPM1D expression is a significant marker of poor prognosis in adult supratentorial diffuse astrocytic and oligodendroglial tumors.

A quantitative assessment of the membrane-integral sub-proteome of a bacterial magnetic organelle

Magnetotactic bacteria produce chains of complex membrane-bound organelles that direct the biomineralization of magnetic nanoparticles and serve for magnetic field navigation. These magnetosome compartments have recently emerged as a model for studying the subcellular organization of prokaryotic organelles. Previous studies indicated the presence of specific proteins with various functions in magnetosome biosynthesis. However, the exact composition and stoichiometry of the magnetosome subproteome have remained unknown.In order to quantify and unambiguously identify all proteins specifically targeted to the magnetosome membrane of the Alphaproteobacterium Magnetospirillum gryphiswaldense, we analyzed the protein composition of several cellular fractions by semi-quantitative mass spectrometry. We found that nearly all genuine magnetosome membrane-integral proteins belong to a well-defined set of previously identified proteins encoded by gene clusters within a genomic island, indicating a highly controlled protein composition. Magnetosome proteins were present in different quantities with up to 120 copies per particle as estimated by correlating our results with available quantitative Western blot data. This high abundance suggests an unusually crowded protein composition of the membrane and a tight packing with transmembrane domains of integral proteins. Our findings will help to further define the structure of the organelle and contribute to the elucidation of magnetosome biogenesis. Biological SignificanceMagnetosomes are one of the most complex bacterial organelles and consist of membrane-bounded crystals of magnetic minerals. The exact composition and stoichiometry of the associated membrane integral proteins are of major interest for a deeper understanding of prokaryotic organelle assembly; however, previous proteomic studies failed to reveal meaningful estimations due to the lack of precise and quantitative data, and the inherently high degree of accumulated protein contaminants in purified magnetosomes. Using a highly sensitive mass spectrometer, we acquired proteomic data from several cellular fractions of a magnetosome producing magnetotactic bacterium and developed a comparative algorithm to identify all genuine magnetosome membrane-integral proteins and to discriminate them from contaminants. Furthermore, by combining our data with previously published quantitative Western blot data, we were able to model the protein copy number and density within the magnetosome membrane. Our results suggest that the magnetosome membrane is specifically associated with a small subset of integral proteins that are tightly packed within the lipid layer. Our study provides by far the most comprehensive estimation of magnetosomal protein composition and stoichiometry and will help to elucidate the complex process of magnetosome biogenesis.

A protocol to quantify protein copy number in super-resolution using DNA Origami as a calibration standard

A protocol to quantify protein copy number in super-resolution using DNA Origami as a calibration standard

Quantitative Analysis of Human Red Blood Cell Proteome.

Red blood cells (RBCs) are the most abundant cell type in the human body. RBCs and, in particular, their plasma membrane composition have been extensively studied for many years. During the past decade proteomics studies have extended our knowledge on RBC composition; however, these studies did not provide quantitative insights. Here we report a large-scale proteomics investigation of RBCs and their "white ghost" membrane fraction. Samples were processed using the multienzyme digestion filter-aided sample preparation (MED-FASP) and analyzed using Q-Exactive mass spectrometer. Protein abundances were computed using the total protein approach (TPA). The validation of the data with stable isotope-labeled peptide-based protein quantification followed. Our in-depth analysis resulted in the identification of 2650 proteins, of which 1890 occurred at more than 100 copies per cell. We quantified 41 membrane transporter proteins spanning an abundance range of five orders of magnitude. Some of these, including the drug transporter ABCA7 and choline transporters SLC44A1 and SLC44A2, have not previously been identified in RBC membranes. Comparison of protein copy numbers assessed by proteomics showed a good correlation with literature data; however, abundances of several proteins were not consistent with the classical references. Because we validated our findings by a targeted analysis using labeled standards, our data suggest that some older reference data from a variety of biochemical approaches are inaccurate. Our study provides the first "in-depth" quantitative analysis of the RBC proteome and will promote future studies of erythrocyte structure, functions, and disease.

Abstract 5822: Increase in protein expression and copy number drives the activation of NPY/Y5R pro-survival loop in chemotherapy-treated neuroblastoma

Abstract Neuroblastoma (NB) is a tumor derived from neural crest cells, primitive progenitors of sympathetic ganglia. It accounts for 6-10% of all pediatric cancers with approximately 700 new cases per year throughout the US. Although there are highly effective therapies for patients with low-risk and intermediate-risk disease who have local relapses, recurrent disease in patients with high-risk NB is mostly refractory to therapy. Neuropeptide Y (NPY) is a sympathetic neurotransmitter highly expressed in NB. Its elevated release from tumor tissue is associated with unfavorable clinical outcome. NPY, acting via its Y5 receptor (Y5R), stimulates NB cell survival and chemoresistance, however the mechanisms underlying NPY/Y5R axis activation in these tumors remain unclear. The aim of this work was to investigate the correlation between the expression of NPY and NPY5R proteins and the copy number status of the NPY and NPY5R genes in pre- and post-chemotherapy NB. Eighty-five tissue samples, including specimens from the primary tumors, distant metastases and local relapses, pre- and post-chemotherapy, were collected from the Hospital Pequeno Principe, Parana, Brazil. Protein expression was investigated by immunohistochemistry. Copy number alterations (CNAs) for NPY and NPY5R genes were determined using TaqMan copy number assay. Additionally, FISH analysis was performed to assess MYCN amplification status, a genetic marker of high risk NB. Our results show that elevated extracellular NPY staining, which reflects peptide release, correlates with patients’ age above 18 months, relapse and poor clinical outcome. Moreover, the intensity of NPY staining was increased in chemotherapy-treated NBs, as compared to tumors at diagnosis. However, the differences in NPY CNAs between these samples were not statistically significant. Thus, chemotherapy-induced increase in NPY levels observed in post-treatment NB is driven by its elevated expression rather than genomic changes. For NPY5R, significantly higher level of CNAs was observed in the post-chemotherapy samples (P&amp;lt;0.05), independently of the MYCN status. These findings are in line with previous studies reporting elevated NPY5R expression in chemotherapy-treated NB tumors and cell lines. Therefore, for this receptor genomic changes may play an important role in conferring chemotherapy-driven Y5R up-regulation. Altogether, our results confirm activation of NPY/Y5R pro-survival loop in chemotherapy-treated NB tumors. However, these coordinated increases in the NPY and NPY5R expression levels are driven by different molecular mechanisms. Citation Format: Selene Elifio-Esposito, Akanksha Mahajan, Aline S. Fonseca, Susana Galli, Lucia Noronha, Lisiane C. Poncio, Bonald C. Figueiredo, Joanna B. Kitlinska, Luciane R. Cavalli. Increase in protein expression and copy number drives the activation of NPY/Y5R pro-survival loop in chemotherapy-treated neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5822. doi:10.1158/1538-7445.AM2017-5822

A DNA origami platform for quantifying protein copy number in super-resolution.

Single-molecule-based super-resolution microscopy offers a unique opportunity for quantifying protein copy-number with nanoscale resolution. However, while fluorescent proteins have been characterized for quantitative imaging using calibration standards, similar calibration tools for immunofluorescence with small organic fluorophores are lacking. Here, we show that DNA origami in combination with GFP antibodies is a versatile platform for calibrating fluorophore and antibody labeling efficiency to quantify protein copy-number in cellular contexts using super-resolution microscopy.

Stochastic lattice model of synaptic membrane protein domains.

Neurotransmitter receptor molecules, concentrated in synaptic membrane domains along with scaffolds and other kinds of proteins, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here in detail a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Our work sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.

Protein degradation rate is the dominant mechanism accounting for the differences in protein abundance of basal p53 in a human breast and colorectal cancer cell line.

We determine p53 protein abundances and cell to cell variation in two human cancer cell lines with single cell resolution, and show that the fractional width of the distributions is the same in both cases despite a large difference in average protein copy number. We developed a computational framework to identify dominant mechanisms controlling the variation of protein abundance in a simple model of gene expression from the summary statistics of single cell steady state protein expression distributions. Our results, based on single cell data analysed in a Bayesian framework, lends strong support to a model in which variation in the basal p53 protein abundance may be best explained by variations in the rate of p53 protein degradation. This is supported by measurements of the relative average levels of mRNA which are very similar despite large variation in the level of protein.

Design of five-layer gold nanoparticles self-assembled in a liquid open tubular column for ultrasensitive nano-LC-MS/MS proteomic analysis of 80 living cells.

In this work, for the first time, a liquid open tubular column modified by five-layer gold nanoparticles and linked with C18 (GNPs@C18 ) was designed and fabricated for nano-LC-MS/MS analysis of 80 living cells. Sixty nanometer gold nanoparticles were self-assembled layer by layer on the inner wall of a 20μm id fused-silica capillary. C18 was then linked on the gold nanoparticles to make the liquid open tubular column show hydrophobic character. Enough loading capacities for analysis of 80 living cells, ∼100 fmol for pk-10 and ∼30 fmol for insulin, were obtained with the 2 m × 20μm id five-layer GNPs@C18 open tubular column. The open tubular column was used in an online pretreatment and direct nano-LC-MS/MS analysis system to analyze 80 living HepG2 cells. In total, 650 proteins were identified in triplicate runs. The subcellular localization of the identified proteins showed that our system had no bias toward different cellular compartments. Protein copy number per cell of the identified proteins showed that the detection limit could reach 50 zmol and the abundance of the identified proteins could cover a dynamic range of 6 orders.

Social network architecture of human immune cells unveiled by quantitative proteomics.

The immune system is unique in its dynamic interplay between numerous cell types. However, a system-wide view of how immune cells communicate to protect against disease has not yet been established. We applied high-resolution mass-spectrometry-based proteomics to characterize 28 primary human hematopoietic cell populations in steady and activated states at a depth of >10,000 proteins in total. Protein copy numbers revealed a specialization of immune cells for ligand and receptor expression, thereby connecting distinct immune functions. By integrating total and secreted proteomes, we discovered fundamental intercellular communication structures and previously unknown connections between cell types. Our publicly accessible (http://www.immprot.org/) proteomic resource provides a framework for the orchestration of cellular interplay and a reference for altered communication associated with pathology.

Abstract P1-08-13: The clinical importance of nuclear wild-type p53-induced phosphatase 1(Wip1) expression in breast cancer patients

Abstract Backgrounds; The wild-type p53-induced phosphatase 1(Wip1) is a member of the serine/threonine protein phosphatases, and plays an important role in the nucleus as one of the key components in the DNA damage response network. Wip1 is encoded by the protein phosphatase magnesium dependent 1 delta (PPM1D), sited on locus 17q23. PPM1D gene amplification and/or Wip1 expression have been observed in numerous tumors, including breast cancer. PPM1D is referred to as oncogene, as Wip1 inhibits phosphorylation of p53 and work as a negative regulator in cell death. Inhibition of Wip1 may have an important therapeutic role in suppressing tumor growth and evolution. Aims; We evaluated the expression of Wip1 mRNA, Wip1 protein and PPM1D DNA copy number to clarify the relationship between Wip1 expression and the clinicopathological features and prognosis to determine the biological significance of Wip1. Materials and Methods; Breast cancer cell lines (MCF7, T47D, MDA-MB231, HCC1937, HS578T, BT20 and SKBr3) were used for Wip1 expression analysis and copy number analysis. The specimens were obtained from Japanese breast cancer patients who underwent surgery without neoadjuvant chemotherapy or endocrine therapy in our department. Wip1 mRNA expression was evaluated in 140 cases by quantitative RT-PCR and Wip1 protein expression was evaluated in 192 cases by immunohistochemistry (IHC). The PPM1D DNA copy number was analyzed by genomic PCR in 33 breast cancer cases and by SNP-CGH array (Illumina, Human Omni 2.5-8) in 12 cases. The effects on the cell growth of the Wip1 inhibitor (GSK2830371) were analyzed by the viability assay in MCF7. Results; Wip1 mRNA expression was significantly higher in MCF7, luminal type cell line. There was no significant correlation between Wip1 mRNA expression and prognosis. In IHC, positive nuclear Wip1 protein expression was detected in 21 cases (10.9%). There was no significant correlation between Wip1 mRNA expression and Wip1 protein expression. There was no significant association between the Wip1 protein expression levels and the clinicopathological factors and the prognosis. PPM1D DNA copy number significantly correlated with Wip1 protein expression (p=0.0035). Copy number gain at 17q23 was detected in 6 cases by SNP-CGH array, and all of these six cases showed positive nuclear Wip1 expression. PPM1D copy number gain was not observed in Wip1 negative cases. In the cell viability assay, the MCF7 cell growth was suppressed by Wip1 inhibitor administration. Conclusions;Wip1 protein expression in nucleus is important as oncogene, and its expression may be regulated by PPM1D copy number gain. Wip1 is considered to be the new therapeutic target for breast cancer patients. Citation Format: Inoue Y, Yamashita N, Tokunaga E, Kitao H, Tanaka K, Saeki H, Oki E, Maehara Y. The clinical importance of nuclear wild-type p53-induced phosphatase 1(Wip1) expression in breast cancer patients [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-08-13.

Versatile Super-Resolution Calibration Standard for Quantifying Protein Copy Number

Single molecule based super-resolution microscopy offers a unique opportunity for quantifying protein copy numbers with nanoscale resolution [1,2]. While fluorescent proteins have been extensively characterized for quantitative imaging using calibration standards, similar calibration tools for small organic fluorophores used in conjunction with immunofluorescence are lacking.Within this framework, the development of methods able to access a precise molecular counting of protein copy numbers is essential, clearing the way to address several biological questions using super-resolution techniques such as stochastic optical reconstruction microscopy (STORM).The development of a suitable calibration method represents the best way to address the challenges of molecular counting using super-resolution [3,4]. Within this project, we demonstrate that DNA origami in combination with GFP antibodies is a versatile platform for quantifying protein copy number in immunofluorescence based super-resolution microscopy. We show that this calibration method, besides quantifying the average protein copy number in a cell, allows determining the abundance of various oligomeric states. Furthermore, we apply this calibration method to quantify nucleoporins (NUP107) [5] and molecular motors (dynein intermediate chain) [6] in vivo. Overall, we provide a versatile strategy for quantifying a large number of proteins of interest using various labeling approaches.1. Durisic, N., et al., Single-molecule evaluation of fluorescent protein photoactivation efficiency using an in vivo nanotemplate. Nat Methods, 2014. 11(2): p. 156-62.2. Ulbrich, M.H. and E.Y. Isacoff, Subunit counting in membrane-bound proteins. Nat Methods, 2007. 4(4): p. 319-21.3. Schmied, J.J., et al., DNA origami-based standards for quantitative fluorescence microscopy. Nat Protoc, 2014. 9(6): p. 1367-91.4. Jungmann R. et al. Quantitative superresolution imaging with qPAINT Nature methods doi:10.1038/nmeth.3804 (2016)5. Szymborska, A., et al., Nuclear Pore Scaffold Structure Analyzed by Super-Resolution Microscopy and Particle Averaging. Science, 2013. 341(6146): p. 655-658.6. Derr, N.D., et al., Tug-of-war in motor protein ensembles revealed with a programmable DNA origami scaffold. Science, 2012. 338(6107): p. 662-5.

Single-Molecule Transcription Factor Dynamics in Saccharomyces Cerevisiæ Glucose Sensing

Metabolic processes underlie all forms of life. An organism's ability to utilise chemical energy to stay alive and eventually reproduce is a central feature of life, regardless of organism length scale. To achieve this, an organism must be able to adapt to varying surrounding environmental conditions. Cells respond to external stimuli by releasing kinase cascades along often intricate signalling pathways which regulate cellular function. These chemical signals eventually bring about some cell level response.Brewer's yeast, Saccharomyces cerevisiae is an extremely well characterised eukaryote model organism and many of its signal pathways have been studied extensively. The bulk behaviour of glucose sensing in yeast has recently been well characterised(1) but the dynamics and interaction of individual molecules in the pathway has not. We use several mutant yeast strains with fluorescent protein tags attached to the transcription factors Mig1 and Msn2 and the AMP kinase Snf1.We have developed a novel high speed fluorescence microscope system capable of imaging and tracking diffusing single or small clusters of fluorescent protein molecules. We have combined this with a bespoke microfluidic channel system allowing us to precisely change the extracellular glucose content and study the dynamics of signal transduction along the glucose sensing pathway in yeast. Our novel deconvolution method(2) let us count the total protein copy number by compartment and accurately follow a cascade interaction with transcription factors.1. Bendrioua L, Smedh M, Almquist J, Cvijovic M, Jirstrand M, Goksor M, et al. Yeast AMP-activated protein kinase monitors glucose concentration changes and absolute glucose levels. J Biol Chem. 2014;289(18):12863-75.2. Wollman AJM, Leake MC. Millisecond single-molecule localization microscopy combined with convolution analysis and automated image segmentation to determine protein concentrations in complexly structured, functional cells, one cell at a time. Faraday Discuss. 2015 Jan;184:401-24.

Time-Resolved Single Cell, Sub-Cellular Compartmentalized Proteomics, Combining Precise Microfluidics, Deconvolution and Ultrasensitive Single-Molecule Microscopy

Optical microscopy is emerging as a powerful tool in quantified in vivo proteomics, allowing protein copy number determination in live cells and even sub-cellular compartments, but to date without dynamic information. Here, we have combined a novel microfluidics technology, Fluicell(1) with cell tracking and deconvolution software(2), to create a new high-throughput dynamic proteomics platform, capable of quantifying copy number changes in sub-cellular compartments in live cells in response to extracellular micro-environmental changes. We used a canonical signal transduction pathway in eukaryotic budding yeast cells as a test system to observe the localisation changes of the Mig1 transcription factor between nucleus and cytoplasm in response to extra-cellular glucose concentration changes. Combined with single-molecule Slimfield measurements of the dynamics of individual Mig1 molecular clusters, we find that clusters of Mig1 molecules translocate across the nuclear envelope and bind target genes, enabling a tuneable response to the glucose concentration signal. By combining microfluidics control of the input signal, with molecular quantification of the output on a single cell level, this new platform generates novel insight into the precise mechanisms of cellular processes.1. A. Ainla, G. D. Jeffries, R. Brune, O. Orwar, A. Jesorka, A multifunctional pipette. Lab Chip. 12, 1255-1261 (2012).2. A. J. M. Wollman, M. C. Leake, Millisecond single-molecule localization microscopy combined with convolution analysis and automated image segmentation to determine protein concentrations in complexly structured, functional cells, one cell at a time. Faraday Discuss.184, 401-24 (2015).

Decision Making in an Intracellular Genetic Classifier

A model for an intracellular genetic classifier is introduced and studied to investigate how cellular decision making will function under the stochastic conditions. In particular, this provides a basis to investigate whether a binary classification under the effects of intrinsic noise is still possible. More precisely, a mathematical model of a genetic classifier is derived using a standard approach using Hill functions and its dynamical properties are explored. Classification mechanism is studied considering the effects of low copy number of mRNA and proteins in terms of the degree of cooperativity, inputs and transcription rates. It is shown that the intrinsic noise blurs the separation line between the classification classes, but the influence of stochasticity is qualitatively different for the case of monostable or bistable dynamics. Finally, potential applications are discussed.

Effects of cell-cycle-dependent expression on random fluctuations in protein levels.

Expression of many genes varies as a cell transitions through different cell-cycle stages. How coupling between stochastic expression and cell cycle impacts cell-to-cell variability (noise) in the level of protein is not well understood. We analyse a model where a stable protein is synthesized in random bursts, and the frequency with which bursts occur varies within the cell cycle. Formulae quantifying the extent of fluctuations in the protein copy number are derived and decomposed into components arising from the cell cycle and stochastic processes. The latter stochastic component represents contributions from bursty expression and errors incurred during partitioning of molecules between daughter cells. These formulae reveal an interesting trade-off: cell-cycle dependencies that amplify the noise contribution from bursty expression also attenuate the contribution from partitioning errors. We investigate the existence of optimum strategies for coupling expression to the cell cycle that minimize the stochastic component. Intriguingly, results show that a zero production rate throughout the cell cycle, with expression only occurring just before cell division, minimizes noise from bursty expression for a fixed mean protein level. By contrast, the optimal strategy in the case of partitioning errors is to make the protein just after cell division. We provide examples of regulatory proteins that are expressed only towards the end of the cell cycle, and argue that such strategies enhance robustness of cell-cycle decisions to the intrinsic stochasticity of gene expression.

Tools and limitations to study the molecular composition of synapses by fluorescence microscopy.

The synapse is densely packed with proteins involved in various highly regulated processes. Synaptic protein copy numbers and their stoichiometric distribution have a drastic influence on neuronal integrity and function. Therefore, the molecular analysis of synapses is a key element to understand their architecture and function. The overall structure of the synapse has been revealed with an exquisite amount of details by electron microscopy. However, the molecular composition and the localization of proteins are more easily addressed with fluorescence imaging, especially with the improved resolution achieved by super-resolution microscopy techniques. Notably, the fast improvement of imaging instruments has not been reflected in the optimization of biological sample preparation. During recent years, large efforts have been made to generate affinity probes smaller than conventional antibodies adapted for fluorescent super-resolution imaging. In this review, we briefly discuss the current views on synaptic organization and necessary key technologies to progress in the understanding of synaptic physiology. We also highlight the challenges faced by current fluorescent super-resolution methods, and we describe the prerequisites for an ideal study of synaptic organization.